Avaliação da performance no treino em jogos desportivos coletivos

Transcription

Avaliação da performance no treino em jogos desportivos coletivos
Eduardo André de Azevedo Abade
Avaliação da performance no treino em jogos
desportivos coletivos
Tese de Doutoramento em Ciências do Desporto
Orientador: Professor Doutor António Jaime da Eira Sampaio
Universidade de Trás-os-Montes e Alto Douro
Vila Real, 2014
Eduardo André de Azevedo Abade
Avaliação da performance no treino em jogos
desportivos coletivos
Este trabalho foi expressamente elaborado
com vista à obtenção do grau de Doutor
em Ciências do Desporto de acordo com o
Decreto-lei 115/2013 de 7 de Agosto.
O trabalho apresentado nesta dissertação foi suportado pela Fundação para a Ciência e
Tecnologia (Portugal) bolsa SFRH / BD / 74544 / 2010
Universidade de Trás-os-Montes e Alto Douro
Vila Real, 2014
ii
“Se acha que a educação é cara, experimente a ignorância”
Derek Bok
iii
DEDICATÓRIA
Aos meus pais, Eduardo José Abade e Maria Antonieta Abade e irmão Tiago
Abade. Não há nada melhor que me pudessem ter dado que uma boa educação!
iv
AGRADECIMENTOS / ACKNOWLEDGEMENTS
“A vida deve ser uma constante educação”! Mais uma etapa cumprida com o apoio
indispensável de professores, família e amigos. Para eles o meu sentido agradecimento.
Ao professor Jaime Sampaio pela orientação imaculada. Pela disponibilidade diária
(literalmente), pelo apoio, paciência, espírito crítico e rigor que tão bem o caracterizam.
Não há preço que pague os últimos 4 anos de educação profissional e pessoal que me
prestou. Pelos “ok”, “boa”, “excelente”, “gosto”, “não gosto”, “corrige”…o meu muito
obrigado. A viagem ainda agora começou, espero eu!
Ao Bruno Gonçalves pela preciosa e insubstituível participação neste trabalho. Pelas
horas e horas de conversa, debate, partilha de conhecimento e companheirismo. É difícil
explicar o caminho desde o primeiro “olá, então o que é que fazes aqui no laboratório?”
até hoje. De colega a amigo!
Ao Bruno Figueira e ao Diogo Coutinho pela colaboração em todo o processo, desde
o primeiro dia! O vosso apoio foi fundamental em todos os momentos, bons e menos
bons. Obrigado pela troca de ideias, experiências e conhecimentos. Obrigado pelas
insubstituíveis gargalhadas e brindes Amigos!
À Alexandra e aos professores Nuno Leite, Catarina Abrantes e José Vilaça pelo
contributo científico prestado na elaboração deste trabalho.
Ao professor Carlo Castagna pela fantástica experiência que me proporcionou em
Itália, pela atenção prestada e competência profissional. Agradeço igualmente a sua
colaboração científica na realização deste trabalho.
A todos os colegas (Sara, Nuno, Laura, Rui, Manuel) e professores (Luís Vaz, Vítor
Maçãs, Isabel Gomes, Paulo Vicente) do CreativeLab pela ajuda direta ou indireta que
prestaram na elaboração deste trabalho. Ao Tiago Oliveira um especial obrigado pelo
seu contributo...a pessoa mais apaixonada por Andebol que alguma vez conheci.
Obrigado pelas ideias andebolísticas que partilhaste comigo. Ainda nos vamos cruzar no
retângulo de jogo, como adversários ou colegas de equipa!
Aos professores Paulo Sá e Mário Santos pela total disponibilidade, paciência,
colaboração e apoio prestados durante o processo de recolha de dados. Mas acima de
tudo pela vossa amizade. A vós devo muito do que tenho conseguido alcançar. Temos
com certeza um portfólio de momentos desportivos para mais tarde recordar, mas as
verdadeiras memórias terão sempre os pés debaixo da mesa.
Aos jogadores da ADA/Maia ISMAI pelo irrepreensível contributo dado na realização
deste trabalho. Foram 8 anos de trabalho fantásticos, da base ao topo. É um orgulho
olhar para trás e ver o percurso trilhado até ao presente.
Ao professor Alberto Carvalho por me ter incutido a verdadeira paixão pelo treino
desportivo. Não me esquecerei nunca do passo acelerado e abraço que me deu no
v
momento imediatamente após a defesa da tese de licenciatura. O “obrigado” nunca será
suficiente para agradecer o que tem feito por mim e pelas competências que me tem
transmitido. Obrigado por acreditar.
Ao professor João Paulo Barbosa por me ter ensinado o significado das palavras
“competência” e “empreendedorismo”. Em algum lado teria que estar escrito que seria
meu/nosso orientador do estágio pedagógico. Foi um dos anos mais marcantes da minha
formação académica. Obrigado por ter incentivado a leitura e procura do conhecimento.
Obrigado pelos fantásticos anos que passámos juntos no Andebol.
Aos treinadores José Carlos Ribas, Raquel Silva, Paulo Ribas e Susana Leal pela
troca de experiências proporcionada ao longo de anos. A vossa dedicação ao Andebol é
ímpar.
Às jogadoras do Maiastars, da formação às seniores, por estarem sempre disponíveis
para colaborar. Mas acima de tudo pelo que aprendi com vocês. Proporcionaram-me
aprendizagens e momentos inigualáveis.
Ao professor Nuno Montenegro pelos assertivos e sábios conselhos que me deu
durante o estágio pedagógico. Ainda hoje respeito alguns dos seus mandamentos.
Ao professor Rolando Freitas por ter acreditado no meu valor.
A todos os professores com quem me cruzei. Tive uma tremenda sorte em vos ter como
tutores. Aos meus alunos, porque a melhor maneira de aprender é ensinar.
A toda a minha família, Tios, Primos e Avós por tudo o que significam. Á minha Tia
Isabel pelo carinho sem limites que tem pelo seu sobrinho. Obrigado por tudo
madrinha!
À Filipa, a minha melhor amiga, confidente e companheira. Obrigado pelos constantes
sacrifícios, por estares sempre presente, pelas discussões saudáveis e construtivas…e
pelas fantásticas viagens. Obrigado pelo teu carinho insubstituível!
Ao Carlos, Fernando, Filipe e Tiago (ordem alfabética) pela vossa amizade! Porque
Amigos há poucos…vocês são “aqueles” e sabem-no porquê.
A todos os meus colegas de licenciatura. Pelo que aprendi com vocês e pelos momentos
inesquecíveis que proporcionaram.
A todos aqueles que por lapso não estão aqui mencionados mas que contribuíram de
uma ou outra forma para a conclusão deste trabalho.
vi
RESUMO
O planeamento a curto prazo em jogos desportivos coletivos representa um desafio para
os treinadores, uma vez que o microciclo semanal inclui sessões de treino com objetivos
múltiplos. A necessidade de manter ou melhorar a capacidade física, o desenvolvimento
das habilidades técnicas e o treino tático, convergem numa complexidade de conteúdos
que requer conhecimentos profundos acerca das suas interações, no sentido de otimizar
a periodização e o planeamento do treino. Neste sentido, conhecer os perfis de carga
externa e interna dos jogadores torna-se imprescindível para um planeamento dirigido à
melhoria da performance desportiva.
Uma vez que o treino técnico-tático é incapaz de induzir adaptações neuromusculares
significativas, a primeira parte deste estudo procurou descrever os efeitos agudos que a
adição de sessões específicas de treino de força teve na resposta física, fisiológica e
performance técnico-tática em sessões de treino de Andebol. O treino de força mostrouse influenciador da intensidade do esforço durante a prática dos jogos reduzidos. Os
jogadores passaram mais tempo em zonas elevadas de frequência cardíaca quando
existiu treino de força antecedente. Em sessões de treino com jogos reduzidos 6x6, o
treino de força mostrou-se útil no aumento da intensidade do esforço, não deteriorando a
capacidade de salto. Mesmo antecedendo jogos reduzidos 3x3, o treino de força
promoveu aumentos do tempo passado em zonas elevadas de frequência cardíaca,
assumindo-se como uma ferramenta apropriada para o desenvolvimento da performance
aeróbia em contexto de jogo. No entanto, os treinadores deverão considerar a
possibilidade da ocorrência de mais falhas técnicas e diminuição da eficácia no remate
quando o treino de força antecede sessões de jogos reduzidos com um menor número de
participantes.
A segunda parte desta tese focou-se na avaliação da carga externa durante unidades de
treino de futebol, através da descrição de perfis de performance e métodos de
classificação dos jogadores. Aparentemente, a elevada variabilidade de estímulos é uma
característica transversal às sessões de treino de equipas jovens de elite (sub-15/17/19).
O foco no desenvolvimento de princípios táticos básicos e habilidades técnicas em
idades mais jovens (sub-15) parece diminuir o estímulo fisiológico. Por outro lado, à
medida que a idade biológica avança, os treinadores parecem privilegiar mais situações
de jogo, o que resulta num aumento significativo da intensidade do treino. Esta
vii
tendência foi mais evidente nas unidades de treino de escalões sub-17, constituídas por
jogos reduzidos com poucos constrangimentos que induziram valores mais elevados de
distâncias totais e distâncias percorridas em sprint. Em idades mais avançadas (sub-19),
as interrupções e feedbacks recorrentes da crescente preocupação com os modelos
táticos das equipas parece comprometer o padrão fisiológico competitivo. Esta
descrição dos perfis físicos e fisiológicos foi ainda utilizada para classificar os jogadores
em grupos distintos de performance, em detrimento de critérios comuns como a idade e
posto específico. O estabelecimento de grupos homogéneos reduziu a variabilidade na
resposta ao estímulo, o que permite aos treinadores um controlo mais eficiente das
respostas às cargas de treino.
Palavras-chave: Planeamento a curto prazo; carga interna; carga externa; treino de
força; jogos reduzidos; perfis de performance; andebol; futebol.
viii
ABSTRACT
Short-term planning in team sports is challenging for coaches, since the weekly training
cycles include sessions with multiple goals. The need to maintain or improve the
physical capacity, the development of technical skills and tactical training, represent a
complexity of contents that require a significant knowledge of its interactions in order to
optimize the training processes. In this sense, studying the players’ internal and external
loads profiles is a key issue to establish training programs aimed for the improvement of
sports performance. Technical and tactical training do not induce significant
neuromuscular adaptations. For that reason, the first part of this study described the
acute effects of specific strength training sessions in the physical, physiological,
technical and tactical response during handball small sided games. It was showed that
strength training influenced the intensity of the effort during small sided games. The
players spent more time in higher heart rate zones when there was precedent strength
training. In training sessions that included 6x6 small sided games, strength training was
able to increase training intensity without impairing the vertical jump capacity. Even
when strength training preceded 3x3 small sided games, players experienced more time
in higher heart rate zones. Thus, strength training may be used as an appropriate tool to
develop the aerobic performance in game context. However, coaches should consider
the occurrence of a higher number of technical errors and the deterioration of the shots
efficiency when strength training precedes small sided games with a lower number of
players.
The second part of this thesis focused on the evaluation of the external load during
football training units, using the description of performance profiles and methods of
classifying the players. Apparently, the high variability of stimuli is a key characteristic
of elite young football training sessions (sub-15/17/19). The focus on the development
of basic tactical principles and technical skills in younger ages (sub-15) seems to
decrease the physiological stimulus. On the other hand, as the biological age increases
coaches seem to privilege more game situations, which results in higher training
intensities. This trend was clearer in sub-17 training units that included small sided
games with fewer constraints, inducing higher values of total distances and distances
covered in sprint. In older ages (sub-19), the focus on team tactical principles appears to
require
additional
coaching
intervention,
promoting
more
interruptions
and
compromising the replication of the competitive physiological pattern. This description
ix
of the physical and physiological profiles was also used to classify the players in
different groups of performance, contrasting the traditional criteria of classification
based on age and specific playing position. The establishment of homogenous groups
reduced the variability of the response to stimuli, allowing coaches to have a more
accurate and efficient control on the players’ responses to training loads.
Key words: Short-term planning; internal load; external load; strength training; small
sided games; performance profiles; handball; football.
x
LISTA DE PUBLICAÇÕES E COMUNICAÇÕES
Durante a elaboração desta tese, alguns trabalhos foram publicados, aceites ou
submetidos para publicação em revistas indexadas (ISI) com sistema de arbitragem.
Algumas partes integrantes ou derivadas da tese foram apresentadas em congressos,
publicadas em livros de resumos e em edições especiais de jornais científicos. Foi
também realizada uma visita de investigação.
Artigos em revistas indexadas no ISI com sistema de arbitragem, como primeiro
autor
Abade E, Gonçalves B, Leite N and Sampaio J (2013). Time-motion and physiological
profile of football training sessions performed by under 15, under 17 and under 19 elite
Portuguese players. International Journal of Sports Physiology and Performance.
(Acceptance Date: June 27, 2013, Impact factor = 2.3)
Abade E, Abrantes C, Ibañez J and Sampaio J (Under Review). Acute effects of
strength training in the physiological and perceptual response in handball small-sided
games.
Abade E, Gonçalves B, Vilaca J and Sampaio J (Under Review). Acute effects of
different strength training programs on the vertical jump and technical actions in
handball small-sided games during preseason.
Abade E, Gonçalves B, Silva A, Leite N, Castagna C and Sampaio J (Submitted).
Helping coaches to classify young footballers according to their training performances.
Artigos em revistas indexada no ISI com sistema de arbitragem, como co-autor
Oliveira T, Abade E, Gonçalves B and Sampaio J (Submitted). Physical and
physiological profiles of elite handball players during training sessions and friendly
matches according to playing positions.
xi
Resumos publicados em livros de atas de encontros técnico-científicos
Abade E, Oliveira T, Gonçalves B & Sampaio J (2013). Strength and conditioning for
team sports: an update. Atas do 3º Simpósio Internacional de Força e Condição Física.
ISBN: 978-989-704-142-6
Comunicações orais em congressos técnico-científicos
Abade E (2013). Strength and conditioning for team sports: an update. 3º Simpósio
Internacional de Força e Condição Física. Universidade de Trás-os-Montes e Alto
Douro, Vila Real.
Abade E (2013). Metodologias de treino – novas perspetivas. 4º Congresso
Internacional Handball Project, “Pensar o Andebol em 2030”. Maia, Portugal.
Abade E (2013). Importância e organização do treino de força para performances
desportivas de excelência. Seminário de investigação nos jogos desportivos coletivos.
Universidade de Trás-os-Montes e Alto Douro, Vila Real.
Abade E (2012). Efeitos agudos do treino de força em jogos reduzidos. Seminário
Brainstorming – fundamentos e aplicações à investigação nos jogos desportivos
coletivos. Universidade de Trás-os-Montes e Alto Douro, Vila Real.
Abade E (2012). Efeitos do treino de força e jogos reduzidos na carga de treino em
jogadores de Andebol. VI Seminário técnico-científico da Federação Portuguesa de
Andebol. Maia, Portugal.
Abade E (2012). Treino de potência para jogadores de Andebol. VI Seminário técnicocientífico da Federação Portuguesa de Andebol. Maia, Portugal.
Abade E (2012). A importância do treino de força na prevenção de lesões. VI
Seminário técnico-científico da Federação Portuguesa de Andebol. Maia, Portugal.
Visitas de investigação
FIGC, Settore Tecnico Coverciano – Laboratorio di metodologia dell’allenamento e
biomeccanica applicata al calcio. Federação Italiana de Futebol (FIGC). Coverciano,
Florença, Itália (2013).
xii
OUTRAS PUBLICAÇÕES
Outros trabalhos foram desenvolvidos paralelamente à elaboração desta tese, como
primeiro ou co-autor.
Artigos em revistas indexada no ISI com sistema de arbitragem, como co-autor
Carvalho A, Caserotti P, Carvalho C, Abade E and Sampaio J (2013). Reliability of
concentric, eccentric and isometric knee extension and flexion with the REV9000
isokinetic dynamometer. Journal of Human Kinetics.
Vaz L, Abade E, Fernandes H and Reis V (2013). Cross-training in rugby: a review of
research and practical suggestions. International Journal of Performance Analysis in
Sport.
Azevedo R, Mourão P, Abade E and Carvalho A (Under Review). Is it important to
know the load mass in lifting tasks to prevent falls?
Carvalho A, Caserotti P, Carvalho C, Abade E and Sampaio J (Under Review). Effects
of a short time concentric versus eccentric training in electromyography activity and
peak torque of quadriceps.
Carvalho A, Mourao P and Abade E (Under Review). Effects of strength training
combined with specific plyometrics on body composition, vertical jump height and
lower limb strength development in elite male handball players: a case study.
Carvalho A, Carvalho C, Caserotti P, Abade E and Sampaio J (submitted). Effects of a
short-time concentric versus eccentric training and detraining in the peak torque of
quadriceps and hamstrings.
Carvalho A, Abade E, Carvalho C and Sampaio J (Submitted). Reliability of
Electromyography and peak torque during maximum voluntary concentric, isometric
and eccentric contractions of quadriceps muscles in healthy subjects.
Resumos publicados em livros de atas de encontros técnico-científicos
Carvalho A, Mourão P, Resende R, Abade E. and Carvalho C (2013). Comparison of
anthropometric profiles between different senior male Volleyball competition levels:
xiii
national team, first and second Portuguese divisions. 18th annual Congress of the
European College of Sport Science. Barcelona, Spain. ISBN: 978-84-695-7786-8.
Carvalho C, Mourão P, Sá P, Abade E and Carvalho A (2013). Comparison of
anthropometric profiles between different senior male Basketball competition levels:
first, second and third Portuguese divisions. 18th annual Congress of the European
College of Sport Science. Barcelona, Spain. ISBN: 978-84-695-7786-8
Mourão P, Abade E, Martins D, Gonçalves F, Carvalho A and Viana J (2012).
Effectivness of a neuromuscular and proprioceptive combination training program in
preventing injuries in youth soccer players. In International Seminar on Physical
Activity and Related Injuries. University of Trás-os-Montes e Alto Douro, Vila Real.
Acta Med Port, 25, 9. ISSN:0870-399X, e-ISSN:1646-0758
Carvalho A, Abade E, Carvalho C and Mourão P (2012). Is isokinetic conventional
ratio “Hcc:Qcc” a good indicator of injury?. In International Seminar on Physical
Activity and Related Injuries. University of Trás-os-Montes e Alto Douro, Vila Real.
Acta Med Port, 25, 8. ISSN:0870-399X, e-ISSN:1646-0758
Comunicações poster em congressos técnico-científicos
Carvalho A, Mourão P, Resende R, Abade E and Carvalho C (2013). Comparison of
anthropometric profiles between different senior male Volleyball competition levels:
national team, first and second portuguese divisions. 18th annual Congress of the
European College of Sport Science. Barcelona, Spain.
Figueira B, Gonçalves B, Coutinho D, Abade E, Freitas R, Leite N, and Sampaio J
(2013). O perfil físico e fisiológico da competição pode classificar jovens futebolistas!
8º Seminário de Desenvolvimento Motor da Criança. Universidade de Trás-os-Montes e
Alto Douro, Vila Real.
Sá P, Carvalho A and Abade E (2013). O jogador especialista na defesa de Andebol. 2º
Congresso internacional de treino desportivo. Instituto superior da Maia. Maia,
Portugal.
Carvalho C, Mourão P, Sá P, Abade E and Carvalho A (2013). Comparison of
Anthropometric Profiles between different senior male Basketball competition levels:
xiv
first, second and third Portuguese divisions. 18th annual Congress of the European
College of Sport Science. Barcelona, Spain.
Sá P, Carvalho A and Abade E (2013). Análise e preponderância do contra-ataque no
jogo de Andebol. 2º Congresso internacional de treino desportivo. Instituto superior da
Maia. Maia, Portugal.
Coutinho D, Gonçalves B, Figueira B, Abade E, Oliveira T, Maçãs V, and Sampaio J
(2013). Variação do perfil físico e fisiológico de jovens futebolistas ao longo de uma
competição concentrada. 8º Seminário de Desenvolvimento Motor da Criança.
Universidade de Trás-os-Montes e Alto Douro, Vila Real.
Abade E, Silva B, Santos F and Sá P (2012). Strength training methodologies applied to
elite handball teams. 9º Congresso técnico-científico de Andebol. Universidade
Lusófona, Lisboa, Portugal.
Carvalho A, Mourão P, Abade E and Carvalho C (2012). Power and explosive strength
comparison between men volleyball national team players. 8th International Conference
on Strength Training. Norwegian School of Sport Sciences. Oslo, Norway.
Mourão P, Abade E, Martins D, Gonçalves F, Carvalho A and Viana J (2012).
Effectivness of a neuromuscular and proprioceptive combination training program in
preventing injuries in youth soccer players. Physical activity and related injuries
international seminar. University of Trás-os-Montes e Alto Douro, Vila Real, Portugal.
Carvalho A, Abade E, Carvalho C and Mourão P (2012). Is isokinetic conventional
ratio “Hcc:Qcc” a good indicator of injury?. Physical activity and related injuries
international seminar. University of Trás-os-Montes e Alto Douro, Vila Real, Portugal.
Carvalho A, Abade E, Mourão P and Carvalho C (2012). Efeitos de um programa de
treino de força combinado com pliometria específica na composição corporal, impulsão
vertical e força dos membros inferiores em jogadores seniores de andebol. Congresso
internacional de treino desportivo. Instituto Superior da Maia, Portugal.
Carvalho A, Mourão P and Abade E (2012). Comparação da força explosiva e reativa
entre atletas pertencentes à seleção nacional masculina de voleibol. Congresso
internacional de treino desportivo. Instituto Superior da Maia, Portugal.
Silva B, Abade E, Santos F and Sá P (2012). Scouting no Andebol. Congresso
internacional de treino desportivo. Instituto Superior da Maia, Portugal.
xv
Santos F, Abade E, Silva B and Sá P (2012). O modelo de jogo numa equipa de
Andebol. Instituto Superior da Maia, Portugal.
Comunicações orais em congressos técnico-científicos
Oliveira T, Abade E, Gonçalves B and Sampaio J (2013). Physical and physiological
profiles of youth elite handball players during training sessions and friendly matches
according to playing positions. 10º congresso técnico-científico da Federação
Portuguesa de Andebol, Universidade Lusófona, Lisboa.
xvi
ÍNDICE
DEDICATÓRIA
IV
AGRADECIMENTOS / ACKNOWLEDGEMENTS
RESUMO
V
VII
ABSTRACT
IX
LISTA DE PUBLICAÇÕES E COMUNICAÇÕES
XI
LISTA DE TABELAS
XX
LISTA DE FIGURAS
XXI
CAPÍTULO 1
23
1.1.
24
INTRODUÇÃO
1.1.1.
A COMPLEXIDADE NOS JOGOS DESPORTIVOS COLETIVOS
24
1.1.2.
MODIFICAR O CONTEXTO PARA OTIMIZAR A APRENDIZAGEM
25
1.1.3.
COMO CONTEMPLAR A COMPLEXIDADE NO TREINO DOS JOGOS DESPORTIVOS
COLETIVOS?
28
1.1.4.
30
DIMENSÕES DOS JOGOS REDUZIDOS
1.1.4.1.
Dimensão muscular
32
1.1.4.2.
Dimensão energética
36
1.1.4.3.
Dimensão técnico-tática
38
1.1.5.
PLANEAMENTO A CURTO PRAZO NOS JOGOS DESPORTIVOS COLETIVOS
43
1.1.5.1.
Efeitos agudos do treino de força nos perfis de performance de andebolistas
43
1.1.5.2.
Variabilidade nos perfis de resposta de jovens futebolistas às cargas de treino
49
1.2.
OBJETIVOS E HIPÓTESES
52
1.3.
REFERÊNCIAS
53
CAPÍTULO 2
2.1
71
ACUTE EFFECTS OF STRENGTH TRAINING IN THE PHYSIOLOGICAL AND
PERCEPTUAL RESPONSE IN HANDBALL SMALL-SIDED GAMES
72
2.1.1
ABSTRACT
72
2.1.2
INTRODUCTION
73
xvii
2.1.3
METHODS
75
2.1.3.1
Subjects
75
2.1.3.2
Design
75
2.1.3.3
Methodology
76
2.1.3.4
Statistical Analysis
77
2.1.4
RESULTS
77
2.1.5
DISCUSSION
79
2.1.6
CONCLUSION
82
2.1.7
REFERENCES
83
CAPÍTULO 3
3.1.
88
ACUTE EFFECTS OF STRENGTH TRAINING PROGRAMS ON THE
VERTICAL JUMP AND TECHNICAL ACTIONS IN HANDBALL DURING
PRESEASON
89
3.1.1.
ABSTRACT
89
3.1.2.
INTRODUCTION
90
3.1.3.
METHOD
92
3.1.3.1.
Participants
92
3.1.3.2.
Procedures
92
3.1.3.3.
Measures
94
3.1.3.4.
Analysis
94
3.1.4.
RESULTS
95
3.1.5.
DISCUSSION
99
3.1.6.
REFERENCES
104
CAPÍTULO 4
4.1.
107
TIME-MOTION AND PHYSIOLOGICAL PROFILE OF FOOTBALL TRAINING
SESSIONS PERFORMED BY UNDER 15, UNDER 17 AND UNDER 19 ELITE
PORTUGUESE PLAYERS
108
4.1.1.
ABSTRACT
108
4.1.2.
INTRODUCTION
109
4.1.3.
METHODS
110
4.1.3.1.
Subjects
110
4.1.3.2.
Design
111
4.1.3.3.
Methodology
111
xviii
4.1.3.4.
Statistical Analysis
112
4.1.4.
RESULTS
113
4.1.5.
DISCUSSION
115
4.1.6.
PRACTICAL APPLICATIONS
118
4.1.7.
CONCLUSION
118
4.1.8.
REFERENCES
120
CAPÍTULO 5
5.1.
123
HELPING COACHES TO CLASSIFY YOUNG FOOTBALLERS ACCORDING
TO THEIR TRAINING PERFORMANCES
124
5.1.1.
ABSTRACT
124
5.1.2.
INTRODUCTION
125
5.1.3.
METHOD
127
5.1.3.1.
Participants
127
5.1.3.2.
Procedures
128
5.1.3.3.
ANALYSIS
129
5.1.4.
RESULTS
130
5.1.5.
DISCUSSION
133
5.1.6.
REFERENCES
136
CAPÍTULO 6
140
6.1.
141
CONCLUSÕES E APLICAÇÕES PRÁTICAS
xix
LISTA DE TABELAS
Table 2.1. Comparing the time spent in HR zones and RPE values according to
the number of players and type of ST. .................................................................. 78
Table 3.1. Chronological schedule that preceded the protocol application .......... 93
Table 3.2. Analysis of Variance to Assess Differences in Vertical Jump
Performance by Number of Players in Small-sided Games, Type of Strength
Training, and Time of Testing. ............................................................................. 97
Table 3.3. Analysis of Variance to Assess Statistical Differences in % of
Technical Actions by Number of Players in Small-sided Games, Type of Strength
Training and Half (only statistical significant differences are presented). ........... 99
Table 4.1. Description of players’ sub-samples. ................................................ 110
Table 4.2. Analysis of distance covered, sprint characterization and body impacts
across age groups. ............................................................................................... 113
Table 4.3. Mean intersection Coefficient of variation (%) according to the age
groups. ................................................................................................................. 115
Table 5.1. Characterization of the cluster groups. .............................................. 130
xx
LISTA DE FIGURAS
Figura 1.1. Modelo de interação de constrangimentos (Newell, 1986)......................... 26
Figura 1.2. Aspetos do treino cognitivo a considerar para a construção de tarefas de
treino (Fajardo, 1999). .................................................................................................... 28
Figura 1.3. Exemplo de um exercício que contempla a colaboração e oposição
característica dos desportos de equipa. Em função da atuação do defensor, o atacante
deve escolher entre o lançamento ou progressão com bola (Fajardo, 1999). ................. 29
Figura 1.4. Mudanças na resposta da capacidade força em 3 tipos de treino. Os registos
dos grupos do treino de força e treino de força + resistência foram semanais. O grupo do
treino de resistência foi avaliado no início e final do protocolo (Hickson, 1980). ......... 33
Figura 1.5. Valores médios (%FC máxima) da intensidade do exercício em diferentes
situações de treino de futebol (Hill-Haas et al., 2011). .................................................. 36
Figura 1.6. Abordagem a sistemas complexos utilizada para análise da performance
desportiva (Hughes & Franks, 2004). ............................................................................. 39
Figura 1.7. Duas dimensões da análise do jogo (Volossovitch, 2008). ......................... 40
Figura 1.8. Média ± SD de contactos com a bola em jogo 4x4 e 8x8 de futebol (Jones &
Drust, 2007). ................................................................................................................... 42
Figura 1.9. Os principais fatores responsáveis por determinar o resultado desportivo
(Verkhoshansky, 2006). .................................................................................................. 43
Figura 1.10. Modelo de treino “dois fatores”. O efeito imediato de uma sessão de TF é
caracterizado pelo somatório de dois processos: ganhos na aptidão física e fadiga
(Zatsiorsky & Kraemer, 2006)........................................................................................ 45
Figura 1.11. Intensidade do exercício (% FCmax) em vários formatos de jogos
reduzidos de futebol (Hill-Haas, Dawson, Coutts, & Rowsell, 2009). .......................... 48
Figure 2.1. ST x HR ZONE interaction to the time spent in each one of the four HR
zones (a); PLAYERS x ST x HR ZONE interaction to the time spent in each one of the
four HR zones (b 3x3, b 6x6); PLAYERS x ST interaction to RPE values (c). ............ 79
xxi
Figure 3.1. Results from interaction Players x Strength Training x Time for squat jump
values. LOWER (lower limbs strength training); POS SSG (after small sided games);
POS ST (after strength training); PRE ST (before strength training); TOTAL (upper and
lower limbs strength training); UPPER (upper limbs strength training). ....................... 96
Figure 3.2. Results from interaction Players x Strength Training x Time for counter
movement jump values. LOWER (lower limbs strength training); POS SSG (after small
sided games); POS ST (after strength training); PRE ST (before strength training);
TOTAL (upper and lower limbs strength training); UPPER (upper limbs strength
training). ......................................................................................................................... 96
Figure 3.3. Results from interaction Players x Strength Training x Time for abalakov
jump values. Legend: LOWER (lower limbs strength training); POS SSG (after small
sided games); POS ST (after strength training); PRE ST (before strength training);
TOTAL (upper and lower limbs strength training); UPPER (upper limbs strength
training). ......................................................................................................................... 97
Figure 3.4. Percentage (%) of the height variation from the baseline (PRE ST) to the
interaction Players x Strength Training x Time.............................................................. 98
Figure 4.1. Results from distance covered for each speed zone (a), time spent in each
heart rate zone (b), number of impacts for each intensity zone (c) and distance in
different intensity zones for each 100m covered at very low intensity (d). ................. 115
Figure 5.1. Distribution (%) of players in each cluster considering the players’
development stage and playing position ....................................................................... 131
Figure 5.2. Results from distance covered for each speed zone (i), number of impacts
for each intensity zone (ii) time spent in each heart rate zone (iii) and predictor
importance to all considered variable (iv). Significant differences are identified as: (a)
Cluster 1 vs. Cluster 2; (b) Cluster 1 vs. Cluster 3; (c) Cluster 2 vs. Cluster 3 ............ 132
Figura 6.1. Representação esquemática das principais aplicações práticas (resultados do
presente trabalho).………………………………………………………………….....144
xxii
Capítulo 1
___________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
CAPÍTULO 1
23
Capítulo 1
___________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
1.1.
INTRODUÇÃO
1.1.1. A complexidade nos jogos desportivos coletivos
A essência dos jogos desportivos coletivos (JDC) consiste na imprevisibilidade dos seus
acontecimentos (Glazier, 2010), resultado do grande número de possibilidades de
escolha no decurso de cada jogo, que são únicas e exigem uma adaptação constante dos
jogadores e das equipas. O número de jogadores, as relações que se estabelecem entre
eles, a diversidade de opções que cada um pode tomar e a sua incerteza comportamental
contribuem para que a natureza dos JDC seja complexa (Balague, Torrents, Hristovski,
Davids, & Araujo, 2013).
A complexidade pode ser entendida como uma medida de número de possibilidades
(Bar-Yam, 2003), que no âmbito técnico, tático, físico, psicológico e social dos JDC se
interligam mutuamente (Volossovitch, Dumangane, & Rosati, 2010). Assim, a
complexidade faz apelo à estratégia, ou seja, à arte de utilizar informações que surgem
durante a ação, integrá-las e formular esquemas capazes de reunir o máximo de certezas
para defrontar o incerto (Morin, 1992). Apesar do equilíbrio, desequilíbrio, organização,
interação e a incerteza serem características da complexidade, esta não significa
obrigatoriamente desordem (Volossovitch et al., 2010). Um dos princípios da
complexidade, o da auto-organização, descreve que todos os seres vivos são sistemas
dotados de grande complexidade, fruto da riqueza de interações entre as suas partes
constituintes (Bauer, 1999). Este princípio sublinha que tais sistemas são capazes de
resistir às perturbações externas e tirar partido delas para aprenderem e se
reorganizarem (Duarte, Araújo, Correia, & Davids, 2012).
No âmbito dos JDC, os jogadores deverão ser capazes de gerir a desordem resultante
dos constrangimentos decorrentes do jogo, de se adaptar e auto-organizar de forma
dinâmica (McGarry, Anderson, Wallace, Hughes, & Franks, 2002), tomando decisões
adequadas às circunstâncias vigentes e que respeitem o ambiente que as envolve (Bauer,
1999). Assim, a performance nos JDC deve ser o resultado de um processo de treino a
longo prazo que prepare os jogadores para a complexidade que a competição exige
(Sampaio & Maçãs, 2012). Mais, o treino deve estar direcionado para as ações
funcionais, ajustadas ao contexto e orientadas para um objetivo, devendo ser mais
caracterizadas pela eficácia do que pela sua estética (Araujo, Travassos, & Vilar, 2010).
24
Capítulo 1
___________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
Toda a complexidade do processo de jogo pode ser confundida com o comportamento
caótico, que é caracterizado pela sensibilidade às condições iniciais e às pequenas
perturbações. Na sua essência, caos refere-se ao fenómeno a partir do qual os sistemas
compostos por partes que se relacionam, cada uma das quais com as suas próprias
regras de comportamento, podem gerar interações e efeitos não lineares e de certa forma
imprevisíveis (Holbrook, 2003). Assim, o comportamento de um sistema é altamente
influenciado por variações mínimas que podem ocorrer no seu estado inicial, tornandose o seu desfecho impossível de prever (Gleick, 1987). A título de exemplo prático: um
guarda-redes de Andebol ou Futebol pode optar por fazer a reposição de bola para o
jogador A ou B. A decisão de passar a bola para o jogador A pode hipoteticamente
determinar o sucesso na concretização do processo ofensivo, que por sua vez pode
significar a vitória no jogo, a conquista do campeonato e o apuramento para uma
competição internacional. Por outro lado, o passe para o jogador B poderia resultar na
perda de posse de bola e consequente insucesso.
O jogo traduz-se numa sequência de eventos organizada de forma catastrófica e que
oscila entre períodos de relativa estabilidade e previsibilidade e acontecimentos
casuísticos geradores de desequilíbrios e do imprevisto (Volossovitch et al., 2010).
Como consequência, o jogo deve ser interpretado de forma dinâmica e auto-organizada
para que se percebam os comportamentos emergentes dos jogadores inseridos num
ambiente ecológico (Gonçalves, Figueira, Maçãs, & Sampaio, 2013). Desta forma, a
análise das interações entre os jogadores e a identificação dos padrões de jogo
emergentes poderão preservar a normal sequência do jogo (Vilar, Araújo, Davids, &
Button, 2012).
1.1.2. Modificar o contexto para otimizar a aprendizagem
O processo de aquisição de skills motores e desportivos tem sido alvo de várias
abordagens teóricas. As teorias mais analíticas estão direcionadas para a psicologia
cognitiva e defendem que a prática repetida ao longo do tempo leva à memorização de
padrões motores estanques (Davids, Araújo, & Shuttleworth, 2005). Por exemplo, a
teoria do processamento de informação defende que a regulação das ações reside na
existência de programas motores genéricos armazenados no sistema nervoso que
especificam o modelo ideal de execução (Temprado & Laurent, 1999). Ao atribuir
25
Capítulo 1
___________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
grande importância aos processos internos do sujeito, a teoria do processamento de
informação desloca o problema da tomada de decisão para uma estrutura interna pré
existente e negligencia o ambiente que envolve a tomada de decisão do jogador (Araujo,
Davids, & Serpa, 2005).
Assim, o controlo da ação deve ser percetivo e não assente numa elevada complexidade
de processos computacionais ou da memória (Shaw, 2003). É neste âmbito que surge a
perspetiva eco-dinâmica da aprendizagem, que refuta os modelos tradicionais e defende
que as ações não são impostas por uma estrutura pré-existente, mas residem no sistema
sujeito-ambiente (Gibson, 1979). De entre os vários fatores capazes de influenciar o
comportamento do sujeito nesse ambiente, destacam-se a estrutura e a física do
envolvimento, a biomecânica do corpo de cada indivíduo, a informação percetual
relativa às variáveis informacionais e as exigências específicas de cada tarefa (Warren,
2006) (ver figura 1.1). Assim, os desportistas peritos distinguem-se pela capacidade de
encontrar as informações que, de acordo com as várias possibilidades, lhes permitem
atingir o seu objetivo (Araujo et al., 2005).
Figura 1.1. Modelo de interação de constrangimentos (Newell, 1986).
No entanto, a perspetiva eco-dinâmica não deve ser considerada de forma isolada
(Araujo et al., 2010), uma vez que determinados padrões coordenados podem emergir
entre as partes do sistema de movimento dinâmico através de um processo de auto
organização (Davids, Button, Araujo, Renshaw, & Hristovski, 2006). O processo de
treino não deve ser caracterizado por estímulos e respostas constrangidas por regras prédefinidas cognitivamente pelo jogador, mas sim pela organização funcional de
atividades práticas (Araujo, Davids, & Hristovski, 2006). Cabe assim ao treinador
perceber quais os constrangimentos mais adequados a cada situação e de que forma é
26
Capítulo 1
___________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
que eles influenciam essa organização funcional (Passos, Araujo, Davids, &
Shuttleworth, 2008).
Durante as sessões de treino, os treinadores podem e devem recorrer a múltiplos
parâmetros de ensino que proporcionem a prática de diferentes movimentos e permitam
aos jogadores criarem uma base de experiências que os possa ajudar a construir variados
esquemas de comportamentos (Schmidt & Lee, 1999). No treino de remate de Andebol,
por exemplo, os esquemas utilizados devem incluir o maior número possível de
combinações que exijam mudanças em vários comportamentos com vista à otimização
do gesto técnico (Wagner & Muller, 2008). Respeitando este princípio, o jogador
assimila informação que o ajudará a alterar e ajustar os seus comportamentos em função
de diferentes condições e contextos. No caso particular do remate no Andebol, os
pressupostos para o desenvolvimento deste gesto técnico sugerem que o treino deve
variar parâmetros como velocidade de execução, ponto de largada da bola, ângulo do
braço no remate e facilitação ou handicap da impulsão vertical (Roth, 1989). Assim
como no futebol, onde manipular e constranger gestos técnicos como receção, drible e
remate já mostrou ser benéfico na não-linearidade da aprendizagem e na criação de
padrões de movimentos funcionais durante a prática (Schöllhorn, Hegen, & Davids,
2012). A manipulação destes parâmetros torna os sistemas instáveis e fá-los auto
organizarem-se (Wagner & Muller, 2008), oferecendo ao sujeito a capacidade de reagir
continuamente a novas situações de forma rápida e adequada (Schollhorn, Mayer-Kress,
Newell, & Michelbrink, 2009).
Neste âmbito, o treino diferencial garante a variabilidade da qualidade e quantidade dos
estímulos de exercício para exercício (Schöllhorn et al., 2012), estimulando o jogador a
adaptar-se e a criar uma variedade de padrões de comportamento (Frank, Michelbrink,
Beckmann, & Schollhorn, 2008). A abordagem diferencial tira partido das flutuações
num sistema complexo aumentando-as através de uma “não repetição” e constante
mudança nas tarefas, o que acrescenta perturbações estocásticas (Schöllhorn et al.,
2012). Assim, as flutuações nos subsistemas do sujeito são exploradas mesmo durante a
aprendizagem, aportando-lhe a capacidade de ele próprio encontrar padrões de
performance dependentes do contexto em que está inserido (Frank et al., 2008).
Baseados nestes pressupostos, os jogos reduzidos (JR) assumem-se como uma
ferramenta útil no processo de treino, permitindo ao treinador manipular uma série de
variáveis que influenciam os estímulos dos exercícios, tais como a área de jogo, número
27
Capítulo 1
___________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
de jogadores, feedback do técnico, regime intervalado ou contínuo, regras e uso de
guarda-redes (Hill-Haas, Dawson, Impellizzeri, & Coutts, 2011). As vastas
possibilidades de constrangimentos aplicados aos JR facilitam o desenvolvimento de
habilidades técnico-táticas e melhoria da capacidade física em contexto apropriado de
jogo (Little, 2009).
1.1.3. Como contemplar a complexidade no treino dos jogos desportivos coletivos?
As abordagens teóricas ao treino dos JDC têm sofrido alguns avanços que se opõem aos
modelos mais clássicos, que privilegiavam a simplificação do jogo em elementos
isolados, que desconsideravam a sua totalidade complexa e desrespeitavam as suas
inter-relações (Reverdito & Scaglia, 2007). Os JDC são férteis em acontecimentos cuja
complexidade não pode ser prevista antecipadamente, exigindo aos jogadores uma
predisposição estratégica e tática permanentes (McGarry, 2009). Assim, a definição de
objetivos e seleção de exercícios para o treino não deverá ir de encontro à
automatização do gesto através de repetições indeterminadas, porque embora o jogador
possa ir ajustando a execução desse mesmo gesto, não terá um suporte motor
suficientemente amplo para dar a resposta ideal numa qualquer situação competitiva,
que nunca se repete da mesma maneira (Schollhorn et al., 2009). Para que os jogadores
desenvolvam os seus processos cognitivos e sejam capazes de se adaptar aos diversos
cenários competitivos, é necessário atribuir estímulos variados no treino (ver figura 1.2)
em que o jogador procure a resposta ideal de acordo com o contexto e as suas
características (Fajardo, 1999).
Figura 1.2. Aspetos do treino cognitivo a considerar para a construção de tarefas de
treino (Fajardo, 1999).
28
Capítulo 1
___________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
Uma vez que a competição obriga os jogadores a tomar decisões enquanto executam
ações intensas, a procura do rendimento ótimo exige cargas de treino específicas de
intensidade elevada, variadas e que se manifestem em curtos espaços de tempo
(Tenenbaum, LevyKolker, Sade, Liebermann, & Lidor, 1996). Num âmbito mais
específico do treino de força (TF), por exemplo, o treino deverá incluir tarefas que
impliquem tomadas de decisão características da modalidade (Fajardo, 1999) (ver figura
1.3).
Figura 1.3. Exemplo de um exercício que contempla a colaboração e oposição
característica dos desportos de equipa. Em função da atuação do defensor, o atacante
deve escolher entre o lançamento ou progressão com bola (Fajardo, 1999).
Na verdade, o próprio estímulo fisiológico poderá ser manipulado para que a resposta
motora não seja previamente idealizada e processada pelo executante. Assim, para além
da complexidade na tomada de decisão técnico-tática, também a tarefa de força
específica pode ser constrangida para replicar o estímulo fisiológico imprevisível que
caracteriza todas as ações de cooperação-oposição em jogo.
http://www.youtube.com/watch?v=M7aFrylaCvY&feature=youtu.be
29
Capítulo 1
___________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
Numa dimensão técnico-táctica deve-se privilegiar o jogo como elemento fundamental e
recorrer à sua problematização, o que poderá ser feito a partir da manipulação da sua
estrutura organizacional, ou seja, de variáveis como as dimensões do terreno de jogo, o
número de jogadores e as regras (Hill-Haas et al., 2011).
1.1.4. Dimensões dos jogos reduzidos
Algumas características dos JDC como a variabilidade e a imprevisibilidade têm sido
utilizadas com recurso a exercícios específicos que visam determinadas condicionantes
que integram as variáveis do jogo. Os JR são habitualmente praticados em áreas
reduzidas, envolvem um número reduzido de jogadores e utilizam regras modificadas
(Hill-Haas et al., 2011). Uma vez que este tipo de jogos permite a manipulação de
variáveis que podem influenciar a intensidade do exercício e replicar as exigências
competitivas, o aumento da produção científica centrada no estudo dos JR pode
contribuir para uma análise mais detalhada das principais dimensões do jogo: técnicotática, fisiológica e psicológica.
Relativamente à dimensão técnico-tática, os JR facilitam a assimilação de conceitos
técnicos, táticos individuais e táticos coletivos (Owen, 2003). Numa perspetiva de treino
no alto rendimento, é importante decompor o jogo através do uso de diferentes formatos
de JR com alteração do número de participantes (Rampinini, Impellizzeri, Castagna,
Abt, Chamari, Sassi, et al., 2007). De um modo geral, as formas de jogo mais reduzidas
permitem aos jogadores contactos mais frequentes com a bola em diferentes situações
de jogo, o que requer a utilização de habilidades técnico-táticas ajustadas ao contexto
(Capranica, Tessitore, Guidetti, & Figura, 2001).
Numa dimensão fisiológica, a prática dos JR pode ser usada como uma ferramenta para
a melhoria da condição física, uma vez que induz níveis de frequência cardíaca (FC)
próximos dos 90 a 95% da FC máxima (Hoff, Wisloff, Engen, Kemi, & Helgerud,
2002). Estas intensidades elevadas favorecem o desenvolvimento da performance
aeróbia (Helgerud, Engen, Wisloff, & Hoff, 2001), indo de encontro a valores já
verificados em algumas formas de treino intervalado (Impellizzeri, Marcora, Castagna,
Reilly, Sassi, Iaia, et al., 2006). Na verdade, os benefícios obtidos no treino são
máximos quando a intensidade utilizada é similar aquela que se verifica em competição
(Mallo & Navarro, 2008). Adicionalmente, a inclusão de JR nos programas de treino
30
Capítulo 1
___________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
promove respostas e intensidades neuromusculares específicas da modalidade, para
além de aumentar a motivação para realizar as tarefas (Hill-Haas et al., 2011).
Vários estudos sugerem que a resposta fisiológica é afetada pela alteração de algumas
condicionantes do jogo (Fanchini, Azzalin, Castagna, Schena, McCall, & Impellizzeri,
2011a; Kelly & Drust, 2009; Sampaio, García, Maçãs, Ibáñez, Abrantes, & Caixinha,
2007). A duração, tempos de descanso, o número de jogadores, dimensões do terreno,
alteração de regras e feedback por parte do técnico têm um impacto direto sobre os
fatores fisiológicos e psicofisiológicos, refletidos pelos valores de FC e perceção
subjetiva de esforço (PSE1) (Hill-Haas et al., 2011), respetivamente. A avaliação
sistemática destes parâmetros, em conjunto com as ações técnicas e táticas (ATT), pode
contribuir para a obtenção de resultados válidos e mais fiáveis, melhorando
significativamente o processo de treino (Tessitore, Meeusen, Piacentini, Demarie, &
Capranica, 2006). A investigação centrada na manipulação de variáveis e o seu efeito na
resposta fisiológica, psicológica e técnico-tática em JR é abundante no futebol, mas
praticamente omissa no Andebol. Apesar disso, a utilização de JR no Andebol parece
contribuir para o desenvolvimento da capacidade aeróbia em contexto de jogo,
preservando componentes específicos da modalidade como a agilidade, tempos de
reação e coordenação óculo-manual (Buchheit, Laursen, Kuhnle, Ruch, Renaud, &
Ahmaidi, 2009).
Apesar dos JR permitirem uma reprodução fiel do padrão cardiovascular e técnicotático necessário à preparação desportiva dos jogadores (Reilly & White, 2004), replicar
o padrão de solicitação muscular parece bem mais complexo. Para que as adaptações da
força sejam significativas, tanto a nível morfológico como neuromuscular, são
necessários programas de treino que respeitem metodologias específicas. Por exemplo,
para o aumento da massa muscular são necessárias intensidades próximas de 70 a 80%
de uma repetição máxima (Moore, Burgomaster, Schofield, Gibala, Sale, & Phillips,
2004), enquanto as adaptações neurais requerem intensidades entre 90 a 100% de uma
repetição máxima (Takarada, Takazawa, Sato, Takebayashi, Tanaka, & Ishii, 2000).
1
A PSE é um método de avaliação psico-fisiológico da intensidade percebida do esforço, desenvolvido no início dos anos 60 por
Gunnar Borg. Este autor desenvolveu a escala da percepção subjectiva de esforço, considerada fiável e de fácil compreensão, que
tem sido aplicada na monitorização do exercício em populações adultas (ver Borg, 1990 e 1998; Faulkner & Eston, 2008).
31
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1.1.4.1.
Dimensão muscular
Ao contrário do que acontece com a aptidão cardiovascular e ATT, a força muscular
não é suficientemente solicitada através da prática dos JR. Esta ideia é suportada pela
relação entre a PSE e as concentrações de lactato sanguíneo já investigada (Aroso,
Rebelo, & Gomes Pereira, 2004). Neste estudo verificaram-se concentrações de lactato
de 4.9±2.0 e 2.6±1.7 (mmol/L) e valores de PSE de 14.5±1.7 e 13.3±0.9 em jogo 3x3 e
4x4, respetivamente (Aroso et al., 2004). Assim, diferentes formatos de JR induziram
valores elevados de PSE mas não de lactato sanguíneo, o que sugere uma perceção
elevada da intensidade do esforço que não foi correspondida por uma solicitação
muscular significativa. Como já foi referido, adaptações musculares significativas
exigem cargas específicas, só possíveis com recurso a unidades especiais de TF
(Zatsiorsky & Kraemer, 2006). Neste sentido, torna-se importante perceber os efeitos da
interação entre as unidades de TF e as unidades de treino de pavilhão, procurando obter
modelos de periodização que permitam a sua concorrência e produzam melhorias na
performance.
O TF é essencial para se atingir elevadas performances durante a competição. Na
verdade, os objetivos finais do TF passam por aumentar a força e/ou assegurar a sua
conservação nos diferentes períodos do ciclo anual de treino, atingir um
desenvolvimento harmonioso de todos os grupos musculares (Zatsiorsky & Kraemer,
2006) e alcançar elevados índices de força e potência nos movimentos que caracterizam
cada uma das modalidades (Verkhoshansky, 2006). Em suma, o potencial de força deve
ser manifestado com base no princípio da conjugação de ações, ou seja, melhoria da
capacidade física funcional e habilidades técnico-táticas (Verkhoshansky, 2006).
O Andebol é um jogo caracterizado por movimentos complexos com e sem bola,
executados em regimes variáveis de velocidade e força como acelerações repetidas,
sprints, saltos, mudanças de direção e contacto físico entre jogadores (Ronglan,
Raastad, & Borgesen, 2006). A necessidade que o jogador de Andebol tem de realizar
ações de curta duração a alta intensidade reforça o TF como uma ferramenta
indispensável à melhoria da sua performance, ajudando-o na execução de tarefas de
competição que implicam níveis elevados de força aliados a velocidades de execução
rápidas (Ziv & Lidor, 2009). Partindo destes pressupostos e considerando que
adaptações significativas de força exigem sessões de treino específicas, parece evidente
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que a concorrência entre as unidades de TF e as unidades de treino de pavilhão deve ser
cuidadosamente manipulada na periodização e planeamento do treino.
Já foi demonstrado que a adição de sessões específicas de TF máxima ao treino técnicotático de Andebol resulta em ganhos maximais de força e aumento da velocidade de
remate, embora possa comprometer ganhos de força explosiva nos membros inferiores e
resistência de corrida (Gorostiaga, Izquierdo, Iturralde, Ruesta, & Ibanez, 1999).
Aparentemente, o treino conjunto de força máxima e resistência pode inibir a médio
prazo capacidade de produzir força (Hickson, 1980), provavelmente pela dificuldade de
adaptação da estrutura muscular ao treino combinado (Zatsiorsky & Kraemer, 2006).
Figura 1.4. Mudanças na resposta da capacidade força em 3 tipos de treino. Os registos
dos grupos do treino de força e treino de força + resistência foram semanais. O grupo do
treino de resistência foi avaliado no início e final do protocolo (Hickson, 1980).
No entanto, já foram relatados ganhos em ambas as capacidades quando a força foi
treinada separadamente da resistência (Collins & Snow, 1993; Leveritt & Abernethy,
1999). Neste sentido, sugere-se que o treino concorrente de força e resistência pode
resultar em ganhos para ambas as capacidades, desde que os mecanismos de
recuperação sejam respeitados (Wong, Chaouachi, Chamari, Dellal, & Wisloff, 2010).
Apesar destes resultados, o conhecimento acerca da ordem com que se treina a força e
resistência é ainda escasso. Para além disso, a literatura é pobre no que diz respeito aos
efeitos imediatos que TF tem na performance técnico-tática dos jogadores.
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A magnitude e a fonte de fadiga no TF podem variar de acordo com o tipo de contração
muscular (Babault, Desbrosses, Fabre, Michaut, & Pousson, 2006), intensidade
(Linnamo, Newton, Hakkinen, Komi, Davie, McGuigan, et al., 2000), velocidade de
execução (Linnamo, Hakkinen, & Komi, 1998) e tempo de descanso (Pattersson,
Pearson, & Fisher, 1985). Neste sentido, importa perceber quais as adaptações agudas e
crónicas induzidas pelo TF, para que a seleção da localização das sessões nos
microciclos e mesociclos de treino seja criteriosa e salvaguarde uma metodologia
eficiente.
Em relação às adaptações crónicas, o treino de hipertrofia, caracterizado por
intensidades próximas das 10 repetições máximas (Kraemer, Marchitelli, Gordon,
Harman, Dziados, Mello, et al., 1990), promove alterações morfológicas como o
aumento da secção transversal do músculo (Moore et al., 2004) e facilita o aumento da
força muscular (Verkhoshansky, 2006). Contudo, a capacidade de gerar força depende
igualmente das adaptações do sistema nervoso. Assim, o treino de adaptações neurais
requer intensidades próximas dos 90% de uma repetição máxima, para que haja um
maior recrutamento de fibras musculares (Takarada et al., 2000) e melhor sincronização
entre as unidades motoras responsáveis pelo mecanismo de contração muscular
(Fajardo, 1999). Neste sentido, a combinação entre o aumento da massa muscular e o
trabalho de natureza neural é fundamental para que o desenvolvimento da capacidade
força seja significativo. Quando comparadas no tempo, as adaptações induzidas pelos
programas de hipertrofia são mais lentas e tardias do que as verificadas no treino neural
(Sale, 1988). Por esse motivo, as adaptações hipertróficas requerem um maior número
de unidades de treino. Apesar destas investigações sublinharem importantes adaptações
crónicas ao TF, os efeitos agudos que estes programas de treino induzem na
performance dos jogadores de Andebol são pouco explorados na literatura. Esta
escassez de informação dificulta a tarefa dos treinadores na organização semanal do
processo de treino que inclua sessões de TF combinadas com sessões de treino técnicotático. No entanto, existem estudos focados nos efeitos neuromusculares agudos do TF
máxima que podem ajudar a perceber algumas variações nos perfis de desempenho dos
jogadores imediatamente após uma sessão de TF (Babault et al., 2006; Bigland-Ritchie,
1981; McCaulley, McBride, Cormie, Hudson, Nuzzo, Quindry, et al., 2009; Moore et
al., 2004; Sale, 1992).
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Os períodos curtos de recuperação no treino de hipertrofia parecem aumentar o
recrutamento de unidades motoras, apesar do decréscimo da capacidade de gerar força
(Sale, 1992), consequência da fadiga de origem periférica (Moore et al., 2004).
Contrariamente ao treino hipertrófico, a fonte de fadiga observada nos protocolos
neurais parece estar associada a uma falha na ativação do sistema nervoso central
(McCaulley et al., 2009), resultando na diminuição da atividade muscular e deterioração
da produção de força (Bigland-Ritchie, 1981). Para além disso, o treino neural induz
concentrações de lactato significativamente inferiores aos protocolos de hipertrofia,
muito em parte devido aos intervalos de recuperação prolongados entre séries
(McCaulley et al., 2009). Imediatamente após a realização do TF, os protocolos neurais
parecem estimular grande parte das fibras tipo II (Sale, 1992), enquanto os protocolos
de hipertrofia resultam num decréscimo do peak force e capacidade de gerar força,
aumentando no entanto a atividade elétrica dos músculos (McCaulley et al., 2009). Este
fenómeno é conhecido por ineficiência neuromuscular (Deschenes, Judelson, Kraemer,
Meskaitis, Volek, Nindl, et al., 2000) e pode ser um forte sinal de fadiga periférica
(Babault et al., 2006). Para além destes indicadores, também já foi observado que os
processos de recuperação da capacidade de gerar força (24h e 48h) foram mais rápidos
após um protocolo de hipertrofia do que o verificado no neural (McCaulley et al., 2009).
Em suma, tanto os treinos neural como o hipertrófico resultam em fadiga
neuromuscular, provavelmente com origem em diferentes fontes, central e periférica
respetivamente. Quando comparados com outas metodologias de TF, os protocolos de
hipertrofia e adaptações neurais promovem efeitos imediatos na diminuição do
percentual do peak force isométrico e uma quebra na capacidade de gerar força,
enquanto, por exemplo, os treinos de resistência e potência não são capazes de induzir
alterações significativas (McCaulley et al., 2009).
Apesar destas informações poderem e deverem ser consideradas na prescrição de um
plano de treino, já foi sublinhada a escassez de investigação científica focada nos efeitos
agudos do TF nas ações desportivas do jogador de Andebol. O lapso que a literatura
apresenta neste domínio faz com que os técnicos de Andebol não possuam informação
suficiente e válida que lhes permita identificar os momentos mais adequados para a
inclusão do TF no microciclo e/ou unidades de treino.
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1.1.4.2.
Dimensão energética
São várias as investigações que se têm focado nas respostas fisiológicas agudas a JR e
formas intervaladas de treino (Balsom, Gaitanos, Soderlund, & Ekblom, 1999; Dellal,
Chamari, Pintus, Girard, Cotte, & Keller, 2008; Sassi, Reilly, & Impellizzeri, 2004).
Considerando durações de exercício idênticas, as conclusões desses estudos apontam
para a existência de intensidades semelhantes em ambos os formatos. Para além disso,
já se verificaram adaptações semelhantes ao nível da capacidade aeróbia e realização de
exercícios intermitentes com mudanças de direção após um programa de treino de 6
semanas que contemplou JR e regimes de treino intervalado (Reilly & White, 2004). No
entanto, a variabilidade dos estímulos parece ser superior nos JR em comparação com
os exercícios intervalados (ver figura 1.5), provavelmente pela natureza específica das
ações inerentes ao jogo (Hill-Haas et al., 2011).
Figura 1.5. Valores médios (%FC máxima) da intensidade do exercício em diferentes
situações de treino de futebol (Hill-Haas et al., 2011).
Aparentemente, tanto os JR como os regimes de treino intervalado são ferramentas úteis
para o desenvolvimento da performance aeróbia ao longo da época desportiva. Na
verdade, já foi observado que ambos os métodos induziram valores idênticos da
%FCmax e PSE após 12 semanas de treino (Impellizzeri et al., 2006).
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A intensidade do esforço em JR tem sido avaliada sobretudo com recurso à análise da
FC, lactato sanguíneo e PSE (Hill-Haas et al., 2011). Contudo, a FC parece ser a
ferramenta mais privilegiada, sendo considerada um método válido e fiável na avaliação
da intensidade do esforço em vários desportos (Achten & Jeukendrup, 2003). Por
exemplo, já foi mostrado que a resposta fisiológica é influenciada pela alteração de
fatores como a duração do jogo (Duarte, Batalha, Folgado, & Sampaio, 2009), área do
campo (Kelly & Drust, 2009), regras do jogo (Hill-Haas, Coutts, Dawson, & Rowsell,
2010) e número de jogadores (Owen, Twist, & Ford, 2004; Sampaio et al., 2007). Mais,
a relação entre a média dos valores da FC e do consumo de oxigénio (VO2) detetada em
testes laboratoriais é semelhante à relação da FC com o VO2 verificada durante a
avaliação do esforço em JR (Esposito, Impellizzeri, Margonato, Vanni, Pizzini, &
Veicsteinas, 2004).
Apesar da validade desta variável, o tempo exigido para análise e interpretação dos
dados pode representar um constrangimento para os treinadores. Também o lactato
sanguíneo tem sido utilizado com frequência na avaliação da intensidade esforço, no
entanto é considerado um indicador pobre das concentrações de lactato muscular em
atividades de carácter intermitente (Krustrup, Mohr, Steensberg, Bencke, Kjaer, &
Bangsbo, 2006). Deste modo, a PSE apresenta-se como um método simples, não
invasivo e sem custos para a monitorização da intensidade do exercício (Borg, 1982). O
uso da PSE surge assim como uma alternativa válida para quantificar a intensidade do
esforço durante uma sessão de treino (Impellizzeri, Rampinini, Coutts, Sassi, &
Marcora, 2004a).
A PSE pode ser definida como a intensidade subjetiva de esforço, desconforto e/ou
fadiga sentida durante a realização de um exercício físico (Robertson, 2001). A
interpretação fisiológica dos aspetos cardiorrespiratórios, metabólicos e musculares tem
um papel importante na regulação da intensidade do exercício. No entanto, a atividade
desportiva não possui apenas uma componente física. A PSE tem uma natureza
multifatorial que não é mediada apenas por fatores fisiológicos mas também por fatores
psicológicos (Borg, 1982). Neste sentido, a PSE é considerada um indicador
psicofisiológico para a obtenção do grau do esforço físico, integrando informações
como sinais deduzidos do trabalho muscular, cardiopulmonar e do sistema nervoso
central (Robertson, 2000). Para além disso, tem-se mostrado um método simples e
válido na quantificação da intensidade de sessões de treino, quer em esforços de carácter
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Capítulo 1
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contínuo (Foster, Florhaug, Franklin, Gottschall, Hrovatin, Parker, et al., 2001) como
em esforços intermitentes (Impellizzeri et al., 2004a). A avaliação da PSE foi já
sugerida como um método mais apropriado na avaliação da intensidade do esforço do
que a análise individualizada das variáveis fisiológicas (Borg, 1982). No entanto, é
necessário integrar as informações obtidas a partir dos três diferentes tipos de variáveis
de esforço - performance/rendimento, avaliações fisiológicas e respostas de perceção para que os resultados obtidos sejam mais fiáveis.
Aparentemente existe uma relação forte entre as estimativas do esforço percebido e as
concentrações de lactato, o que sugere que o aumento da PSE pode estar relacionado
com o aumento da FC e lactato sanguíneo (Borg, Hassmen, & Lagerstrom, 1987). Na
verdade, já foi demonstrado que a combinação dos dados obtidos pela avaliação da FC e
concentração de lactato no sangue com a PSE apresentou resultados mais fiáveis do que
a análise isolada da FC ou concentração de lactato (Chen, Fan, & Moe, 2002). Em
suma, a PSE está correlacionada com muitas formas de avaliação da intensidade do
exercício, como o consumo de oxigénio, ventilação, frequência respiratória,
concentração de lactato no sangue e FC (Faulkner & Eston, 2008). Em conjunto, todos
estes fatores parecem suportar a PSE como um método fiável na avaliação da
intensidade em esforços intermitentes, os de manifestação mais frequente nos JDC. No
entanto, não existe nenhuma evidência que permita afirmar que um método de avaliação
é mais fiável do que outro, pelo que a monitorização da intensidade nos JR deve ser
feita através da combinação de métodos (Coutts, Rampinini, Marcora, Castagna, &
Impellizzeri, 2009).
Compreender os efeitos que os vários fatores externos têm na intensidade do esforço e
performance técnico-tática pode permitir uma melhor integração dos JR no processo de
treino (Fanchini, Azzalin, Castagna, Schena, Mccall, & Impellizzeri, 2011b). Neste
contexto, a análise do comportamento dos jogadores e das equipas torna-se
preponderante na avaliação, organização e prescrição do treino.
1.1.4.3.
Dimensão técnico-tática
O carácter complexo e multidimensional dos JDC apresenta constrangimentos na
análise do rendimento desportivo, sobretudo porque o seu produto final é influenciado
por fatores físicos, psíquicos e técnico-táticos (Glazier, 2010). Segundo a teoria das
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Capítulo 1
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performances interativas, a performance de uma equipa é afetada pela qualidade e tipo
de oposição, para além de diferentes jogadores serem influenciados pelo mesmo tipo de
oposição de forma distinta (O'Donoghue, 2009). Deste modo, a relação das equipas com
os jogadores adversários torna-se um fator chave na interpretação dos comportamentos
durante o jogo (McGarry, 2009). Todas estas interações fazem com que a performance
desportiva não possa ser avaliada com recurso a dados isolados, sendo necessária uma
abordagem combinada (ver figura 1.6) que considere a complexidade dos sistemas
(Hughes & Franks, 2004).
Figura 1.6. Abordagem a sistemas complexos utilizada para análise da performance
desportiva (Hughes & Franks, 2004).
Apesar das estatísticas do jogo captarem detalhadamente o que se passa em jogo
(Sampaio, Ibanez, Feu, Lorenzo, Gomez, & Ortega, 2008), a investigação científica
atual acrescenta a necessidade de criar modelos multidimensionais para o estudo de
sistemas complexos. A análise da performance deve considerar fatores como o processo
e o resultado (ver figura 1.7), ou seja, a descrição das condutas dos jogadores e sua
39
Capítulo 1
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eficácia no tempo, bem como o resultado final da interação entre as equipas (Grehaigne
& Godbout, 1995). Por exemplo, o enquadramento temporal das ações registadas pode
contemplar o equilíbrio do resultado e as condutas do adversário, para que a perspetiva
global do jogo se rega pelo princípio de que os elementos não têm significado, senão na
sua relação com o conjunto (Volossovitch, 2008). Deste modo, a análise do jogo deve
respeitar uma abordagem dinâmica que interprete a sua realidade complexa (Bar-Yam,
2003).
Figura 1.7. Duas dimensões da análise do jogo (Volossovitch, 2008).
No Andebol, a performance tem sido avaliada com recurso a indicadores como remates
concretizados e falhados da zona dos 9m, da zona dos 6m (pivot e extremos) e em
contra-ataque, assistências, livres de 7 metros conquistados, falhas técnicas no ataque e
diferença entre golos marcados e sofridos (Gruić, Vuleta, & Milanović, 2006; Ohnjec,
Vuleta, Milanovic, & Gruic, 2008). Outros indicadores como a eficácia dos guardaredes, ações defensivas e eficácia do remate em ataque organizado (Magalhães, 1999)
também já foram utilizados com o objetivo de definir indicadores que associassem a
performance à classificação final de provas oficiais da modalidade.
Em conjunto com as habilidades técnico-táticas, a performance do remate também tem
sido referida como um parâmetro chave para o sucesso no Andebol (Hoff &
Almasbalck, 1995). Nesse sentido, a precisão do gesto técnico e a velocidade da bola
são consideradas variáveis decisivas para o sucesso do remate (Fleck, Smith, Craib,
Denahan, Snow, & Mitchell, 1992). O resultado da combinação entre a precisão e
velocidade do gesto define a eficácia do remate, que é determinada sobretudo por
fatores coordenativos, mecânicos e pela força dos membros superiores e inferiores
(Fleck et al., 1992; Gorostiaga, Granados, Ibanez, & Izquierdo, 2005).
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Torna-se evidente que a diversidade de ações que caracteriza o Andebol requer
preparação específica da força (Boraczynski & Urniaz, 2008), uma vez que o treino
desta capacidade tem um impacto significativo na execução de ações fundamentais no
jogo como o sprint e impulsão vertical máxima (Ronglan et al., 2006). O TF com
intensidades elevadas responde à necessidade de produzir níveis elevados de força em
curtos espaços de tempo (Zatsiorsky & Kraemer, 2006) e à máxima velocidade de
execução (Harris, Stone, O’Bryant, Proulx, & Johnson, 2000), indo de encontro aos
requisitos do jogo de andebol (Rannou, Prioux, Zouhal, Gratas-Delamarche, &
Delamarche, 2001). No entanto, uma vez que a execução técnica é uma peça chave para
a otimização dos resultados desportivos, o TF deve englobar exercícios que reflitam o
conjunto de ações motoras, gestos técnicos e grupos musculares mais solicitados na
modalidade (Marques & Gonzalez-Badillo, 2006). Para além disso, o TF deve respeitar
velocidades, acelerações e amplitudes gestuais idênticas às dos gestos competitivos
específicos (Verkhoshansky, 2006).
Em síntese, a performance desportiva é influenciada pelas capacidades técnicas, táticas
e físicas, cabendo aos técnicos a sua inclusão e organização no processo de treino (Jones
& Drust, 2007). Neste âmbito, os JR são reconhecidos como uma estratégia eficiente
para aumentar o tempo de prática efetiva dos jogadores, solicitando em simultâneo as
habilidades técnicas, táticas e capacidades físicas (Rampinini, Impellizzeri, et al., 2007).
Ao contrário do que acontece nos exercícios de corrida, a presença de bola nos JR
parece facilitar o desenvolvimento das habilidades técnico-táticas em contexto de jogo,
uma vez que permite a replicação de movimentos específicos, intensidades e requisitos
técnicos da competição (Gamble, 2004; Little, 2009). As situações de JR aumentam a
frequência e exigência das ATT (Jones & Drust, 2007), verificando-se um aumento do
número de ações nos formatos de jogo com menor número de jogadores (Hill-Haas et
al., 2011). No caso particular do Andebol, os formatos de jogo reduzido parecem
aumentar a frequência individual de passes, receções, remates, desmarcações e
interceções em idades jovens (Ribeiro & Volossovitch, 2004).
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Figura 1.8. Média ± SD de contactos com a bola em jogo 4x4 e 8x8 de futebol (Jones &
Drust, 2007).
* Diferenças estatisticamente significativas.
No entanto, a frequência das ATT não pode considerada de forma isolada na avaliação
da performance de uma equipa, uma vez que o principal objetivo dos JDC deve estar
direcionado para as ações funcionais, ou seja, para a eficácia das ações (Araujo et al.,
2006). No futebol, a comparação de formatos de JR 4x4 e 6x6 mostrou que apesar de ter
sido previsível observar um maior número de ATT no jogo 4x4, a alteração do número
de jogadores não influenciou significativamente a eficácia das ações (Abrantes, Nunes,
Macas, Leite, & Sampaio, 2012). Estes resultados sugerem a realização de investigações
futuras que esclareçam a relação entre a manipulação de constrangimentos da tarefa e a
eficácia das ações. Para isso, é importante não descurar que os modelos de eficácia são
diferentes em cada equipa e em cada jogo, influenciados em parte pelo tipo de oposição,
interação entre jogadores e sistemas utilizados nos processos defensivo e ofensivo
(Vuleta, Milanović, Gruić, & Ohnjec, 2005). Só assim é que o jogo poderá ser analisado
através de uma abordagem dinâmica que considere o processo e contexto em que os
jogadores estão envolvidos.
A importância demonstrada que o TF e a os JR têm no processo de treino de Andebol
acentua a necessidade de investigar os efeitos que a inclusão de ambos tem na
performance dos jogadores. Em particular, o TF com cargas elevadas está associado ao
declínio da força muscular e a manifestações de fadiga agudas (McCaulley et al., 2009),
provocando, por exemplo, a diminuição da eficácia do passe em jogadores de
basquetebol na realização de exercícios analíticos (Lyons, Al-Nakeeb, & Nevill, 2006).
No entanto, a análise isolada de um exercício ou gesto técnico é insuficiente, uma vez
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que desconsidera a complexidade e o carácter multidimensional do jogo. Deste modo,
continuam a ser escassos os dados acerca dos efeitos agudos do TF máxima na
performance técnico-tática em contexto de jogo, em particular no Andebol.
1.1.5. Planeamento a curto prazo nos jogos desportivos coletivos
1.1.5.1. Efeitos agudos do treino de força nos perfis de performance de
andebolistas
O Andebol é uma modalidade dinâmica que requer jogadores velozes, ágeis, resistentes,
coordenados e fortes (Hatzimanouil & Oxizoglou, 2004). No caso particular da força
muscular, ela é responsável por assegurar o desenvolvimento das propriedades
funcionais específicas da modalidade e por promover uma estrutura dinâmica perfeita
das ações motoras (Fleck & Kraemer, 2004). Para além disso, a força muscular é um
pressuposto fundamental para o desenvolvimento da potência, um dos principais
requisitos do rendimento desportivo (Allerheiligen, 1994). Assim, o aumento do
potencial motor impõe exercícios de competição, incluindo os de força, combinados
com velocidades de execução elevadas (Verkhoshansky, 2006). O aumento na produção
de potência é conseguido sobretudo pelo desenvolvimento da capacidade motora, que
por sua vez depende do aumento da capacidade dos sistemas do corpo produzirem
energia e da perfeição dos skills dos jogadores para aplicarem todo o seu potencial
motor em competição (ver figura 1.9).
Figura 1.9. Os principais fatores responsáveis por determinar o resultado desportivo
(Verkhoshansky, 2006).
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Vários estudos demonstram que programas periodizados de TF são determinantes no
desenvolvimento de ações motoras como a impulsão vertical (Christou, Smilios,
Sotiropoulos, Volaklis, Pilianidis, & Tokmakidis, 2006; Gorostiaga, Izquierdo, Ruesta,
Iribarren, Gonzalez-Badillo, & Ibanez, 2004; Luebbers, Potteiger, Hulver, Thyfault,
Carper, & Lockwood, 2003), agilidade e velocidade de deslocamento (Christou et al.,
2006; McBride, Triplett-McBride, Davie, & Newton, 2002; Miller, Herniman, Ricard,
Cheatham, & Michael, 2006). No Andebol, já foi verificado que o TF é preponderante
para o aumento da velocidade de remate (Gorostiaga et al., 1999), o que em conjunto
com a melhoria das ações acima referidas pressupõe que o desenvolvimento desta
capacidade acrescenta a possibilidade de recurso a mais estratégias e táticas por parte
dos jogadores. Deste modo, sem negar a importância de outras capacidades físicas, o
planeamento do TF assume uma elevada preponderância no progresso desportivo,
devendo seguir uma direção lógica para maximizar a performance desportiva
(Verkhoshansky, 2006).
A importância que cada microciclo de força assume na periodização e planificação do
treino varia, principalmente em função de fatores como a frequência do TF, objetivos do
TF, intensidade do TF e variabilidade dos exercícios (Badillo, 2000). Com vista à
obtenção do máximo rendimento, a distribuição e a carga dos exercícios devem ser
parâmetros considerados aquando da prescrição de um programa de TF (Zatsiorsky &
Kraemer, 2006). No entanto, outros constrangimentos se emergem, como a localização
da unidade de TF no microciclo e o tempo de recuperação entre sessões.
Ao contrário do que acontece em modalidades como o halterofilismo e culturismo, no
Andebol não se pode considerar a força como única componente do treino, uma vez que
a necessidade de desenvolver capacidades como a resistência, velocidade e habilidades
técnicas, faz com que o TF se assuma como parte do processo de treino. Assim, é
preciso ter em atenção as dificuldades que o organismo pode ter em se adaptar quando
as solicitações são múltiplas e em simultâneo, correndo-se o risco de obter modificações
insignificantes nas diferentes capacidades motoras (Zatsiorsky & Kraemer, 2006). Neste
sentido, os efeitos da fadiga devem ser interpretados e manipulados de forma cautelosa
durante o planeamento de curta duração(Hansen, Kvorning, Kjaer, & Sjøgaard, 2001).
44
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De acordo com o modelo “ dois fatores” (Zatsiorsky & Kraemer, 2006), o efeito agudo
do TF resulta da combinação de dois aspetos: ganhos na aptidão física (mudanças lentas
na componente motora da performance desportiva) e fadiga (diminuição transitória e
reversível da capacidade de trabalho). Após uma unidade de TF, o potencial de
performance desportiva de um atleta melhora devido aos ganhos de aptidão física mas
deteriora-se devido à fadiga. Assim, o resultado final é o somatório das mudanças
positivas e negativas ocorridas neste processo (ver figura 1.10).
Figura 1.10. Modelo de treino “dois fatores”. O efeito imediato de uma sessão de TF é
caracterizado pelo somatório de dois processos: ganhos na aptidão física e fadiga
(Zatsiorsky & Kraemer, 2006).
Desta forma, os ganhos de aptidão física resultantes de uma sessão de treino de força
são moderados em magnitude mas prolongam-se no tempo, enquanto o efeito da fadiga
é superior em magnitude mas relativamente curto em duração. Este é mais um fator a ter
em conta no estabelecimento de etapas de TF, exigindo aos técnicos conhecimentos
profundos acerca da periodização e planeamento desportivo (Gamble, 2010).
A periodização tradicional, caracterizada pela divisão do programa desportivo anual em
pequenos períodos e unidades de treino, tem sido limitada por uma série de fatores. De
entre eles destacam-se o conflito das respostas fisiológicas produzido pelo treino
dirigido a várias capacidades motoras em simultâneo, a fadiga excessiva provocada por
longos períodos com múltiplos objetivos de treino, o fraco estímulo induzido por cargas
leves/médias e a incapacidade de proporcionar picos de forma ao longo da época
(Issurin, 2008). Como consequência, um planeamento baseado no método tradicional
45
Capítulo 1
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pode resultar em perdas acentuadas na massa magra (Allerheiligen, 1994), força
máxima (Astorino, Tam, Rietschel, Johnson, & Freedman, 2004), potência máxima
anaeróbia (Lorenz, Reiman, & Walker, 2010) e até velocidade máxima (Fleck &
Kraemer, 2004). Desde logo, a aplicação de um método unidirecional não dá resposta às
múltiplas manifestações físicas e técnicas que a performance desportiva na maior parte
das modalidades requer (Zatsiorsky & Kraemer, 2006). Num período preparatório, por
exemplo, a necessidade de desenvolver a capacidade aeróbia e força muscular oferece
limitações à partida, já que são requeridas adaptações específicas a nível fisiológico e
morfológico que podem não ser compatíveis se trabalhadas em simultâneo (Issurin,
2008). Já no período competitivo, a periodização tradicional caracteriza-se pelo
estabelecimento de dois ou três macrociclos (Platonov, 1997). Mais uma vez, este tipo
de organização não satisfaz as exigências dos calendários congestionados que
caracterizam o grosso dos desportos coletivos de alto rendimento (Lago-Penas, Rey,
Lago-Ballesteros, Casais, & Dominguez, 2011).
Durante o período competitivo, os objetivos estão mais relacionados com os aspetos
técnico-táticos do que com o TF (Baker, 2007). Por esse motivo, o principal desafio dos
técnicos passa por manter os elevados níveis de potência muscular adquiridos durante
período preparatório (Porta, Viñaspre, & Morera, 1996). No entanto, a tarefa de
constituir programas de treino que mantenham ou elevem os níveis de força durante a
etapa competitiva é complexa (Wathen, Baechle, & Earle, 2000). Com o objetivo de
ultrapassar estas limitações, o modelo de periodização por blocos propõe quatro
princípios fundamentais de organização: concentração elevada de cargas de trabalho,
um número mínimo de capacidades alvo num só bloco, desenvolvimento consecutivo de
várias habilidades e estabelecimento de mesociclos especializados (Issurin, 2008). Ao
contrário do modelo tradicional no qual várias habilidades são desenvolvidas em
simultâneo, a organização por blocos pressupõe um desenvolvimento consecutivo de
habilidades especificamente selecionadas, compilando um plano anual que deve ser
entendido como uma sequência de estádios autónomos, onde os objetivos são obtidos
através de programas de treino parcialmente renovados(Issurin, 2008).
Tal como já foi referido, a tentativa de obter o máximo proveito do TF obriga a uma
periodização cuidada que exige a consideração de aspetos como a relação entre volume
e intensidade, ordem e sequência dos exercícios (Fleck & Kraemer, 2004). Por exemplo,
se um atleta realizar um exercício para membros inferiores (e.g. agachamento) e um
46
Capítulo 1
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exercício para membros superiores (e.g. supino), o número total de repetições será
superior se a sequência for vertical e inferior quando for horizontal (Zatsiorsky &
Kraemer, 2006), uma vez que solicitar de forma alternada os segmentos permite uma
recuperação mais eficaz (Bompa, 1993).
Apesar destas orientações, a literatura focada na periodização do TF nem sempre tem
em consideração as especificidades dos vários grupos musculares, como as diferenças
em número e tamanho das fibras, conteúdo de glicogénio e ATP, braços de alavanca e
força de contração. Para além de aspetos neurais como a coordenação intramuscular e
intermuscular, os fatores que mais influenciam a capacidade de um músculo gerar força
são o número de fibras musculares e respetiva área de secção transversal (Zatsiorsky &
Kraemer, 2006). Neste sentido, as diferenças de força podem ser justificadas pelo facto
de músculos com maior área de secção transversal terem um maior número de pontes
cruzadas (Orellana & Prada, 2000). De facto, já foi observado que para a mesma
intensidade de carga, jogadores profissionais de futebol foram capazes de executar o
exercício squat com cargas superiores às verificadas no exercício supino (Wisloff,
Helgerud, & Hoff, 1998). Numa outra investigação, verificou-se que após a aplicação de
um programa de TF de 12 semanas, os membros superiores obtiveram ganhos de 15%
relativamente aos obtidos nos membros inferiores (Sousa, Mendes, Abrantes, &
Sampaio, 2011). Apesar de este estudo ter sido realizado com sujeitos idosos, os
resultados sugerem que a menor funcionalidade quotidiana dos membros superiores
permite adaptações mais significativas quando sujeitos a um programa de TF (Enoka,
1988).
As conclusões observadas nestes estudos sugerem que quando sujeitos a intensidades
idênticas, os músculos dos membros inferiores são capazes de suportar cargas mais
elevadas do que os membros superiores. No entanto, a literatura ainda não fundamenta
de forma esclarecedora as diferenças que possam existir na adaptação aguda ao esforço
entre diferentes tipos de TF, dirigidos a membros superiores, inferiores ou a ambos.
Para além disso, não se conhece o modo como estas adaptações se podem refletir na
performance dos jogadores, traduzida pela eficácia das várias ações motoras, técnicas e
táticas. Mais, partindo do pressuposto já fundamentado que os JR devem fazer parte do
processo de treino, também se desconhecem os efeitos da relação e coabitação entre
diferentes tipos de TF e diferentes formatos de JR.
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Capítulo 1
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A intensidade do esforço em JR pode ser analisada através dos movimentos dos
jogadores e/ou respostas fisiológicas/percetuais (Hill-Haas et al., 2011), cabendo ao
treinador selecionar e manipular os constrangimentos que podem influenciar essa
intensidade. De todas as variáveis já investigadas, interessa perceber de que forma é que
a redução do número de jogadores se pode refletir nas ATT, solicitação muscular e
energética. Tal como já foi referido, a utilização de JR permite a replicação de
intensidades de esforço e requisitos técnico-táticos próximos dos perfis de competição
(Little, 2009). A literatura também já mostrou que a redução do número de jogadores
aumenta os valores da FC (ver figura 1.11), lactato sanguíneo e resposta percetual
(Owen et al., 2004).
Figura 1.11. Intensidade do exercício (% FCmax) em vários formatos de jogos
reduzidos de futebol (Hill-Haas, Dawson, Coutts, & Rowsell, 2009).
Apesar de vários estudos se terem centrado na análise das ATT em JR (Capranica et al.,
2001; Duarte et al., 2009; Fanchini et al., 2011b; Jones & Drust, 2007; Kelly & Drust,
2009; Owen et al., 2004), os resultados não têm sido coerentes. Esta incerteza dificulta
o esclarecimento dos técnicos no que diz respeito à relação entre a intensidade do
exercício e o seu reflexo na performance técnico-tática. No entanto, sabe-se que a
prática dos JR induz intensidades de esforço elevadas, requerendo aos jogadores
tomadas de decisão rápidas e sobre o efeito da fadiga (Gabbett & Mulvey, 2008).
48
Capítulo 1
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Dado que fadiga atua nos sistemas nervosos central e periférico, a quebra no controlo
das ações por parte dos jogadores pode estar relacionada com uma má condição física,
em particular com a diminuição da força muscular (Lyons et al., 2006). Partindo do
princípio de que a maioria das atividades motoras que envolvem manifestações de força
e velocidade exigem um elevado estado de excitação para um ótimo desempenho
(Oxendine, 1984), a influência da fadiga sobre estas capacidades pode comprometer a
obtenção do rendimento pretendido (Knicker, Renshaw, Oldham, & Cairns, 2011).
Assim, é indispensável que os treinadores incluam programas específicos de TF no
processo de treino. Na verdade, o TF de alta intensidade contribui para melhoria da
performance desportiva, melhora a eficiência mecânica, diminui os gastos energéticos
(Heggelund, Fimland, Helgerud, & Hoff, 2013), aumenta o limiar anaeróbio (Marcinik,
Potts, Schlabach, Will, Dawson, & Hurley, 1991), reduz a FC de repouso (Antoniazzi,
Portela, & Dias, 1994) e reduz o risco de lesão (Fleck & Falkel, 1986).
A otimização dos processos de treino no Andebol deve considerar a complexidade e a
imprevisibilidade dos seus acontecimentos. A utilização de JR permite a replicação do
perfil fisiológico e padrões técnicos e táticos, preservando a variabilidade das ações em
contexto de jogo. No entanto, estas tarefas ficam aquém das solicitações musculares
requeridas em certos momentos da época desportiva, obrigando os treinadores a recorrer
a sessões específicas de TF. Em suma, a inclusão do TF e JR nos programas de treino
parece ser decisiva para a melhoria da performance dos jogadores, no entanto não se
conhecem os efeitos que a sua coabitação poderá ter no planeamento a curto prazo. A
resposta a esta questão irá esclarecer de forma mais sustentada a influência de sessões
específicas de TF na resposta fisiológica, técnica e tática dos jogadores em JR. Desta
forma, será aportado conhecimento aos treinadores que lhes permitirá otimizar o
processo de treino.
1.1.5.2. Variabilidade nos perfis de resposta de jovens futebolistas às cargas de
treino
O futebol de elite exige a utilização de processos de treino capazes de dar resposta à
complexidade do jogo e que reproduzam fielmente os seus padrões fisiológicos,
técnicos e táticos. Para que os treinadores possam prescrever cargas de treino que
49
Capítulo 1
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repliquem as exigências competitivas, é necessário identificar os indicadores de
performance que melhor definam o perfil de atividade dos jogadores em competição.
O futebol pode ser descrito como uma modalidade de caráter intermitente com uma
elevada variabilidade de estímulos e intensidades (Rebelo, Brito, Seabra, Oliveira, &
Krustrup, 2012) resultantes da luta pela posse de bola, sprints com mudanças de direção
e tomadas de decisão técnico-táticas (Gonçalves et al., 2013). Os valores de FC máxima
de um jogador durante um jogo de futebol raramente estão abaixo dos 65% (Bangsbo,
Mohr, & Krustrup, 2006), com valores médios e máximos de 85% e 98%,
respetivamente (Krustrup, Mohr, Ellingsgaard, & Bangsbo, 2005). Na verdade, os
jogadores são obrigados a executar ações de alta intensidade que incluem mudanças de
direção com períodos curtos de recuperação (Dellal, Keller, Carling, Chaouachi, Wong,
& Chamari, 2010). Neste sentido, a capacidade de recuperar e produzir ações
subsequentes de alta intensidade é considerada um requisito importante para se atingir
performances de alto nível (Girard, Mendez-Villanueva, & Bishop, 2011).
São vários os parâmetros que devem ser considerados na avaliação dos perfis físicos e
fisiológicos, tais como a FC (Buchheit, Simpson, Al Haddad, Bourdon, & MendezVillanueva, 2012), perceção subjetiva do esforço (Impellizzeri, Rampinini, Coutts,
Sassi, & Marcora, 2004b), capacidade de executar sprints repetidos e mudanças de
direção (P., Chan, & Smith, 2012). Para além destas variáveis, os perfis de tempomovimento têm sido analisados com recurso a sistemas de posicionamento global (GPS)
(Casamichana & Castellano, 2010), considerados válidos para a avaliação da
performance em jogos desportivos coletivos (Coutts & Duffield, 2010). O uso extensivo
desta tecnologia deve-se em parte, ao facto dos aparelhos serem leves, pequenos,
portáteis e permitirem analisar vários jogadores em simultâneo (Aughey & Falloon,
2010). Partindo dos registos de posicionamento, estes instrumentos são capazes de
fornecer dados em tempo real relativos a velocidades de deslocamento, distâncias
percorridas e acelerações, normalmente descritos em função do posto específico
(Bradley, Di Mascio, Peart, Olsen, & Sheldon, 2010), nível de jogo (Mohr, Krustrup, &
Bangsbo, 2003) e idades (Buchheit, Mendez-Villanueva, Simpson, & Bourdon, 2010a).
Por exemplo, a distância total percorrida por jogadores jovens durante um jogo pode
variar entre 4435 e 8098m, sendo que 12% inclui ações de alta intensidade (Rebelo et
al., 2012), valores que tendem a aumentar com a idade (Buchheit et al., 2010a). Os
defesas percorrem menores distâncias em alta intensidade do que os outros jogadores,
50
Capítulo 1
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enquanto os médios e laterais percorrem distancias semelhantes a alta intensidade
(Mohr et al., 2003). Curiosamente, a distância total percorrida durante um jogo está
fortemente correlacionada com a capacidade de realizar sprints repetidos (Rampinini,
Bishop, Marcora, Bravo, Sassi, & Impellizzeri, 2007). Neste sentido, a capacidade de
sprints repetidos é considerada uma qualidade chave na discriminação de jogadores
hábeis tecnicamente (Gabbett, 2010). Mais, as sequências de sprints repetidos e o
número de sprints são afetados pela idade, posto específico e tempo de jogo, sendo que
tendem a diminuir à medida que o jogo avança (Buchheit, Mendez-Villanueva,
Simpson, & Bourdon, 2010b).
As sessões de treino de futebol centram-se em situações jogadas com grande
variabilidade ao nível dos estímulos técnicos, táticos e fisiológicos (Hill-Haas et al.,
2011). Por essa razão, a manipulação de constrangimentos é uma tarefa complexa, uma
vez que as características individuais de cada jogador podem permitir a manifestação de
diferentes comportamentos em resposta a estímulos semelhantes (Chow, Davids,
Hristovski, Araujo, & Passos, 2011).
Muitas competições de equipas jovens organizam-se por escalões etários, no entanto é
importante
considerar
que
a
maioria
das
habilidades
motoras
experiencia
desenvolvimentos significativos durante o período pubertário (Cady, 1984; Côté &
Fraser-Thomas, 2007; Fernandez-Gonzalo, De Souza-Teixeira, Bresciani, GarciaLopez, Hernandez-Murua, Jimenez-Jimenez, et al., 2010). Como consequência, os
perfis físicos e fisiológicos podem variar entre jogadores de idades e tempos de prática
semelhante (Cobley, Baker, Wattie, & McKenna, 2009). Ainda assim, os dados da
performance no treino poderão ser usados para classificar os jogadores e estabelecer
grupos homogéneos para a identificação de talentos e prescrição dos exercícios. Se os
jogadores forem agrupados em função de perfis físicos e fisiológicos semelhantes, a
variabilidade da resposta a nível fisiológico será minimizada, permitindo aos treinadores
ter um controlo mais fiável e eficiente sobre a resposta dos jogadores.
As cargas de treino semanais variam de acordo com as fases do ciclo anual, o que pode
induzir diferentes stresses fisiológicos nos jogadores (Impellizzeri et al., 2004a). O
período pré-competitivo é geralmente associado a maiores intensidades, principalmente
devido à elevada concentração de cargas de treino (Issurin, 2008) e tempo de treino
técnico-tático específico que, regra geral, consistem em JR de alta intensidade e jogos
simulados (Jeong, Reilly, Morton, Bae, & Drust, 2011). Por outro lado, o calendário do
51
Capítulo 1
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período competitivo cria constrangimentos como a recuperação após o jogo e
preparação para o jogo seguinte (Gastin, Fahrner, Cook, Huntsman, Meyer, &
Robinson, 2010). Assim, a principal preocupação dos treinadores durante este período é
manter a capacidade física que os jogadores adquiriram durante o pré-competitivo
(Reilly, 2007). Nesta linha de raciocínio, um estudo com jogadores jovens de elite
mostrou que, no geral, a carga fisiológica da semana de treino foi superior no período
pré-competitivo em comparação com o competitivo, verificando-se valores mais
elevados de FC, mais tempo passado em zonas elevadas de FC e valores elevados de
PSE (Jeong et al., 2011).
Aparentemente, as cargas de treino semanais variam de acordo com a idade,
observando-se um aumento da intensidade em idades mais avançadas, provavelmente
pelo enfoque no desenvolvimento das capacidades físicas e preparação para a
competição (Wrigley, Drust, Stratton, Scott, & Gregson, 2012). Como resultado, os
microciclos são ajustados e adequados a esses objetivos. Por exemplo, a literatura já
mostrou que jogadores sub-18 foram sujeitos a volumes de treino superiores refletidos
por sessões adicionais de campo e ginásio quando comparados com jogadores sub-16 e
sub-14 (Wrigley et al., 2012). De facto, a progressão das cargas físicas de treino é
crucial para o desenvolvimento da performance física e prevenção de lesões (Matos &
Winsley, 2007). Esta tendência parece reproduzir os princípios de treino defendidos
pelo modelo de preparação desportiva a longo prazo, que sugere cargas de treino
estruturadas de acordo com o estado de maturação do jogador (Balyi & Hamilton,
2004).
http://www.youtube.com/watch?v=NEwkkjvs-C8
1.2.
OBJETIVOS E HIPÓTESES
A primeira parte deste estudo teve como objetivo identificar os efeitos agudos que a
adição de sessões específicas de treino de força teve na resposta física, fisiológica e
performance técnico-tática em sessões de treino de Andebol. Neste sentido formularamse as seguintes hipóteses:
o O jogo 3x3 induz valores de FC e PSE mais elevados do que o jogo 6x6;
o Os valores da FC e PSE são superiores quando existe TF máxima antecedente;
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Capítulo 1
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o A IV diminui após a realização do TF máxima;
o A performance técnico-tática é afetada pelo TF antecedente.
A segunda parte do presente trabalho focou-se na avaliação da carga externa durante
unidades de treino de futebol, através da descrição de perfis de performance e métodos
de classificação dos jogadores. Assim, colocaram-se as seguintes hipóteses:
o O impacto fisiológico das sessões de treino tende a aumentar progressivamente
com a idade.
o As distâncias percorridas em treino pelos jogadores sub-19 são superiores às dos
escalões sub-15 e sub-17;
o
Jogadores com idades idênticas apresentam perfis de performance diferentes;
o Agrupar jogadores com perfis físicos e fisiológicos semelhantes reduz a
variabilidade na resposta ao estímulo.
1.3.
REFERÊNCIAS
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CAPÍTULO 2
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2.1
ACUTE
EFFECTS
OF
STRENGTH
TRAINING
IN
THE
PHYSIOLOGICAL AND PERCEPTUAL RESPONSE IN HANDBALL SMALLSIDED GAMES
Eduardo Abade1, Catarina Abrantes1, Sergio Ibáñez2 and Jaime Sampaio1
1
University of Trás-os-Montes e Alto Douro, Research Center in Sport Sciences,
Health and Human Development (CIDESD). Vila Real, Portugal.
2
Faculty of Sports Science, University of Extremadura.
2.1.1 Abstract
The purpose of this study was to identify the acute effects of different strength training
(ST) programs in perceptual and physiological response to handball small-sided games
(SSG). Twelve senior male players participated in the study (age 22.2 ± 3.4, height 1.82
± 0.05 m, weight 80.6 ± 5.38 kg, BMI 24.4 ± 1.33; HR max 195 ± 10.3). The heart rate
(HR) and the rating of perceived exertion (RPE) were measured during SSG (3x3 and
6x6: 4 blocks of 5 minutes each) in a handball half court, with and without precedent
ST. The results showed that ST increased the time spent above 90% HR max (ST x HR
Zone, p < 0.01) and the RPE during handball SSG (PLAYERS x ST, p < 0.05).
Additionally, the ST induced higher HR and RPE values in SSG 3x3 (PLAYERS x ST
x HR Zone, p < 0.01). Thus, including ST before a SSG training unit increases the
external load and induces higher HR values. Coaches may use ST to increase the
workload during 6x6 games and to develop the aerobic performance during 3x3.
Key words: strength training; heart rate; perceived exertion; small-sided games;
handball.
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2.1.2 Introduction
Team sports performance is the result of a complex and dynamic process, with a high
amount of uncertainty, unpredictability and randomness (Volossovitch, Dumangane, &
Rosati, 2010). Therefore, the players must be able to respond to competition requests, to
manage the disorder resultant from the game constraints and to adapt themselves to
emergent situations of cooperation and opposition (Grehaigne & Godbout, 1998). To
this end, the training units should include constraints involving decision-making, tactics
or techniques that respect the appropriate functional environment (Volossovitch et al.,
2010). In this sense, the small-sided games (SSG) are considered as one of the most
useful drills to be used in the training process, allowing the coaches to manipulate
several variables that can modify the exercise stimulus, such as the number of players or
court size (Hill-Haas, Dawson, Impellizzeri, & Coutts, 2011).
From a physiological standpoint, SSG can induce HR values as high as 90 to 95% of
HR max (Hoff, Wisloff, Engen, Kemi, & Helgerud, 2002). In general, most studies
show that reducing the number of players increase the HR, %HR max, blood lactate
concentrations and perceptual response (Hill-Haas et al., 2011). Other studies have
analyzed the time spent in different intensity HR zones (Gore, 2000) and concluded that
reducing the number of players led to intensity increases, reflected by the time spent
above 90% of HRmax (Hill-Haas, Dawson, Coutts, & Rowsell, 2009) and higher RPE
values (Rampinini, Impellizzeri, Castagna, Abt, Chamari, Sassi, et al., 2007).
Despite the high intensities, similar to those observed in some interval training forms
(Dellal, Chamari, Pintus, Girard, Cotte, & Keller, 2008), the variability of stimulus is
higher in SSG, due to the specific nature of actions inherent to these game formats
(Hill-Haas et al., 2011). In fact, the high intensities and variability of stimulus allow
SSG to include action patterns close to competition requests, since physiological,
technical and tactical demands of the game are always present. Although these results
are useful to understand the physiological demands in SSG, most of the investigations
were performed in soccer. The literature is very scarce in handball and additional
cautions should be taken when using the available results.
Even if SSG are able to faithfully reproduce most of the patterns required to players
conditioning (Impellizzeri, Marcora, Castagna, Reilly, Sassi, Iaia, et al., 2006), the
replication of the muscle demands seems much more difficult. Thus, to benefit from
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significant muscular adaptations, it is necessary to use intense and specific external
loads, only available with specific ST (Zatsiorsky & Kraemer, 2006). In fact, the ST is
essential for achieving high performances during competition (Verkhoshansky, 2006)
and there are several studies showing that ST units are decisive to develop motor
actions such as vertical jump (Luebbers, Potteiger, Hulver, Thyfault, Carper, &
Lockwood, 2003), agility and speed (Miller, Herniman, Ricard, C., Cheatham, &
Michael, 2006).
Concurrent training research describes the effects of combining ST and endurancebased training, suggesting that residual fatigue occurs following the endurance
component, compromising the ability of muscles to develop tension during the strength
training (Hennessy & Watson, 1994). Probably for these reasons, it is common that
handball high-level teams organize their weekly practices combining ST in a weights
room immediately followed by technical and tactical training in court using SSGs-based
training sessions. However, the available research is unclear due to differences in design
factors such as mode, intensity, frequency of training and training history of subjects.
For example, there is no research describing ST programs with different muscular
solicitations (i.e., focused on upper limbs, lower limbs or both), neither describing their
acute effects on intermittent exercise, such as simulated game situations. In fact,
combining these two components may lead to conflicting physiological adaptations,
endocrine changes or acute fatigue (Leveritt, Abernethy, Barry, & Logan, 1999).
In regard to the acute responses to different ST programs, it seems possible that
different programs might have different effects. For example, a program based on lower
limbs can have an acute effect of impairing the vertical jump and agility during the
game, a program based on upper limbs can have strong acute impact on passing and
goal shots and a program based on both limbs can have both effects and additional
energy expenditure. All these possible single and interactive effects can be indirectly
addressed by the players’ physiological and perceptual responses during SSGs. In fact,
it was already found deterioration on the performance of some technical skills when the
exercise intensity induced RPE values above 15 (Gabbett, 2008). Because sports
performance depends on the ability to performing at high-levels in physical, technique,
decision making and psychological dimensions (Knicker, Renshaw, Oldham, & Cairns,
2011), it is possible that induced fatigue might affect some of these skills, reducing the
performance during team sport games. Despite the important information provided,
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most research was not carried in game-like situations, neglecting the fact that team
sports performance is grounded in the interactions between the individual and the
dynamic constraints of the environment (Araujo, Travassos, & Vilar, 2010).
In essence, there is no available research describing how different ST programs can
influence handball SSGs’ performance. Revealing the acute effects of ST in SSGs
physiological and technical performances, can help handball coaches to optimize the
training process by selecting and combining ST and SSGs according to their best
interest. Therefore, the aim of the present study is to identify the acute effects of
different ST in physiological and perceptual responses to handball small-sided games.
2.1.3 Methods
2.1.3.1 Subjects
The sample included 12 male handball players (age 22.2 ± 3.4, height 1.82 ± 0.05 m,
weight 80.6 ± 5.38 kg, BMI 24.4 ± 1.33; HR max 195 ± 10.3). All subjects were part of
the same team with seven training units per week (5 handball sessions lasting for 90
minutes and two ST lasting for 60 minutes) and competed in 30 matches per season. A
briefing session took time where it was presented to the players a disclosure document
with all the procedures, benefits and risks associated with participation in this study. All
of them were notified that they could leave the study at any time. This protocol was
approved by the ethics committee of the Research Center in Sports Sciences, Health and
Human Development.
2.1.3.2 Design
The protocol familiarization took place in distinct stages by using ST with external
loads of approximately 50% to 60% of 1 RM (Hakkinen, Pakarinen, Kraemer, Newton,
& Alen, 2000) that included all ST exercises, 33 and 66 in a handball half court (400
m²). Both HR and RPE were monitored in these sessions.
The following week began with the first data collection session (UPPER + SSG 33).
During UPPER, the six players participating in this first part of the study were grouped
in pairs to perform the sequence of a circuit with four stations. The groups organization
allowed a player to rest while the other was performing the exercise, optimizing
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recovery times (Zatsiorsky & Kraemer, 2006). The rotary system provided to all
individuals the same recovery time between the last strength exercise and the beginning
of the SSG 33.
After UPPER, a 20 minutes interval was allowed to set HR monitors on each subject.
After this break, the players performed the 33 SSG (4 blocks of 5 minutes each) with
alternated functions between the attack and defense. At the end of the 4th block, the HR
monitors were gathered and all players filled the RPE values on a printed sheet of paper
to facilitate their decision (Coutts, Rampinini, Marcora, Castagna, & Impellizzeri,
2009). After a period of 72 hours from the first data collection (UPPER + SSG 33), the
protocol was repeated in SSG 33 with no ST. In the three following weeks, the
procedure was identical, only with a different type of ST preceding the SSG. The weeks
5, 6 and 7 followed the same organization and procedures of weeks 2, 3 and 4, however,
the SSG were played in 66. The ST with 12 subjects had exactly the same
methodology and organization.
All SSG took place in an indoor sports court with a total area of 400m² (half court
handball), however, 74.5m² belong to the goalkeeper area, which makes a playable area
of approximately 325.5m². The SSG were played according to the International
Handball Federation (IHF) official rules and the ball used was from size three for senior
males (60cm and 475g - IHF). Several balls were placed at the playing area perimeter so
that it could be immediately restored when leaving the bounding lines (Kelly & Drust,
2009).
2.1.3.3 Methodology
The dependent variables were the time spent in four zones of %HR max and RPE
values. The ST and handball SSG were the independent variables. The ST type was
divided in four intervention levels: no strength training (NONE), strength training for
upper limbs (UPPER), strength training for lower limbs (LOWER) and strength training
for upper and lower limbs (TOTAL). The type of SSG had two levels: SSG 33 and
SSG 66.
Individual HR monitors (Polar Team System, Polar, FI) were used to record HR
continuously during SSG (33 and 66) and to measure HRmax by performing the Yo-
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Yo Intermittent Endurance Test - Level 2 (Bangsbo, 1996). After the implementation of
the protocol, HR data was downloaded to the Polar Precision Performance SW Version 4.01.029 and later exported to a spreadsheet where it was grouped in four zones
of %HR max (Gore, 2000): Zone 1 (<75%), Zone 2 (≥ 75% - 84.9%), Zone 3 (≥ 85% 89.9%) and Zone 4 (≥ 90% - 100%). To determine the maximum dynamic strength the
test of one maximum repetition (1RM) was performed on different days (Brown &
Weir, 2001) for each strength exercise.
During the protocol application, all types of ST were carried according to the
hypertrophic methodology (Zatsiorsky & Kraemer, 2006) with 3 sets of 10 to 12 RM,
low speed execution (4-5 seconds per repetition) and recovery periods of approximately
60 seconds. The perceived exertion was measured by using the Borg Perceived Exertion
Scale (6-20) (Borg, Hassmen, & Lagerstrom, 1987).
2.1.3.4 Statistical Analysis
Data are expressed as means (±S.D). The RPE and technical variables were analyzed
with a 24 repeated measures ANOVA: number of players (33 or 66) and strength
training situation (NONE, UPPER, LOWER, TOTAL). To analyze HR data, the zone
repeated factor (with 4 levels) was included in the model, resulting in a 244 repeated
measures ANOVA. Eta squared values were used as effect sizes. All analyses were
performed using Statistica software version 8 (Statsoft, Tulsa USA) and the significance
level was maintained at 5%.
2.1.4 Results
The table 2.1 presents the results of simple effects comparisons and interactions
between the number of players (33 and 66), types of ST (NONE, UPPER, LOWER
and TOTAL) and time spent in the four HR zones. Also, table 2.1 shows the results of
simple effects comparisons and interactions between the number of players (33 and
66) and types of ST (NONE, UPPER, LOWER and TOTAL) to the RPE values.
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Table 2.1. Comparing the time spent in HR zones and RPE values according to the
number of players and type of ST.
F
p
Ƞ2
Power
0.0
0.972
-
-
ST
4.2
0.013*
0.27
0.81
HR ZONE
7.2
0.001*
0.40
0.97
PLAYERS  ST
0.1
0.980
-
-
PLAYERS  HR ZONE
14.9
0.000*
0.58
1.00
ST  HR ZONE
2.9
0.004*
0.21
0.95
PLAYERS  ST  HR ZONE
6.5
0.000*
0.37
1.00
78.2
0.000*
0.88
1.00
ST
9.2
0.000*
0.46
0.99
PLAYERS  ST
3.3
0.032*
0.23
0.70
Simple effect/Interaction
HR
PLAYERS
RPE
PLAYERS
* Significant difference between conditions (p<0.05)
The ST  HR ZONE interaction identified higher values of time spent in zone 4 when
there was ST. The players spent more time in HR zones 1 and 2 without ST (Fig.2.1a).
Figure 2.1b represents the PLAYERS  ST  HR ZONE interaction. In 33 SSG, ST
(UPPER, LOWER and TOTAL) did not decrease the time spent at the highest intensity
HR zone (Z4, ≥90 – 100%). Regardless of precedent type of ST, players spent more
time in HR zones 1 and 2 during SSG 66. The PLAYERS  ST interaction analysis
shows that the SSG 33 induced greater RPE values than SSG 66. At both SSG, RPE
values were higher when there was precedent ST (Fig. 2.1c).
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Figure 2.1. ST x HR ZONE interaction to the time spent in each one of the four HR
zones (a); PLAYERS x ST x HR ZONE interaction to the time spent in each one of the
four HR zones (b 3x3, b 6x6); PLAYERS x ST interaction to RPE values (c).
2.1.5 Discussion
The purpose of this study was to identify the acute effects of different ST programs in
perceptual and physiological response to handball small-sided games. In general, the
results showed that ST induced higher HR and RPE values in both SSG. The results
also suggest that, during SSG 33, the ST did not decrease the time spent in HR zones
of highest intensity (above 85%HR max). Additionally, the responses identified in 66
SSG presented increased variability.
Our results showed that after the ST, SSG 33 elicited greater HR and RPE values than
those verified in SSG 66. SSG with a reduced number of players seem to induce higher
physiological stimulus, probably due to the larger ratio area per player and the superior
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number of ball contacts. Thus, it is possible that the addition of ST resulted in an
additional muscular stimulus, reflected by the higher values of HR and RPE during SSG
33. Available research, mainly in soccer, presents several factors that may contribute
to increase intensity in SSG, such as the reduction of players number (Capranica,
Tessitore, Guidetti, & Figura, 2001), the greater interaction of the players with the ball
and the opponents (Hill-Haas et al., 2009), the increase of individual technical and
tactical actions and the higher distance travelled with the ball (Katis & Kellis, 2009).
Research focused on the analysis of specific soccer motor skills during SSG (33 and
66) found that the sprint, agility and horizontal jump performances decreased after
both SSG, but mainly in 33 (Katis & Kellis, 2009). The difficulty to perform some of
these motor tasks can be related to the fatigue induced by SSG with a reduced number
of players (Katis & Kellis, 2009). These results confirm that playing handball 33 SSG
elicits a superior physiological stimulus than playing 66. Therefore, SSG 33 can be
used as an important drill to improve the aerobic performance in game context.
In the current results, the addition of ST did not decrease the time spent above 85%
HRmax and the RPE in both SSG. Despite the SSG format, it is possible that the
muscular fatigue induced by ST affected the performance of some motor skills and that
might resulted in higher physiological strain during SSG. Together, the stimulus of both
ST and SSG can elicit neuromuscular mechanisms that might be a handicap to perform
some handball speed, agility and vertical jump based drills. Several studies have found
increases in muscle fatigue immediately after ST with high loads (McCaulley, McBride,
Cormie, Hudson, Nuzzo, Quindry, et al., 2009). It was also verified that ST (70% of
1RM) induced muscular fatigue and decreased muscular torque five minutes after the
training (Ferri, Narici, Grassi, & Pousson, 2006), however, there were not significant
changes in muscle activation and voluntary electromyography activity. This fact may
suggest that peripheral mechanisms play a key role on reducing the muscular strength.
The decrease in the ability to generate power is also justified by the increasing
concentrations of blood lactate during the ST with high intensities (Kraemer,
Marchitelli, Gordon, Harman, Dziados, Mello, et al., 1990). In this context, it has
already been observed an increase in blood lactate concentration of about 10 to 13
mmol/L during a hypertrophic ST (Mero, Leikas, Knuutinen, Hulmi, & Kovanen,
2009).
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Handball is mainly characterized by high intensity but short duration skills, as sprints
and vertical jumps (Rannou, Prioux, Zouhal, Gratas-Delamarche, & Delamarche, 2001).
However, these kind of specific actions are dependent on the ability to generate power
in lower limbs muscles, particularly on the knee extensors, hip extensors and plantar
flexors (Frick, Schmidtbleicher, & Stutz, 1995). Muscle fatigue, high lactate
concentrations and the reduction of muscle torque, seem to lead to lower agility, speed
and jumping ability. Therefore, the current results suggest that ST may contribute to
increase exercise intensity, which supports the higher values of RPE and the time spent
above 85% HR max, as seen when ST preceded SGG. Although under different
conditions, concurrent training research has also found higher HR values in aerobic
interval exercise, when performed after strength training (Alves, Saavedra, Simão,
Novaes, Rhea, Green, et al., 2011).
Our results identified increased variability during 66 SSG, suggesting higher and less
predictable inter-player differences for the same exercise. The SSGs with a higher
number of players resulted in a decrease of individual contacts with the ball and,
therefore, the physiological pattern becomes more intermittent, e.g., the high intensity
actions are interspersed with low intensity actions with less predictable durations.
Contrarily to the intermittent running exercises, the players’ activity during SSG cannot
be controlled by coaches, as there are factors which influence the physiological
responses and promote these heterogeneous intensities (e.g., the inclusion of
goalkeepers (Dellal et al., 2008), number of contacts with the ball (Capranica et al.,
2001), running without the ball (Katis & Kellis, 2009), the specific positioning and the
opponents behavior (Stolen, Chamari, Castagna, & Wisloff, 2005)). In fact, the higher
variability in SSGs when compared to intermittent run exercises was already identified
(Dellal et al., 2008).
The issue of selecting the most compatible level of ST in combination with the used
SSGs is complex. One of the first physiological adaptations to exercise is the
catecholamine responses, which can influence skeletal muscle force and metabolic
activity (Fry, Kraemer, Vanborselen, Lynch, Triplett, Koziris, et al., 1994). Also, the
mechanisms of fatigue are related to several metabolic factors (e.g. adenosine
triphosphate, inorganic phosphate, phosphocreatine, lactate), diminished glucose or
glycogen availability, ionic factors (e.g. K+, Na + , Ca2+, Cl - ), acidosis (Fitts, 1994),
hypoxia (Amann, Romer, Pegelow, Jacques, Hess, & Dempsey, 2006), reactive oxygen
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species and/or ultrastructural damage (Byrne, Twist, & Eston, 2004). In single terms
and probably interactively, the symptoms underlying these mechanisms are peripheral
and central fatigue, afferent feedback, diminished time to exhaustion, increased RPE,
impaired motor skill outcomes and decision-making (Knicker et al., 2011). Therefore,
from the current results, it might be possible to suggest that 3x3 SSG seems to promote
intensities above 85% HR max regardless of the preceding ST (UPPER, LOWER,
TOTAL). The 6x6 SSG, however, does not seem to induce high intensities when there
was no preceding ST. In this case, the TOTAL ST was the most effective in increasing
intensity.
In addition, our results show that players spent more time in lower HR zones (<75% and
≥75% - 84.9%) when there was no ST. It is possible that the lower muscular stimulus
may be a handicap to reach similar intensities to those verified in competition. Handball
games can elicit average %HRmax values of 85% (Loftin, Anderson, Lytton, Pittman,
& Warren, 1996), thus the lack of ST can compromise, mainly in 66, the replication of
significant physiological demands in SSG.
All ST levels (UPPER, LOWER and TOTAL) were able to promote high HR and RPE
values, therefore, ST in general can be used to reach high intensities in training. Adding
together, HR and RPE values show that the SSG implies high physiological loads,
especially when there is precedent ST.
2.1.6 Conclusion
The main findings of this study demonstrate that the ST can influence the overall
intensity during SSGs. For example, the inclusion of a ST before a SSG training unit
increases the external load and induces higher HR values than those verified in SSG
without precedent ST. Despite of the high intensity verified at both SSG, the 33 format
provided higher HR values. Thus, coaches can use ST as a useful tool to induce higher
intensities during training sessions, enabling the development of aerobic performance in
a game situation. When using SSG 66, coaches should consider the TOTAL program
as more effective to increase the physiological stimulus. However, the possibilities of
other ST methods induce different effects to those found in this study, requires further
research. The data collected from this investigation may provide useful information to
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coaches, helping them to organize and plan microcycles that includes co-existence of
SSG and ST.
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CAPÍTULO 3
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3.1.
ACUTE EFFECTS OF STRENGTH TRAINING PROGRAMS ON THE
VERTICAL JUMP AND TECHNICAL ACTIONS IN HANDBALL DURING
PRESEASON
Eduardo Abade1, Bruno Gonçalves1, José Vilaça1 and Jaime Sampaio1
1 University of Trás-os-Montes e Alto Douro, Research Center in Sport Sciences,
Health and Human Development (CIDESD). Vila Real, Portugal.
3.1.1. Abstract
The aim of this study was to identify the acute effects of hypertrophic strength
training programs on the vertical jump and technical actions in small-sided handball
games during preseason. 12 senior male players (M age = 22.2 yr., SD = 3.4)
participated in 3x3 and 6x6 small-sided games preceded by no strength training or
upper limbs/ lower limbs/ upper + lower limbs strength training. The results showed
that strength training can affect the vertical jump performance and the effectiveness of
some skills towards the end of the small-sided games duration. The higher
physiological stimuli during 3x3 promote the deterioration of some skills’ proficiency,
mainly during small-sided games with preceding strength training. The 6x6 elicits
higher cooperation and interaction between players and potentiates the vertical jump
performance after strength training.
Key words: strength training; preseason; vertical jump; technical skills; small-sided
games; handball.
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3.1.2. Introduction
Handball is characterized by repeated accelerations, sprints, jumps and repeated changes
of direction that involve a great amount of body contact between players. Such demands
may affect the physical performance of players during competition, elicit high fatigue
and increase the risk of injury (Zebis, Bencke, Andersen, Alkjaer, Suetta, Mortensen, et
al., 2011). Muscle strength and power in the pelvis, upper, and lower extremities are
determinant factors in specific handball actions such as the jump throw (Wagner,
Pfusterschmied, Tilp, Landlinger, von Duvillard, & Muller, 2012). Strength training is a
key factor to obtain high level performance and it is essential to developing the vertical
jump (Luebbers, Potteiger, Hulver, Thyfault, Carper, & Lockwood, 2003). However,
adequate inclusion of strength training in the annual cycle of handball training is a
complex issue, due to the diversity of contents to be trained in a concentrated
competitive schedule (Verkhoshansky, 2006). Apparently, to promote maximum
performance and to diminish the possibility of injury, most strength training loads
should be in the first half of the preseason (Bompa, 1993). For team sports like
handball, the goal of strength training should be the development of the muscle strength
and strength endurance during the preseason (Issurin, 2010), immediately before the
maximum strength adaptations (Bompa, 1993).
Hypertrophic training is commonly used to promote structural changes in the muscle
morphology and cross sectional area that support greater gains in muscle strength
(Verkhoshansky, 2006). However, these structural changes are slower than neural
adaptations (Sale, 1988), which may be a constraint when planning a handball
preseason that usually lasts from four to six weeks. The preseason training demands for
high volume and diversified exercises to develop physical and technical abilities in a
short period of time (Issurin, 2010). Therefore, coaches should cautiously organize their
weekly schedule to prevent for conflicting physiological responses.
The performance in handball can be measured with scoring (e.g., goals) and
performance indicators (e.g., successful or unsuccessful passes) (Hughes & Bartlett,
2002) during small-sided games. These situations can be manipulated to influence
physiological, technical, and tactical stimuli (Hill-Haas, Dawson, Impellizzeri, &
Coutts, 2011) and allow for functional movement behaviors to emerge (Pinder, Davids,
& Renshaw, 2012). Small-sided games seem to increase the frequency of technical
actions, specifically when performed with a small number of players (Hill-Haas, et al.,
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2011). Additionally, the variability of stimuli allows small-sided games to include
action patterns similar to competition requests, since physiological, technical, and
tactical demands of the game are strongly replicated. Therefore, small-sided games are
vital to the development of skills in game-like situations and to optimize the training
process during the preseason. However, small-sided games do not appear to provide
significant muscle demand, i.e., specific external loads that induce considerable
neuromuscular adaptation (Zatsiorsky & Kraemer, 2006). Consequently, the preseason
should include both small-sided games and strength training to maximize the players’
technical and physical performance.
Strength training is essential for improvement of critical handball motor actions such as
the vertical jump (Marques & Gonzalez-Badillo, 2006). Vertical jump ability has been
related to muscle contractile mechanisms, maximal force capacity, rate of force
development, muscle coordination, and the stretch-shortening cycle (Rimmer &
Sleivert, 2000). These neuromuscular patterns reproduced during the vertical jump
performance can be found in handball-specific defensive (e.g., blocking) and offensive
movements (e.g., jump shots). Therefore, the vertical jump is recognized as a useful
index of the muscular ability to generate power and can be used to monitor performance
as well as to provide important information about the functional ability of lower limbs
under different conditions (Quagliarella, Sasanelli, Belgiovine, Moretti, & Moretti,
2010). Regardless of the recent investigation of the acute effects of strength training
(Babault, Kouassi, & Desbrosses, 2010) and acute fatigue in response to handball match
play (Thorlund, Michalsik, Madsen, & Aagaard, 2008), the available literature does not
describe the effects of strength training programs with different muscular solicitations
(i.e., focused on upper limbs, lower limbs or both) on players’ performance in game-like
situations. Additionally, there is no research relating the acute effects of combining both
strength training and small-sided games in technical and vertical jump performance
during a handball preseason. Such information could provide coaches important
information for planning short-term programs including both small-sided games and
strength training. Therefore, the goal of the present study is to identify the acute effects
of different strength training in the skill and vertical jump performance to handball
small-sided games.
Hypothesis 1. A significant decrease in the vertical jump performance is expected
immediately after the strength training.
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Hypothesis 2. Greater deterioration of the vertical jump is expected after 3x3 smallsided games.
Hypothesis 3. Maximum strength training is expected to impair technical performance
during small-sided games.
3.1.3. Method
3.1.3.1.Participants
Twelve male senior handball players who competed in the Portuguese second division
volunteered to participate in this study. All participants were part of a team with an
average of eight hours of training per week (M age = 22.2 yr., SD=3.4; M height =1.82
m, SD = 0.05; M weight 80.6 kg, SD = 5.38; M BMI = 24.4, SD = 1.33; M HR max =
195 bpm; SD = 10.3). The participants agreed with the protocol description and were
aware of its benefits and risks. They were also notified that they could withdraw from
the study at any moment without any penalty. The study protocol was conformed to the
declaration of Helsinki and was approved by the ethics committee of the Research
Center in Sport, Health and Human Development (Vila Real, Portugal).
3.1.3.2.Procedures
The strength training type was divided in four levels: no strength training, upper limbs
strength training (Upper), lower limbs strength training (Lower) and upper and lower
limbs strength training (Total). The small sided games were performed in two formats:
GK + 3x3 and GK + 6x6 in a handball half court. The maximum dynamic strength (1
maximum repetition, 1RM) was assessed for each exercise (Upper: Horizontal bench
press, Deltoid press, Pullover, and Wrist flexion; Lower: Squat, Leg Curl, Lunge, and
Plantar flexion) (Brown & Weir, 2001). The Total strength training included two
exercises from both Upper and Lower (Horizontal bench press, Squat, Plantar flexion
and Wrist flexion).
The strength training protocol was performed according to the hypertrophic methods
with 3 sets of 10 to 12 maximal repetitions at a low speed execution (5 sec. per
repetition) and recovery periods of 60 sec. (Zatsiorsky & Kraemer, 2006). To measure
vertical jump height, the participants performed the squat jump, counter movement
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jump and abalakov jump (Bosco, Luhtanen, & Komi, 1983). The jumping height (m)
was calculated with an Ergojump (Bosco System, Globus, Italy). All games were
recorded with a standard camcorder and the reliability of notational analysis was
inspected by calculating kappa (ĸ) coefficients. Four weeks before the protocol
application, there was an anthropometric and dynamic maximum strength evaluation. In
the following week, all participants were familiarized with the protocol procedures. The
notational analysis of technical skills was held experimentally by the observers during
the protocol familiarization. A chronological schedule of the protocol is presented in
table 3.1.
Table 3.1. Chronological schedule that preceded the protocol application.
Week 1
Protocol
presentation
Presentation of
protocol contents
and standards.
Week 2
Week 3
Week 4
Anthropometric
characterization
HR max
evaluation
Maximum
dynamical strength
evaluation
Protocol
familiarization
Weight, Height
and BMI
assessment
yo-yo
Intermittent
Endurance
Test (Level 2)
1 RM evaluation
SSG 33; SSG
66; UPPER;
LOWER;
TOTAL; VJ
Week 5
Protocol
6 weeks
Note. SSG = small sided games; Total = upper and lower limbs strength training; Upper
= upper limbs strength training; Lower = lower limbs training; VJ= Vertical jump.
The first data collection (3x3 + Upper) started with stretching and a low intensity run (7
km / hr.) on a treadmill for warm-up. Afterwards, the players performed two attempts
for each vertical jump protocol with a 10-sec. break. The best jump value was recorded.
After this first vertical jump evaluation (Pre strength training, PRE ST), a 5-min. rest
interval was given before initiating Upper strength training. The strength training was
done on a rotary system with four stations, to optimize the recovery time between
exercises and to provide the same recovery time from the last strength training exercise
to the beginning of the 3x3 small-sided game. A second vertical jump evaluation took
place immediately after Upper strength training (post strength training, POS ST),
followed by a 20-min. interval. After this break, a 3x3 small-sided game was performed
with teams alternating attack and defense per block. Small-sided games were divided in
four blocks of 5 min. (1st half, 1st and 2nd blocks; 2nd half, 3rd and 4th blocks) with 293
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min. inter-game intervals (20 minutes of effective activity). The players were divided
(following the instructions of the head coach) into two balanced teams according to
their ability in passing, ball control, and game sense (Hill-Haas, et al., 2011).
Immediately after the small-sided games, the vertical jump was evaluated for the third
and last time (Post small-sided games, POS SSG). In that same week, after a 72-hour
interval, the protocol was repeated without strength training.
In the two following weeks, the protocol respected the exactly same procedure but in
this case, the strength training units that preceded the 3x3 were Lower and Total
strength training conditions, respectively. In Weeks 4, 5, and 6 the protocol was the
same, however, strength training and 6x6 small-sided games were performed with 12
participants, so four players took part in each one of the strength training stations. The
small-side games took place in an indoor court with a total area of 400 m² (325.5 m² of
playable area). The games were played according to the International Handball
Federation official rules and the ball used was size three for senior males (60 cm
diameter, 475 g). To avoid intensity disruptions, all penalty infractions were considered
as goals to the attacking team. In addition, to prevent subjectivity in rules interpretation,
a single referee was selected and maintained during the whole protocol. The offensive
actions were recorded within three shooting zones (Zone A: area between the midfield
and 9-m line; Zone B: central zone area between the 9- and 6-m lines; Zone C: wing
shooting zone). All actions were assigned to ball possessions and analyzed using the
percentage per 100 ball possessions.
3.1.3.3.Measures
The notational analysis of offensive technical actions included passes and catches (with
and without success), set shots and jump shots (with and without success) and technical
errors. The interceptions and goalkeeper actions were the considered defensive actions.
Data reliability was high (ICCs above .90).
3.1.3.4.Analysis
The data are presented as means and standard deviations. All data sets from technical
indicators and vertical jump performance were assessed for outliers and assumptions of
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normality. A repeated-measures ANOVA was performed to identify inferential
differences in vertical jump performance (PRE ST, POS Stand POS SSG) according to
the number of players, type of strength training, and time of testing effects. When
appropriate, the Scheffe post-hoc test was used for multiple comparisons. Effect size
was presented as eta squared form (mean, [95% confidence intervals]). The vertical
jump performance was also presented as percentage of height variation, with the Pre
strength training (PRE ST) performance being considered as the baseline.
All analyses were performed using Statistica Version 8 (Statsoft, Tulsa USA) and alpha
was set at .05.
3.1.4. Results
The vertical jump values according to the number of players, type of strength training
and time of testing are presented in Fig. 3.1. Significant differences were found in the
triple interaction between the time of testing, number of players, and strength training
(table 3.2). Also, differences were identified in the single effect of time of testing, in the
interaction between time of testing and number of players. Overall, the vertical jump
performance decreased after all types of strength training, with higher values after the
6x6 small-sided games. However, Figs. 3.1 , 3.2 and 3.3 show that after 3 small-sided
games there was a decrease in vertical jump performance when the game was preceded
by Upper or Lower strength training.
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Figure 3.1. Results from interaction Players x Strength Training x Time for squat jump
values. LOWER (lower limbs strength training); POS SSG (after small sided games);
POS ST (after strength training); PRE ST (before strength training); TOTAL (upper and
lower limbs strength training); UPPER (upper limbs strength training).
Figure 3.2. Results from interaction Players x Strength Training x Time for counter
movement jump values. LOWER (lower limbs strength training); POS SSG (after small
sided games); POS ST (after strength training); PRE ST (before strength training);
TOTAL (upper and lower limbs strength training); UPPER (upper limbs strength
training).
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Figure 3.3. Results from interaction Players x Strength Training x Time for abalakov
jump values. Legend: LOWER (lower limbs strength training); POS SSG (after small
sided games); POS ST (after strength training); PRE ST (before strength training);
TOTAL (upper and lower limbs strength training); UPPER (upper limbs strength
training).
Table 3.2. Analysis of Variance to Assess Differences in Vertical Jump Performance by
Number of Players in Small-sided Games, Type of Strength Training, and Time of
Testing.
Source
MSE
F
df
p
2
mean, [95% CIs]
Time of testing (T)
SJ
0.0125
48.8
22
<.001
0.82, [0.61, 0.88]
CMJ
0.0090
34.1
22
<.001
0.76, [0.50, 0.84]
AJ
0.0105
67.6
22
<.001
0.86, [0.70, 0.91]
SJ
0.0016
7.5
22
<.01
0.41, [0.07, 0.59]
CMJ
0.0022
8.3
22
<.01
0.43, [0.08, 0.61]
AJ
0.0026
10.1
22
<.001
0.48, [0.13, 0.64]
SJ
0.0016
9.1
44
<.001
0.45, [0.18, 0.57]
CMJ
0.0001
3.3
44
<.05
0.23, [0.01, 0.37]
AJ
0.0013
5.1
44
<.001
0.32, [0.06, 0.46]
T x Players (P)
T x P x Strength training
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According to Fig. 3.4, the percent change in vertical jump performance from baseline,
recorded after the 6x6 small-sided games (POS SSG), were lower than those after
strength training (POS ST). Compared to baseline, the vertical jump performance
increased after 6x6 small-sided games when there was precedent Upper and Lower
strength training. However, after the 3x3 games there was a decrease from the vertical
jump baseline after Upper strength training (squat jump and countermovement jump)
and Lower strength training (countermovement jump and abalakov jump).
Figure 3.4. Percentage (%) of the height variation from the baseline (PRE ST) to the
interaction Players x Strength Training x Time.
The 6x6 games promoted a higher percentage of passes than the 3x3 games (17.21±5.14
of successful and 0.59±0.22 of unsuccessful versus 9.33±2.10 of successful and
0.24±0.18 of unsuccessful, respectively). Also, the 6x6 games elicited a higher
percentage of successful catches than the 3x3 (17.10±5.25 and 9.15±1.93, respectively).
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The percentage of unsuccessful set shots was higher in 3x3 compared to those verified
in 6x6 (0.64±0.31 and 0.33±0.19, respectively).
Furthermore, significant differences were identified in the percentage of technical errors
between 3x3 and 6x6 games when there was Total strength training (0.12±0.08 and
0.01±0.01, respectively). The percentage of interceptions was higher in the 6x6
(0.41±0.21) compared to those occurred in the 3x3 (0.10±0.09). The percentage of
goalkeeper actions increased in the second half of both SSG (first half, 0.95±0.33;
second half, 1.34±0.51) and it was higher when there was precedent Upper (1.45±0.67)
and Lower strength training (1.21±0.43). Finally, the number of players influenced the
number of shots per shooting zone, with a higher number of shots in the wingers’
position (zone C) being recorded in 3x3 small-sided games (28.08±12.28 and
12.84±3.77).
Table 3.3. Analysis of Variance to Assess Statistical Differences in % of Technical
Actions by Number of Players in Small-sided Games, Type of Strength Training and
Half (only statistical significant differences are presented).
Source
MSE
F
df
p
2
mean, [95% CIs]
Number of players
Passes (successful)
16.775
28.5
16
<.001
0.64, [0.27, 0.78]
Passes (unsuccessful)
0.0421
24.7
16
<.001
0.61, [0.23, 0.76]
Catches (successful)
17.230
27.3
16
<.001
0.63, [0.26, 0.77]
Set shots (unsuccessful)
0.0605
16.3
16
<.001
0.51, [0.12, 0,69]
Interceptions
0.0347
22.4
16
<.001
0.58, [0.20, 0.74]
0.0831
11.9
16
<.01
0.69, [0.28, 0.79]
0.0006
3.65
16
<.05
0.41, [0.00, 0.59]
0.0285
4.1
16
<.05
0.43, [0.00, 0.61]
Half
Goalkeeper actions
Number of players x Strength training
Technical errors
Strength training  Half
Goalkeeper actions
3.1.5. Discussion
The results showed that vertical jump decreased after all types of strength training,
probably justified by the neuromuscular process, elastic and contractile capacity of the
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muscle structure (Komi, Nicol, & Marconnet, 1992) and to the present study
hypertrophic strength training methodology. In fact, this strength training methodology
can increase blood lactate concentrations up to 10 to 13 mmol (Mero, Leikas,
Knuutinen, Hulmi, & Kovanen, 2009), impair the muscular contraction and the acute
capacity of the stretch shortening cycle to generate muscular torque (Rodacki, Fowler,
& Bennett, 2002). These symptoms play a crucial role on the reducing of the lower
limbs strength power, which may support the deterioration of the vertical jump
performance after strength training units.
The results showed that vertical jump absolute values increased after 6x6 games when
compared to the POS ST values. Previous studies have demonstrated that high-threshold
fast motor units are recruited during maximal intensity actions such as vertical jump
(Kubo, Morimoto, Komuro, Tsunoda, Kanehisa, & Fukunaga, 2007). In fact, vertical
jump height is considered an important indicator of the lower limbs muscle power and it
has been used to assess the lower extremity function and to measure the power
development because of its high reproducibility (Slinde, Suber, Suber, Edwen, &
Svantesson, 2008). Also, strength training research has shown that performing maximal
(or near maximal) muscular contractions can produce short-term increases in maximal
force due to phosphorylation of myosin light chains resulting from the initial muscle
activity and excitability of alfa-motoneurons resulting in a greater contractile
performance after previous muscular activity (Sweeney, Bowman, & Stull, 1993). Thus,
it seems that maximal voluntary contractions can improve the acute muscle peak torque
and the explosive muscle performance. In contrast, vertical jump capacity was impaired
after 3x3 with precedent Upper strength training (squat and counter movement jumps)
and Lower strength training (countermovement and abalakov jumps). One of the
possible reasons is that small-sided games with a higher number of players have lower
physiological impact because the addition of players lowers %HRmax, blood lactate
concentrations and perceived exertion (Hill-Haas, et al., 2011). The strength training
using high loads promotes acute muscular fatigue, however, it was already found that
after a 60-min. hypertrophy strength training, lactate concentrations and the ability to
generate force returned to levels close to those recorded before the strength training
(McCaulley, McBride, Cormie, Hudson, Nuzzo, Quindry, et al., 2009). The time gap
between the strength training and game situations, the apparently recovery of the ability
to generate power and the stimulus elicited by 6x6, may have resulted in the
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potentiating of the vertical jump performance. Indeed, the agility, sprint and jump
capacity decline after playing a soccer 3x3 game (Hill-Haas, et al., 2011). Considering
that sprint capacity depends on the stretch-shortening cycle muscle function of upper
and lower musculature and its relation with vertical jump height (Maulder & Cronin,
2005), the general impairment of the vertical jump performance after 3x3 with
preceding strength training may be explained by the decrease of both limbs muscle
power. Interestingly, despite of the importance acknowledged to lower limbs when
performing jumping actions, upper extremity strength is also important in jump throws,
due to difficulties to use trunk rotation or lower extremity force (Fleck, Smith, Craib,
Denahan, Snow, & Mitchell, 1992). Apparently, the high intensity promoted by 3x3
resulted in vertical jump decreases and did not allow recovering from fatigue induced
by Upper and Lower strength training.
The 6x6 small-sided games promoted more successful and unsuccessful passes,
successful catches and interceptions, suggesting higher interaction between the players
for the same playable area. The higher number of passing possibilities in 6x6 has
facilitated the occurrence of successful catches and passes. On the other hand, it appears
that the reduction of the ratio area per player and the consequent proximity between
players has provided a higher number of unsuccessful passes and interceptions.
Opposing to the small-sided games with a reduced number of players that seem to
decrease the available choices for the player with ball, the 6x6 games appear to facilitate
the cooperation between players. Previous research has found that the addition of
players increased the number of skills per team, while reducing the number of players
has been related to the increase of individual contacts with the ball (Hill-Haas, et al.,
2011). The small-sided games with smaller number of players reduced the solutions to
the player with the ball and consequently, the possibilities of cooperation. As a
consequence, the tendency of the player to solve the constraints using individual
solutions increases. Adding together, it is possible that the higher physiological stimulus
and the increase of individual actions promoted by 3x3 games may not allow sustaining
the technical skill proficiency. In fact, the present study showed that the number of
unsuccessful set shots was higher in 3x3, which supports the idea that high intensity
game situations may be counterproductive in terms of playing performance.
The number of shots in the wingers’ zone (zone C) was higher during 3x3, suggesting
that players tend to search for unoccupied areas in the lateral corridors when the number
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of players is lower. In fact, it was already showed that small-sided games with a smaller
number of players require different tactical requirement (Hill-Haas, et al., 2011). The
greater distances travelled when the ratio area per player is higher, turn out the game
pattern to be more unpredictable. In accordance to previous research (Hill-Haas, et al.,
2011), it may be suggested that the relationship between the individual workout profiles
and the skills performance should be the target of future investigations to help clarifying
these results.
The 3x3 with precedent Total strength training induced a higher number of technical
errors. The high intensity exercises like strength training and small-sided games with a
smaller number of players can increase the peripheral and central fatigue, impair the
motor skills outcomes and decision-making (Knicker, Renshaw, Oldham, & Cairns,
2011). Adding together, these fatigue related symptoms seem to affect the skill
performance as it is shown by the increase of technical errors verified in current study
when the 3x3 small-sided games was preceded by Total strength training. Additionally,
the acute muscular fatigue elicited by the Lower and Upper strength training may have
affected the lower and upper limbs capacity to generate power during both SSG, which
supports the higher occurrences of unsuccessful jump shots.
Apparently, high-duration small-sided games decrease the number of consecutive
contacts with the ball, suggesting that as game progresses, players tend to solve the
constraints using less individual solutions. In the final 15 minutes of a soccer game, the
peak sprinting speed can be hampered (Bangsbo & Mohr, 2005) and replacement
players can perform 25% more high-intensity running and 63% more sprinting (Mohr,
Krustrup, & Bangsbo, 2003). These fatigue manifestations can deteriorate the technique
execution and the throwing velocity (Knicker, et al., 2011), which explains the
increased number of goalkeeper actions in the final moments of the small-sided games
with preceding strength training (mostly after Upper and Lower).
Short-term planning in team sports requires that coaches understand the acute effects of
combining strength and technical-tactical training. This study provided new evidences
on how strength training may be combined with court training (small-sided games). The
vertical jump capacity is impaired after maximum strength training. Comparatively to
the moment immediately following strength training, the vertical jump height increases
after 6x6, but is impaired after 3x3 with precedent Upper and Lower strength training.
The high intensity promoted by 3x3 does not allow recovering from fatigue induced by
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Upper and Lower strength training, probably due to the decrease of both limbs muscle
power. The higher physiological stimuli during 3x3 promote the deterioration of some
technical skills proficiency, mainly during high duration small-sided games with
preceding strength training. The 6x6 elicits a higher cooperation and interaction
between players and potentiates the vertical jump performance after strength training.
Coaches usually consider the preseason as a specific period to develop technical-tactical
skills but also to increase the players’ muscle mass. These findings highlight the
importance of selecting adequate court training exercises after a hypertrophic strength
training session.
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CAPÍTULO 4
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4.1.
TIME-MOTION AND PHYSIOLOGICAL PROFILE OF FOOTBALL
TRAINING SESSIONS PERFORMED BY UNDER 15, UNDER 17 AND UNDER
19 ELITE PORTUGUESE PLAYERS
Eduardo Abade1, Bruno Gonçalves1, Nuno Leite1 and Jaime Sampaio1
1 University of Trás-os-Montes e Alto Douro, Research Center in Sport Sciences,
Health and Human Development (CIDESD). Vila Real, Portugal.
4.1.1. Abstract
The aim of this study was to provide time-motion and physiological profiles of football
training sessions (TS) performed by under 15, under 17 and under 19 elite level
Portuguese players. 151 elite players of under 15 (age 14.0±0.2 n=56), under 17 (age
15.8±0.4 n=66) and under 19 (age 17.8±0.6 n=29) participated in the study during a 9week period. Time-motion and body impact data were collected using GPS technology
(15Hz) with heart rate monitored continuously (1Hz) across 38 randomly selected TS
that resulted in a total of 612 samples. The total distances covered (m) were higher in
U17 (4648.3±831.9), followed by U19 (4212.5±935.4) and U15 (3964.5±725.4) players
(F=45.84, p<.001). Total body impacts and relative impacts were lower in U15 (total:
490.8±309.5, F=7.3, p<.01), but no differences were identified between U17 (total:
584.0±363.5) and U19 (total: 613.1±329.4). U19 players had less high/very high
intensity activity (F=11.8, p<.001) and moderate intensity activity (F=15.07, p<.001).
The heart rate values showed significant effects of zones (F=575.7, p<.001) and
interaction with age groups (F=9.7, p<.001) with pairwise differences between all
zones. All players spent most of time below 75% HRmax. Results showed high
variability between training sessions, refraining from identifying meaningful trends
when measuring performance, although, different demands were identified according to
the age groups. The U15 TS were less physiologically demanding, probably caused by
increased focus on small-sided games to develop basic tactical principles and technical
skills. The focus on game like-situations imposed a higher external and internal
workload on U17 and U19 players.
Key words: age groups; workloads; youth football
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4.1.2. Introduction
The identification of key performance indicators in football is important to improve the
training process among youths. Football is an intermittent team sport that includes both
high and low intensities with mean and peak heart rates between 69% and 91% of
maximal values, respectively1. Also, short-term training field periods can elicit average
HR values (b.min-1) of 135±5, 151±4 and 151±5 in U18, U16 and U14 age groups2. The
variability and unpredictability of the game is reflected in accelerations, decelerations,
changes of direction and in the execution of several technical skills, all of them having a
strong effect in energy expenditure3. For these reasons, the training drills should include
different physiological stimuli to provide optimal adaptations4. If the training process is
exclusively directed to the development of technical and tactical skills, the intensity and
the variability of the physiological stimulus could be compromised. Thus, in order to
promote an effective transfer to the competitive environment, it is suggested that the
sport-specific training must provide the inclusion of technical and tactical abilities in
similar conditions to those which occurs during the match play5. In essence, the
stimulus intensity is a key variable that influences the training response and should be
carefully considered when short and mid-term plans are designed.
Describing the intensity of training can provide valuable information for adjusting the
training stimulus to the players’ specific needs6. The study of important variables such
as the number of sprints performed, high-intensity running and total distance covered7,
can contribute for a better understanding of the performance during a game or training
session. The total distance covered by youth players during a match is approximately
6311 meters (ranging from 4435 to 8098m) with 12% comprising high intensity
activities1. The analysis of these movement patterns can be useful to study the activity
profiles of players8, however, football is a contact sport that requires the performance of
other specific actions such as tackles and jumps9. From this point of view, literature is
scarce describing the body impacts experienced by football players, either in training or
game situation. An accurate determination of the G forces experienced by football
players might help to better understand the competition physical demands10. Moreover,
adding physiological variables such as the heart rate to these work-rate profiles can be
helpful in understanding the oscillations in players’ performance during training drills.
Heart rate monitoring has been regularly used to assess the intensity during training and
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game situations and it has been recognized as a valid indicator to quantify physical
demands9.
The available research in football time-motion and physiological responses is mostly
focused in competition demands and disregards the training sessions (TS). In fact, there
seems to be a clear need to have reference values regarding the physical demands
according to different age groups in TS. The availability of such data can help coaches
to support daily planning by selecting task constraints that may optimize the players’
performance development. Therefore, the aim of this study was to describe the timemotion and physiological profile of TS performed by under 15, under 17 and under 19
elite level Portuguese players.
4.1.3. Methods
4.1.3.1.Subjects
The sample included 151 elite young Portuguese football players of under 15 (three U15
teams, n=56), under 17 (four U17 teams, n=66) and under 19 (two U19 teams, n=29)
age groups (see table 4.1). The players belong to five different elite youth teams that
were competing in the national championship (2011/2012 season). The participants,
their parents and coaches agreed with the protocol description and were notified that
they could withdraw from the study at any moment. This protocol was conformed to the
declaration of Helsinki and was approved by the ethics committee of the Research
Center in Sports Sciences, Health and Human Development (Vila Real, Portugal). The
sample size was calculated with G*Power (Version 3.1.5.1 Institut für Experimentelle
Psychologie, Düsseldorf, Germany) for an effect size of 0.4, an α of 0.05, and a power
of 0.8 (1-β). The total sample size computed by this method was 66, i.e., a minimum of
22 subjects in each group.
Table 4.1. Description of players’ sub-samples.
U15 (n=56)
U17 (n=66)
U19 (n=29)
F
p
Age (years)
14.0±0.2
15.8±0.4
17.8±0.6
4137.9
<.001
Height (m)
1.71±0.07
1.76±0.06
1.77±0.07
46.5
<.001
Weight (kg)
60.1±6.3
65.8±5.5
70.0±5.6
170.1
<.001
BMI (a.u)
20.4±1.2
21.2±1.4
22.4±1.0
154.5
<.001
Experience (years)
5.4±1.2
6.8±1.7
9.0±1.7
312.5
<.001
Significant differences are identified as: (a) U15 vs. U17; (b) U15 vs. U19; (c) U17 vs. U19.
110
Post-hoc
a,b,c
a,b
a,b,c
a,b,c
a,b,c
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4.1.3.2.Design
The study was conducted during the competitive season over a 9-week period
(December to February) and 38 randomly chosen TS (U15 n=12, U17 n=16 and U19
n=10) representing a total of 612 cases. All the practice sessions were performed at the
same time period of the day (from 16.30h to 21.00h) on natural turf pitches, under
similar environmental conditions (temperature 14–19°C, relative humidity 52–66%).
Both U15 and U17 teams trained in the same 60x40 meters on an outdoor pitch (4 TS
per week with an average duration of 90 minutes), while U19 teams trained in an
outdoor pitch with official dimensions (5 TS per week with an average duration of 90
minutes). For each age group, all TS were continuously performed in the same pitch.
Besides the regular physical education classes, none of the players was involved in
some other sport activity. The average number of players per training unit was 23±4.
4.1.3.3.Methodology
All practice sessions started with low intensity running and ball possession drills for
warm up and ended with a standardized cool down consisting of stretching exercises.
Players were allowed to consume water during a specific training session recovery
period (approximately 3 minutes). The goals of the TS differed among the age groups.
The clubs and coaches authorized to perform only a comprehensive general description
of practice sessions’ used drills. TS were mainly based on constrained small-sided
games according to each age group technical, tactical and physical aims. The U15 TS
mainly included the development of technical skills and elementary tactical principles.
Although the specific goals of U17 practices remained similar to U15, there was an
increased focus in game-like situations. The U19 TS included constrained small-sided
games focused on team tactical principles and physical conditioning stimulus. Players
were allowed to consume water during a specific TS recovery period (approximately 3
minutes).
The time motion variables were collected with 20 GPS units working at a sampling
frequency of 15Hz (SPI-Pro X II, GPSports, Canberra, Australia). Although the validity
and reliability of 10 Hz devices were already inspected by independent verifications 11,
no validation study has been done for 15Hz units. The variables recorded were the
relative distance covered per minute (m.min-1), the total distance covered (m) and the
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distances at different speed zones12: zone 1 (0-6.9 Km.h-1), zone 2 (7.0-9.9 Km.h-1),
zone 3 (10.0-12.9 Km.h-1), zone 4 (13-15.9 Km.h-1), zone 5 (16-17.9 Km.h-1) and zone 6
(≥18.0 Km.h-1). Sprints (zone 6) were also measured by number, average time interval
and average distance covered. Additionally, three ratios were calculated in order to
relate distance covered at high/very high (above 16 Km.h-1), moderate (10.0-15.9 Km.h1
) and low-intensity (7.0-9.9 Km.h-1) with distance covered at very low intensities (0-6.9
km.h-1) normalized for each 100 meters for comparison purposes. These work:rest
related ratios are frequently used in the literature to describe the activity profiles13,14.
The heart rate (HR) data were recorded continuously with individual monitors (Polar
Team System, Polar, FI) and grouped into four zones of %HRmax15: zone 1 (<75%),
zone 2 (75% - 84.9%), zone 3 (85% - 89.9%) and zone 4 (≥ 90%). To measure the
players’ HRmax, the Yo-Yo intermittent recovery level 2 test was performed16,17. Also,
the GPS devices are coupled with a 100 Hz tri-axial accelerometer which allowed the
estimation of body impacts18. This variable was grouped into six zones of G force10:
Zone 1 (< 5.0–6.0g), Zone 2 (6.1-6.5g), Zone 3 (6.5-7.0g), Zone 4 (7.1-8.0g), Zone 5
(8.1-10.0g) and Zone 6 (> 10.1g). Also, the relative impacts per minute and the total
impacts performed (independently of the zones) were recorded. The GPS and the HR
devices were attached to the players and activated 15 minutes before the beginning of
each training session, according to the manufacturer guidelines. The analysed TS had
different durations, therefore, all the data was normalized to 60 minutes of training time.
4.1.3.4.Statistical Analysis
The data are presented as means ± standard deviations. The mean intersection
coefficient of variation (%) was obtained across all considered variables according to
the age groups. A one-way ANOVA was performed to identify the differences in total
and relative distance covered, body impacts and workout ratios across the age groups.
The sprint activity variables were tested using non-parametric Mann-Whitney U tests.
Three repeated measures factorial ANOVA models were performed to identify
differences in time motion (6 zones x 3 age groups), heart rate (4 zones x 3 age groups)
and body impact zones (6 zones x 3 age groups) according to the age groups. Pairwise
differences and post-hoc comparisons were tested with Bonferroni post-hoc test.
Finally, a non-parametric independent sample Kruskal-Wallis test was performed to
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identify the differences in coefficient of variation (%) according to the age groups19. All
data sets were tested for each statistical technique corresponding assumptions. These
calculations were done SPSS Software (version 18.0, Chicago, Illinois, USA). The
statistical significance was maintained at 5%.
4.1.4. Results
The table 4.2 presents the results from distance covered, sprint characterization and
impacts across age groups. The total and relative distances covered presented significant
differences between age groups (F=40.2, p<.001). The number of sprints (activity
performed above 18 Km.h-1) were different between U15 and U17 (10.9±6.3 and
16.4±8.2, z=-7.2 p<.001, respectively) and between U17 and U19 (16.4±8.2 and
11.8±7.9, z=-5.1 p<.001, respectively). The average time interval presented differences
between U19 and both U15 (z=-2.2, p<.05) and U17 (z=-2.6, p<.01). Also, the average
distance covered for each sprint was significant higher (z=-2.6, p<.01) in U17 than in
U19 (13.0±5.3 and 11.8±6.7, respectively). In addition, the total impacts and relative
impacts presented statistical differences (F=7.3, p<.01) between U15 and the other two
age groups. No differences were found between U17 and U19.
Table 4.2. Analysis of distance covered, sprint characterization and body impacts
across age groups.
Variables
U15
U17
U19
Distance covered (m)
Total
3964.5±725.4
4648.3±831.9
4212.5±935.4
-1
Relative (m.min )
66.1±12.1
77.5±13.9
70.2±15.6
Sprint
Number
10.9±6.3
16.4±8.2
11.8±7.9
Time interval per sprint (s)
2.1±0.8
2.3±0.9
2.1±1.2
Average distance covered per sprint (m)
12.1±4.9
13.0±5.3
11.8±6.7
Body Impacts (number)
Total
490.8±309.5
584.0±363.5
613.1±329.4
Relative (impacts.min-1)
8.2±5.2
9.7±6.1
10.2±5.5
Significant differences are identified as: (a) U15 vs. U17; (b) U15 vs. U19; (c) U17 vs. U19.
Post-hoc
a,b,c
a,b,c
a,c
b,c
c
a,b
a,b
The figure 4.1a presents the variation of distance covered at the considered speed zones
for each group. There was a significant effect of speed zones (F=6495.5, p<.001,
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2=.92, Power=1.00), with pairwise differences between all zones. Also, the interaction
between speed zones and players’ age groups was significant (F=22.1, p<.001, 2=.07,
Power=1.00). The heart rate values (see figure 4.1b) showed significant effects of zones
(F=575.7, p<.001, 2=.49, Power=1.00) and interaction with age groups (F=9.7, p<.001,
2=.03, Power=1.00) with pairwise differences between all zones. The players spent
most of time below 75% HRmax. The Figure 4.1c presents the number of impacts in the
six considered G force zones. There was a significant effect of zone (F=1936.6, p<.001,
2=.76, Power=1.00) with pairwise differences in all zones. Additionally, differences
were found (F=4.8, p<.01, 2=.02, Power=1.00) between U15 and U17 and between
U15 and U19. The players performed a higher number of impacts in zone 1 (<5.0–6.0g).
Finally, the figure 4.1d presents the distance covered at high/very high, moderate and
low speed zones for each 100 meters covered in the very low-activity zone. The results
showed significant differences in the high/very high intensity activity (F=11.8, p<.001)
and moderate intensity activity (F=15.07, p<.001), between U19 and both U17 and U15.
No differences were found in low/very low activity.
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Figure 4.1. Results from distance covered for each speed zone (a), time spent in each
heart rate zone (b), number of impacts for each intensity zone (c) and distance in
different intensity zones for each 100m covered at very low intensity (d).
The table 4.3 presents the mean intersection coefficient of variation (%) between age
groups. Significant differences were found (p<.05) in distances covered for zones 1, 5
and 6 between U17 and U19. HR presented significant differences (p<.05) for zones 2
and 3 between U15 and U19. Also, the variability in the number of sprints performed
was different (p<.05) between U17 and U19.
Table 4.3. Mean intersection Coefficient of variation (%) according to the age groups.
Variables
U15
U17
U19
Post-hoc
Distance covered
Zone 1
16.28
12.63
16.06
b
Zone 2
29.75
37.05
25.36
Zone 3
33.73
38.90
34.12
Zone 4
37.75
36.83
43.10
Zone 5
44.10
32.80
52.12
b
Zone 6
64.60
47.33
67.52
b
Total
17.33
16.83
19.58
Heart Rate
Zone 1
33.10
36.18
35.36
Zone 2
36.68
35.63
40.36
a
Zone 3
46.18
47.05
73.76
a
Zone 4
78.05
77.70
105.66 Sprint
Number
57.20
42.98
69.16
b
Time interval
32.13
30.58
39.42
Distance covered
34.18
32.13
40.76
Impacts zone
Zone 1
53.28
55.33
48.60
Zone 2
65.28
62.53
57.00
Zone 3
73.93
68.75
59.40
Zone 4
80.00
75.13
69.24
Zone 5
91.03
94.45
86.04
Zone 6
127.48 126.65 127.44 Total
61.45
59.25
56.80
Significant differences are identified as: a) between U15 and U19; b) between U17 and U19.
4.1.5. Discussion
This study aimed to describe time-motion and physiological profiles of TS performed
by under 15, under 17 and under 19 players competing in the Portuguese national
championship. Previous research has been exclusively focused on monitoring specific
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moments of practice sessions or drills in highly controlled situations using constrainedtasks20. However, in order to improve ecological validity it seems important to monitor
and describe the total physiological workload imposed by the regular training process
without any external manipulation.
Results showed high variability between training sessions, refraining from identifying
meaningful trends when measuring performance but, alternatively, it might also be
consider that this variability is functional and constitutes a key-characteristic of elite
training sessions21. The distances covered for all age groups confirm the diversity of
stimulus promoted during a football practice session, probably by including technical,
tactical and physical drills with diverse aims, variable intensity and volume loads9. The
coefficient of variation (%) according to age groups showed higher values in distances
covered, HR and number of sprints for U19 players. Probably, the focus on team tactical
principles required additional coaching intervention, promoting more task interruptions
across the training sessions and eliciting variability. Consequently, the lower effect sizes
across variables may also be linked to this high variability. Nevertheless, the focus on
constrained small-sided games to develop basic tactical principles and technical skills
during U15 TS probably promoted a more regular activity pattern and resulted in the
lowest variability among the age groups.
The results of the present study suggest coaches to establish short and mid-term
planning guidelines corresponding to elite demands in youth football players.
Unfortunately, only a comprehensive description of practice sessions’ tasks could be
carried. Thus, the impossibility of manipulating the training contents implies caution on
the practical application of the results. Yet, the general idea from the results points that
football game-based training in these age groups has different consequences. Although
speculative, it is likely that the U15 training is less physiologically demanding, probably
because of the time spent in learning technical skills and basic tactical principles in
short-dimension pitches. The U17 age group gathers players with increased biological
maturation, capable of responding to higher power and speed demands during the
frequent game-like situations. Finally, the U19 constrained small-sided games focused
on team tactical principles may be linked to the decrease of the physiological demands.
Still, considering different age groups may have impaired an accurate control of the
players’ maturational status.
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The external load was already described according to playing positions by using
distances covered during match-play22 and running velocities in treadmill protocols23.
Although it is known that the physiological demands may vary according to playing
position24, available literature does not clarify the variations that might exist both
among different age groups and during training situations. The short term planning of
the three age groups was established by coaches, based on technical and tactical needs
in each one of the age groups. The U15 TS were mainly focused on constrained smallsided games directed to the development of the basic tactical principals and technical
skills, which can help justifying the lower distance covered. These training guidelines
are in accordance with the long-term athlete development plans for this age group,
reinforcing the importance of deliberate practice based on targeted and task centred
training programs25.
Comparatively to U15, the use of frequent game-like situations during U17 and U19 TS
can support the higher covered distances. In particular, the U17 players covered the
highest total and relative distances and had the highest number of sprints. The use of
game-like situations played with fewer constraints helped to increase physiological
stimulus. On the other hand, the small-sided games training used in U19 practice
sessions might have more stopping times to adjust the teams’ tactical model. In fact, the
U19 high/very high:very low and moderate:very low work ratios presented the lowest
values. This lack of high intensity activity may compromise the replication of the
physiological pattern required in elite competition, as described by early available
research7,9,26.
In all age groups, the players covered higher distances in the first four speed zones
(between 0-6.9 km.h-1) and players spent the highest amount of time below 75%
HRmax. A previous study focused on the distances covered at different running speeds
during a young football match found that players covered the highest distances between
0-6.0 km.h-1 and the lowest above 21.1 km.h-1
22
. However, the time spent above 180
b.min-1 intervals was higher than below 180 b.min-1
22
. Although the external load
imposed on young players during training is similar to those verified during a match
play, the average HR values during matches is substantially higher than those found in
practice sessions. In the U17 and U19 sessions, the frequent use of game like situations
elicited a higher number of sprints. The use of constrained small-sided games aiming to
the basic tactical principles and technical development during U15 TS resulted in lowest
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distances covered below 9.9 km.h-1. Thus, coaches should be aware that the replication
of the competition physiological pattern may be compromised if TS do not include more
game-like situations to promote higher intensities and variability13,27,28.
Although football is an invasion team sport with frequent contact, the activity profile
does not seem to promote a high occurrence of impacts. In the current study, the
average number of total impacts identified during the football-TS was of 471±291.5,
563±350.7 and 572±325 for U15, U17 and U19 players, respectively. Of interest is,
however, the significant difference identified between the U15 practices and the other
groups. In fact, when game situations are frequently used, the higher occurrence of
specific football actions such as changes of directions29,30 may increase the number of
impacts and consequently the strength and power demands.
4.1.6. Practical Applications

High variability between training sessions can be a key-characteristic of elite
teams’ training sessions.

The constrained small-sided games used to develop the basic tactical principles
and technical skills during TS promoted a decrease of the physiological
demands. In order to promote an increase in external and internal workload,
coaches should frequently use game like situations.

Youth football coaches can use these reference data to establish accurate short
and mid-term planning guidelines corresponding to elite demands in youth
football players for practice sessions.
4.1.7. Conclusion
The high variability between training sessions might refrain from identifying
meaningful trends, however, it might also be consider that this variability is functional
and constitutes a key-characteristic of elite training sessions. The external load imposed
on players differed in accordance with the age group. The U15 TS promoted less
physiological demands because of the focus on the small-sided games aiming to the
development of basic tactical principles and technical skills. Conversely, the frequency
of game like-situations was higher during U17 and U19 sessions that imposed a higher
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and more variable external load to the players. In addition, the use of game situations
during football TS seems to increase the number of impacts, resulting in activity
patterns that is more similar to the competition requirements. From a practical point of
view, coaches seem to be aware of the importance of the technical abilities development
at earlier age stages. Also, more game situations are promoted as biological maturation
increases. As the age groups progress, football coaches may plan the TS more similar to
the formal game physical, technical, and tactical demands.
Acknowledgements
This study was supported by PTDC/DES/098693/2008 project: “Evaluating training and
competition in team sports. Aggregating tactical analysis, external and internal
workload” financed by the Portuguese Foundation for Science and Technology (FCT).
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4.1.8. References
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Rebelo A, Brito J, Seabra A, Oliveira J, Krustrup P. Physical match performance
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Wrigley R, Drust B, Stratton G, Scott M, Gregson W. Quantification of the
typical weekly in-season training load in elite junior soccer players. J Sport Sci.
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Bangsbo J. The physiological profile of soccer players. Sports Exerc Injury. Nov
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Impellizzeri FM, Marcora SM, Castagna C, et al. Physiological and performance
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Williams AM, Hodges NJ. Practice, instruction and skill acquisition in soccer:
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Coutts A, Rampinini E, Marcora S, Castagna C, Impellizzeri F. Heart rate and
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Mohr M, Krustrup P, Bangsbo J. Match performance of high-standard soccer
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Bangsbo J, Mohr M, Krustrup P. Physical and metabolic demands of training
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McLellan CP, Lovell DI, Gass GC. Biochemical and endocrine responses to
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11.
Castellano J, Casamichana D, Calleja-Gonzalez J, San Roman J, Ostojic SM.
Reliability and accuracy of 10 Hz GPS devices for short-distance exercise. J
Sport Sci Med. Mar 2011;10(1):233-234.
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Aguiar M, Botelho G, Goncalves B, Sampaio J. Physiological responses and
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Casamichana D, Castellano J, Castagna C. Comparing the physical demands of
friendly matches and small-sided games in semiprofessional soccer players. J
Strength Cond Res. 2012.
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Cunniffe B, Proctor W, Baker JS, Davies B. An evaluation of the physiological
demands of elite rugby union using global positioning system tracking software.
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Gore C. Physiological Tests for Elite Athletes. Champaign, IL.: Human Kinetics;
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Krustrup P, Mohr M, Nybo L, Jensen JM, Nielsen JJ, Bangsbo J. The Yo-Yo
IR2 test: Physiological response, reliability, and application to elite soccer. Med
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Bangsbo J, Iaia FM, Krustrup P. The yo-yo intermittent recovery test - a useful
tool for evaluation of physical performance in intermittent sports. Sports Med.
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Montgomery PG, Pyne DB, Minahan CL. The physical and physiological
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Hill-Haas S, Dawson B, Impellizzeri F, Coutts A. Physiology of small-sided
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Davids K, Glazier P, Araujo D, Bartlett R. Movement systems as dynamical
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Aslan A, Acikada C, Guvenc A, Goren H, Hazir T, Ozkara A. Metabolic
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Dellal A, Wong D, Moalla W, Chamari K. Physical and technical activity of
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Memmert D, Baker J, Bertsch C. Play and practice in the development of sportspecific creativity in team ball sports. High Abil Stud. 2010;21(1):3-18.
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Rienzi E, Drust B, Reilly T, Carter JE, Martin A. Investigation of
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Carling C, Dupont G. Are declines in physical performance associated with a
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Castagna C, Impellizzeri FM, Chaouachi A, Bordon C, Manzi V. Effect of
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Gabbett TJ, Sheppard JM, Pritchard-Peschek KR, Leveritt MD, Aldred MJ.
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Varley MC, Aughey RJ. Acceleration profiles in elite Australian soccer. Int. J.
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CAPÍTULO 5
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5.1.
HELPING
COACHES
TO
CLASSIFY
YOUNG
FOOTBALLERS
ACCORDING TO THEIR TRAINING PERFORMANCES
Eduardo Abade1, Bruno Gonçalves1, Alexandra Silva1, Nuno Leite1, Carlo Castagna2
and Jaime Sampaio1
1 University of Trás-os-Montes e Alto Douro, Research Center in Sport Sciences,
Health and Human Development (CIDESD). Vila Real, Portugal.
2 Football Training and Biomechanics Laboratory, Italian Football Federation (FIGC),
Technical Department, Coverciano (Florence), Italy.
5.1.1. Abstract
This study aimed to classify young footballers according to their physical and
physiological profiles in training sessions (TS) and to contrast this classification
procedure against the age and playing position criteria. 151 male elite football players of
under 15, under 17 and under 19 years old stages participated in this study over a 9week period. Time-motion and body impact data were collected using GPS technology
with heart rate monitored continuously across 38 randomly selected TS. The results
demonstrated that players with identical ages and playing experience may have very
different performance profiles. This method may provide helpful criteria to group
players and diminishes the variability of the physiological outcomes, allowing coaches
to have an accurate control on players’ responses.
Key words: football, cluster analysis, performance profiles.
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5.1.2. Introduction
The competition in many youth team sports is organized according to several age
groups, mostly because of the need to enhance educational and fair-play values.
Although generally accepted, this organization form may fail to consider differences in
chronological age, since players within the same age group can have very distinct
physical and physiological profiles (Cobley, Baker, Wattie, & McKenna, 2009).
The identification and description of these profiles may provide valuable information to
refine the training workloads, task designs and environmental constraints. During
adolescence, the playing positions and selection level (i.e., Regional, National) have an
important interactive effect in players’ characteristics (Till, Cobley, O'Hara, Chapman,
& Cooke, 2012). In fact, most motor skills experience significant developments during
the pubertal period, reinforcing the importance of specific training (Fernandez-Gonzalo
et al., 2010). Therefore, the coaches should regularly track the progression of players’
responses to training and competition, considering the interaction between ages and
playing positions.
From a physiological perspective, understanding the development of athletic potential
alongside biological growth is crucial to select appropriate training aims at different
stages of players’ development. The long-term athlete development models generally
encourage the use of a wide range of activities in the earlier ages with a progressive
narrowing of sport focus in more advanced ages (Côté & Fraser-Thomas, 2007).
However, aiming for the most sensitive development periods seems to be a very delicate
issue, partly because the long-term effects of youth intensive training and competitive
schedules are poorly explored by literature.
To develop a successful sports career, young players have to perform adequately in
several dimensions (Elferink-Gemser, Visscher, Lemmink, & Mulder, 2004). Generally,
the training sessions have a strong focus on game like situations, eliciting both dynamic
and adaptive responses, providing high variability of physiologic, technical and tactical
stimulus (Pinder, Davids, & Renshaw, 2012). However, the manipulation of constraints
can be quite limited because, even if the task constraints contain relevant information
for learning a specific activity, the unique characteristics of each learner also represent
personal constraints (Chow et al., 2006). In fact, it is possible to identify that individual
learning dynamics will be different since the interacting configurations of constraints
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will differ between learners (Chow, Davids, Hristovski, Araujo, & Passos, 2011).
Consequently, when physiological profiles vary among players, caution should be
applied in data interpretation, mainly because of the differences in emergent behaviors.
Therefore, it is dysfunctional to establish universal optimal learning pathways to which
all learners should adhere. The presence of instabilities in the perceptual-motor
landscape related to differences in growth, development, maturation and learning might
provide qualitative changes in their performance (Hristovski, Davids, Araujo, & Passos,
2011).
Within the available literature, the activity profiles of young football players are usually
described in relation to playing positions (Aslan et al., 2012; Buchheit, MendezVillanueva, Simpson, & Bourdon, 2010) and age groups (Fernandez-Gonzalo et al.,
2010; Till et al., 2012). For example, it was showed that running performance tends to
increase with age (Buchheit et al., 2010) and youth players cover from 4435 to 8098m
during a match (Rebelo, Brito, Seabra, Oliveira, & Krustrup, 2012). The players seem to
cover the highest distances in low speed zones (0-6.0 km.h-1) and the lowest above
21.1km.h-1 (Aslan et al., 2012). The distances covered vary according to playing
positions, with defenders and midfielders achieving the lowest and highest distances,
respectively (Buchheit et al., 2010). The defenders seem to have lower endurance
performances than midfielders and forwards (Markovic & Mikulic, 2011).
The differences in movement and activity patterns require for different conditioning and
recovery programs according to age and positional groups (Quarrie, Hopkins, Anthony,
& Gill, 2012) because football demands for hard accelerations and decelerations,
changes of direction and collisions. Therefore, the players’ body impact activity and HR
profiles will help to better understand and assess the physical demands as well as to
adjust rest and recover times after training and matches (Quarrie et al., 2012). Highlevel players are frequently required to perform high intensity sprints and changes of
direction which underlines agility as a key ability (Sheppard & Young, 2006).
Consequently, the development of changing direction related mechanisms, such as the
sprinting capacity (Jones, Bampouras, & Marrin, 2009), power and strength qualities is
a major issue to coaches and considered an important predictor of performance (P.,
Chan, & Smith, 2012).
All these variables seem important to describe the players’ physiological profile and to
provide key information to adjust the training load. However, these were really never
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contrasted against the players’ actual internal load in training. The data gathered in
training sessions can also be used to classify the players into different groups of
performance, alternatively to different groups of ages and playing positions. In fact,
physiological variables are suggested to be powerful predictors to identify talent in
youth sports (Unnithan, White, Georgiou, Iga, & Drust, 2012). In this sense, the
classification techniques (e.g., cluster analysis) based on physiological profiles may
provide useful information for establishing groups of interest for talent identification
and training prescription.
Therefore, the aim of this study was to classify young footballers according to their
physical and physiological profiles in training sessions and to contrast this classification
procedure against the age and playing position criteria. In addition, we aimed to identify
the most powerful variables in players’ classification. The improvements in these
classification procedures will allow the sports clubs and coaches to improve the
accuracy of training plans and the improvement in players’ interactions along the
training tasks.
Hypothesis 1. It is expected to find different performance profiles among players with
identical ages and playing experience.
Hypothesis 2. We hypothesized that heart rate values and body impacts would represent
the most powerful predictors to discriminate performance profiles in training.
5.1.3. Method
5.1.3.1.Participants
One hundred and fifty-one male football players of under 15 (U15 n=56), under 17
(U17 n=66) and under 19 (U19 n=29) years old stages participated in this study. The
participants were part of five different elite youth teams, training and competing
regularly in the Portuguese national competition (2011/2012 season). After a detailed
protocol explanation about the aims, benefits and risks involved in this investigation, all
participants, parents and coaches signed a written informed consent. Additionally,
players were informed that they were free to withdraw from the study at any time
without any penalty. The study protocol was conformed to the declaration of Helsinki
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and was approved by the ethics committee of the Research Center in Sport, Health and
Human Development (Vila Real, Portugal).
5.1.3.2.Procedures
The study was conducted during the competitive season over a 9-week period
(December to February) with 38 randomly chosen training situations (U15 n=12, U17
n=16 and U19 n=10) representing a total of 612 cases. All the practice sessions were
performed at the same time period of the day (from 16.30h to 21.00h) in outdoor natural
turf pitches, under similar environmental conditions (temperature 14–19°C, relative
humidity 52–66%). Both U15 and U17 teams trained four times per week for a total of
360 minutes in a 60x40 meters pitch, while U19 teams trained five times per week for a
total of 450 minutes in a pitch with official dimensions. Besides the regular physical
education classes, none of the players was involved in other sports. The average number
of players per training unit was 23±4.
All practice sessions started with a specific warm up that included low intensity running
and ball possession drills. Stretching exercises were performed at the end of each
training session. Players were allowed to drink water during specific recovery periods
were allowed (approximately 3 minutes). The clubs and coaches authorized to perform
only a comprehensive general description of practice sessions’ used drills. All sessions
began with a ~15 minute warm-up and ended with ~10 minutes of cool down exercises.
The U15 training sessions mainly included the development of technical skills and
elementary tactical principles. Although the specific goals of U17 practices remained
similar to U15, there was an increased focus in game-like situations. The U19 training
sessions included constrained small-sided games focused on team tactical principles and
physical conditioning stimulus.
The players’ external workload was represented by the median values from all
monitored training units. The distance covered was measured in predefined speed zones
(Aguiar, Botelho, Goncalves, & Sampaio, 2012): zone 1 (0.0-6.9 km.h-1), zone 2 (7.09.9 km.h-1), zone 3 (10.0-12.9 km.h-1), zone 4 (13.0-15.9 km.h-1), zone 5 (16.0-17.9
km.h-1) and zone 6 (≥18.0 km.h-1). Sprints (zone 6) were also measured by both average
time interval and distance covered. The data were collected at 15Hz through the entire
duration of each training sessions using portable global positioning system units (SPI128
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PRO X II, GPSports, Canberra, ACT, Australia). These units were fitted to the upper
back of each participant using an appropriate elastic harness. The validity and reliability
of these instruments were already inspected by independent verifications for the both 5
and 10Hz units (Castellano, Casamichana, Calleja-Gonzalez, San Roman, & Ostojic,
2011; Johnston et al., 2012).
Players’ internal workload included the HR and the body impacts variables. The HR
absolute values were recorded continuously throughout all training sessions using the
Polar Team System (Polar Electro, Oy, Kempele, Finland) and, subsequently, converted
into percentages of HRmax and classified into time spent in four zones of intensity
(Gore, 2000): Zone 1 (<75% HRmax), Zone 2 (75-84.9 % HRmax), Zone 3 (85-89.9 %
HRmax) and Zone 4 (≥ 90 % HRmax). To measure the players’ HRmax, the Yo-Yo
intermittent recovery level 2 test was performed (Krustrup et al., 2006). The SPI-PRO X
II units are coupled with a 100Hz accelerometer capable of measuring the body impacts
thought the rate of acceleration and deceleration ability in horizontal axis (x), transverse
axis (y) and vertical axis (z). This variable measures the changes of direction, collisions
with opposition and the ground. The values were grouped into six zones of G force
(McLellan, Lovell, & Gass, 2011): zone 1 (very light impact, <5.0–6.0g), zone 2 (light
to moderate impact, 6.1-6.5g), zone 3 (moderate to heavy impact, 6.5-7.0g), zone 4
(heavy impact, 7.1-8.0g), zone 5 (very heavy impact, 8.1-10.0g) and zone 6 (severe
impact, >10.1g).
5.1.3.3.Analysis
A two-step cluster with log-likelihood as the distance measure and Schwartz’s Bayesian
criterion was performed to classify athletes according to their performance profiles (i.e.
all variables described in procedures section). The considered analysis was used to point
out physical and physiological similarities among players. This method differs from
traditional clustering techniques by handling of categorical variables (assuming
variables to be independent), automatic selection of number of clusters (automatically
determines the optimal number of clusters) and scalability (by constructing a cluster
membership) (Tabachnick & Fidell, 2007). The variables were ranked according to their
predictor importance, indicating the relative importance of each predictor in estimating
the model (the sum of the values for all predictors on the display is 1). Subsequently,
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the clustering variables description was presented as means ± standard deviations. The
sprint activity variables were tested using one-way ANOVA. Finally, a repeated
measures factorial ANOVA was performed to identify differences in time motion, HR
and body impact zones according to the clustering groups. Pairwise differences were
assessed with Bonferroni post-hoc test. All data sets were tested for each statistical
technique corresponding assumptions. These calculations were carried in SPSS
Software (v20.0, IBM Corporation, USA) and statistical significance was maintained at
.05.
5.1.4. Results
The cluster analysis classified the players into three distinct groups in accordance with
their physical and physiological performances during the training sessions. The obtained
clusters comprised, respectively, 15.2%, 37.1% and 47.7% of the total sample size. No
differences were found in players’ age, height, weight, BMI and experience between the
clusters (see table 5.1).
Table 5.1. Characterization of the cluster groups.
Age
Height
Weight
BMI
Experience
Cluster 1 (n=23)
Cluster 2 (n=56)
Cluster 3 (n=72)
15.7±1.5
1.72±0.06
63.2±5.6
21.3±1.4
6.5±1.9
15.4±1.0
1.76±0.07
65.1±6.2
21.0±1.3
6.8±1.7
15.5±1.7
1.74±0.07
64.5±7.7
21.2±1.6
6.7±2.3
The figure 5.1 shows the distribution (%) of players in each Cluster considering the
players’ actual development stage and playing position. The Cluster 1 presents the
lowest percentage of sample size, with a high presence of U19 midfielders,
comparatively with the other age groups and playing positions. The Cluster 2 includes
the highest percentage of U17 players and the lowest percentage of U19 players. The
Cluster 3 is the group with higher size. The percentage of U15 forwards and defenders
is high, as well as U19 midfielders and defenders.
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Figure 5.1. Distribution (%) of players in each cluster considering the players’
development stage and playing position
Sprints characteristics (activity performed above 18 km.h-1) presented differences
between clusters 2 and 3 for both time interval (F=11.7, p<.001) and distance covered
per sprint (F=11.6, p<.001). The cluster 3 presented the lowest average time interval
(1.67±0.24 seconds) and distance covered per sprint (9.45±1.43 meters).
The figure 5.2 presents the results from both external and internal workload across
clusters and also the predictor importance (PI) from all considered variables. Figure 5.2i
presents the variation of distance covered at the considered speed zones for each cluster.
There was a significant effect of both speed zones (F=2573.3, p<.001, η2=.95) and
clusters (F=3.3, p<.001, η2=.43). Also, differences were found in body impacts zones
(F=1020.8, p<.001, η2=.87) and clusters (F=44.1, p<.001, η2=.37), with pairwise
differences across all groups, except between clusters 2 and 3 for zone 6 (see figure
5.2ii). The HR zone values showed significant effect of zones (F=487.1, p<.001,
η2=.77) and clusters (F=30.9, p<.001, η2=.30) with players spending most of the time
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below 75% of HRmax (see figure 5.2iii). Finally, figure 5.2iv presents the obtained
predictor importance from the variables. The strongest PI was found in body impacts for
zones 5 (PI=1.00), 3 (PI=0.88), 4 (PI=0.85) and 2 (PI=0.85). Distance covered at zone 1
was identified as the lowest PI (PI=0.03).
Figure 5.2. Results from distance covered for each speed zone (i), number of impacts
for each intensity zone (ii) time spent in each heart rate zone (iii) and predictor
importance to all considered variable (iv). Significant differences are identified as: (a)
Cluster 1 vs. Cluster 2; (b) Cluster 1 vs. Cluster 3; (c) Cluster 2 vs. Cluster 3
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5.1.5. Discussion
This study aimed to identify the most powerful performance predictors in clustering
young footballers during training sessions, providing more accurate information about
the players’ response to training stimulus. The obtained clusters were very similar in
aging, anthropometric characteristics and experience years. This similarity suggests that
these variables may not be the most important to discriminate the performance profiles
in training. In general, the current results demonstrated that players with identical ages
and playing experience might have very different physiological profiles and,
consequently, respond in different ways to similar training stimulus. Some predictors
such as anthropometric and physiological characteristics have recently been suggested
to identify talent in youth sports and may represent useful information to predict future
career progression (Unnithan et al., 2012). Thus, the clustering methods can provide
performance profiles to enable early identification of talented youths. Also, grouping
players with similar physiological characteristics may diminish the emergence of
heterogeneous responses during training, which can help coaches in the distribution of
training groups and allow an efficient control on the players’ response. Moreover,
clustering may be performed by using valuable information from fitness tests, which
allow coaches to manipulate these profiles in any moment of the competitive season.
The current results identified that body impacts in higher intensity zones (zones 2 to 5)
were the predictors that best discriminated the obtained clusters. Although the training
tasks were similar across all age groups, the players’ responses in body impacts varied
substantially across the clusters. This importance may suggest that selected task
constraints in training enhance a specific learning, exhibited in players’ unique rates of
acceleration and deceleration. Sprints with changes of direction seem to induce a higher
neuromuscular stimulus than intermittent in-line sprints (Dellal et al., 2010), mostly
because of its high relationship with the eccentric strength (Jones et al., 2009). The
results show that players in cluster 1 performed a higher number of impacts across all
zones. This analysis may help coaches to identify the most capable players to
successfully perform high intensity and rapid body movements. It seems that these data
is important to understand and measure the performance indicators of the high intensity
intermittent exercises, frequently experienced during training and/or game situations
(Vaz, Leite, Vicente, Gonçalves, & Sampaio, 2012). These results present a new insight
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to the process of monitoring training effects, by including body impacts as key variable
to understand the players’ individuals’ responses to different task designs.
The Cluster 3 represented the players with lower distances covered and body impacts
across all zones per training. Consequently, these players spent more time below 75%
HRmax. This is the most frequent profile (47.7% of sample size), including a high
percentage of U15 and U19 players, probably because of the players’ fitness, maturity
and status level. It was suggested that higher expertise, positioning and deciding skills
(Kannekens, Elferink-Gemser, & Visscher, 2011) might result in lower physical and
physiological intensity for U19 players. In fact, high-level U19 coaches usually focus
their attention on the team strategic plans and collective tactical responses, by
improving players’ positioning. The U15 training sessions have a different perspective,
mainly focused on acquiring basic collective tactical principles such as the interpersonal
player relations in sub-phases (Duarte et al., 2012). Consequently, the frequent presence
of U15 players in cluster 3 may be the result of lower conditioning variables, such as
strength, power and speed (Malina, Eisenmann, Cumming, Ribeiro, & Aroso, 2004).
The Cluster 2 has a frequent number of U17 players that is beyond the critical period of
physical maturation in an intermediate stage of tactical expertise. Also, the progressive
understanding of the game collective tactical principles potentiated by the training
process may be responsible for the intermediate physiological profile of these players.
The Cluster 1 represented the players within higher values across all variables, but with
the lower number of players. It might be suggested that these players should be
followed with increased attention because they exhibit the higher physical and
physiological potential.
When training tasks are focused on the players’ physical development, grouping players
with similar physiological profiles and fitness level may avoid significant divergent
responses and adaptations to the stimulus. Thus, coaches would have a more accurate
and effective control on the players’ response exercises, mainly during specific blocksperiodized training (Issurin, 2010). However, optimal performance in competitions
requires not only the physiological development, but also the technical and tactical
abilities. In this sense, caution should be applied when game-like situations are
promoted due to the players’ different perceptual-cognitive expertise. Yet, further
investigations are required to explore the short and long-term effects of this clustering
method.
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Similarity in aging, anthropometric characteristics and experience years in the studied
groups, suggest that these variables are not the most important to discriminate the
performance profiles in training. The players’ unique activity profiles suggested a
specific learning effect, as identified by body impacts resulting from players’
accelerations and decelerations in sprints with changes of direction. The body impacts
seem to be powerful predictors to represent players’ performance profiles in training
sessions. As physiological variables are suggested to be important predictors to identify
talent in youth sports, using them to establish cluster classifications may provide
reference profiles to early talent identification. Also, this classification technique may
help coaches to optimize player distribution in training groups during the practice
sessions. Consequently, this approach minimizes the variability of the physiological
outcomes, allowing coaches and fitness trainers to accurately manipulate the training
exercises and have a more effective control on the players’ responses. Thus, coaches
should not hinder mixing up players with different ages and playing positions in order
to optimize their adaptations to training stimulus.
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CAPÍTULO 6
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6.1.
CONCLUSÕES E APLICAÇÕES PRÁTICAS
O planeamento dos ciclos semanais de treino assume-se como um desafio para os
treinadores, em parte pela complexidade que emerge da necessidade de combinar o
treino das capacidades físicas com o aperfeiçoamento das habilidades técnico-táticas.
Por um lado, o desenvolvimento da força muscular requer sessões de treino com
intensidades específicas que induzam adaptações neuromusculares significativas. Por
outro, a procura por estímulos fisiológicos e técnico-táticos de elevada intensidade e
variabilidade faz com que os treinadores optem frequentemente por jogos reduzidos
durante todo o ciclo anual. Neste sentido, o aprofundar de conhecimento nestes dois
tópicos configuram um problema de grande interesse para o avanço do treino
desportivo.
Procurando dar resposta a este problema, a primeira parte deste trabalho foi constituída
por dois estudos centrados nos efeitos agudos de unidades de treino de força na resposta
fisiológica, percetual, ações técnico-táticas e impulsão vertical em sessões de treino de
Andebol. Verificou-se que as unidades de treino de força precedentes a sessões de treino
constituídas por jogos reduzidos induziram valores mais elevados de frequência
cardíaca e perceção subjetiva do esforço. Mesmo com um número reduzido de
jogadores (3x3), o treino de força promoveu aumentos do tempo passado em zonas
elevadas de frequência cardíaca. Assim, a colocação de uma sessão de treino de força
máxima antes de uma unidade de treino que inclua jogos reduzidos parece ser uma
estratégia eficiente para o desenvolvimento da performance aeróbia em contexto de
jogo. Apesar disso, os resultados mostram que a capacidade de salto diminuiu
imediatamente após o treino de força máxima, com uma deterioração ainda mais
significativa após os jogos reduzidos 3x3 com treino de força antecedente,
provavelmente pela fadiga aguda e diminuição da potência muscular. Como
consequência, o maior estímulo fisiológico verificado durante os jogos 3x3 pode afetar
a eficiência de algumas ações técnico-táticas, sobretudo quando existe treino de força
antecedente.
Os jogos 3x3 parecem ser os mais indicados para o aumento da frequência de ações
individuais e estabelecimento de um padrão de jogo mais imprevisível, embora as
tomadas de decisão do jogador com bola pareçam estar limitadas. Por outro lado, os
jogos 6x6 diminuíram o número de contactos individuais com a bola e aumentaram a
variabilidade do estímulo, convergindo num padrão de resposta fisiológica mais
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Capítulo 6
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intermitente. Para além disso, o 6x6 aumentou o número de passes, receções e
interceções, sugerindo uma maior interação e cooperação entre jogadores. Os valores de
impulsão vertical após os jogos 6x6 foram, no geral, superiores aos verificados no
momento após o treino de força. Assim, utilizar sessões de treino de força máxima antes
de jogos 6x6 poderá aumentar a intensidade do estímulo sem prejuízo da eficiência
técnico-tática.
Para além dos efeitos da combinação de sessões de treino com múltiplos objetivos, a
caracterização dos perfis de treino nos jogos desportivos coletivos é bastante omissa na
literatura disponível. Em particular, a descrição dos perfis de performance em idades
jovens é indispensável para um planeamento adequado e que respeite as necessidades
que os jogadores apresentam nos seus diferentes estados de maturação. Mais, conhecer
os critérios utilizados pelos treinadores na organização das sessões de treino pode ajudar
a definir estratégias de planeamento que facilitem a deteção de talentos e a otimização
da resposta fisiológica aos estímulos. Neste sentido, a segunda parte do presente
trabalho focou-se na descrição de perfis físicos e fisiológicos de sessões de treino de
futebol e na otimização da carga de treino através do estabelecimento de critérios para a
classificação dos jogadores.
Observou-se que a elevada variabilidade na resposta aos estímulos foi uma
característica chave transversal a todos os escalões (sub-15, sub-17 e sub-19). Para além
disso, os perfis de carga externa variaram em função da idade. As unidades de treino
sub-15 focaram-se em jogos reduzidos dirigidos ao desenvolvimento de princípios
técnico-táticos base, o que resultou na diminuição do estímulo fisiológico. Os jogadores
sub-17 percorreram as maiores distâncias totais e em sprint, consequência de sessões de
treino principalmente constituídas por jogos reduzidos pouco constrangidos. Os
jogadores sub-19 registaram um perfil de atividade intermitente de baixa intensidade,
em parte porque os exercícios de treino eram frequentemente interrompidos para que os
treinadores pudessem ajustar o modelo tático da equipa. Na verdade, a crescente
preocupação com os aspetos táticos do jogo pode comprometer o padrão fisiológico
exigido durante as competições de elite. Caso pretendam aumentar a intensidade do
estímulo, os treinadores deverão privilegiar mais situações de jogo pouco constrangidas.
De um ponto de vista prático, os treinadores parecem estar cientes da importância do
desenvolvimento das habilidades técnicas em idades mais jovens. À medida que a idade
biológica avança, as situações de jogo parecem ser incluídas com mais frequência nas
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Capítulo 6
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unidades de treino, emergindo perfis técnicos, táticos e físicos mais próximos do padrão
competitivo.
A organização da maior parte das competições jovens baseia-se em critérios
relacionados com a idade dos jogadores. Respeitando a linha destes modelos, muitos
clubes e treinadores optam pela distribuição dos jogadores no treino em função do seu
escalão etário. Foi sugerido um modelo de classificação alternativo a este método
tradicional, apresentando alguns preditores de performance para o estabelecimento de
grupos de treino homogéneos. No geral, os resultados demonstraram que jogadores com
idades e anos de experiência idênticos podem apresentar perfis fisiológicos divergentes.
Assim, a organização de grupos baseada em perfis físicos e fisiológicos semelhantes
pode reduzir a variabilidade da resposta fisiológica e permitir a obtenção de informação
mais precisa sobre a resposta dos jogadores aos estímulos de treino. Por esse motivo, os
treinadores não deverão recear o agrupamento de jogadores com diferentes idades, anos
de experiência e postos específicos durante as sessões de treino. Uma vez que as
variáveis fisiológicas são sugeridas como preditores importantes na identificação de
talentos, esta distribuição por grupos de performance também pode providenciar perfis
de referência para a identificação de talentos em idades jovens.
Os resultados desta tese apresentam dados com implicação direta no planeamento a
curto prazo nos jogos desportivos coletivos. Os treinadores e preparadores físicos
encontram nestes estudos informação que permite manipular, com critério, a
organização de um ciclo semanal com sessões de treino dirigidas a múltiplos objetivos.
A combinação entre o treino de força e o treino de campo sempre levantou algumas
questões, que agora parecem um pouco mais claras. Quando o objetivo passa pelo
desenvolvimento da performance aeróbia, o treino de força máxima pode ser combinado
com sessões de campo, mesmo que estas sejam de intensidade elevada. Por outro lado,
se o foco estiver dirigido para o aperfeiçoamento das habilidades técnico-táticas, as
sessões de campo deverão privilegiar formas jogadas que proporcionem padrões de
performance de maior variabilidade, como o 6x6. Neste caso, como a intensidade do
estímulo é menor, o treino de força pode ser colocado antes da sessão de campo com o
propósito de promover o aumento da intensidade sem prejuízo da performance técnicotática.
Adicionalmente, esta tese faculta informação prática para que os treinadores possam
selecionar as tarefas que melhor otimizam a resposta ao estímulo dos jogadores durante
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Capítulo 6
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as sessões de campo. Quando os treinadores optam por tarefas dirigidas ao
desenvolvimento de princípios técnico-táticos básicos, a carga externa de treino é mais
reduzida. Por outro lado, se as situações de jogo forem privilegiadas com mais
frequência, os perfis de performance irão aproximar-se do padrão competitivo, tanto
mais quanto menores forem os constrangimentos. Complementarmente, o critério da
idade tem que ser destituído como o mais importante na organização de uma sessão de
treino. Caso contrário, jogadores com perfis de performance mais elevados poderão ter
o desenvolvimento do seu potencial motor comprometido por um estímulo que não
corresponde às suas necessidades. Assim, tanto a seleção das tarefas de treino como o
seu modelo de organização parecem interferir nos perfis de carga dos jogadores. Em
suma, esta tese disponibiliza informação prática para que o planeamento do microciclo
semanal e das respetivas unidades de treino seja mais eficiente e adequado ao
desenvolvimento da performance dos jogadores.
Figura 6.1. Representação esquemática das principais aplicações práticas (resultados do
presente trabalho).
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