UNIVERSIDADE DE LISBOA
FACULDADE DE MOTRICIDADE HUMANA
Decision making in Volleyball’s serve reception
Ana Margarida do Amaral Paulo
Orientadores: Prof. Doutor Duarte Fernando da Rosa Belo Patronilho de Araújo Prof. Doutor Frank T. J. M. Zaal
Tese especialmente elaborada para obtenção do grau de Doutor em Motricidade Humana, na Especialidade de Treino Desportivo
UNIVERSIDADE DE LISBOA
FACULDADE DE MOTRICIDADE HUMANA
Decision making in Volleyball’s serve reception
Ana Margarida do Amaral Paulo
Orientadores: Prof. Doutor Duarte Fernando da Rosa Belo Patronilho de Araújo Prof. Doutor Frank T. J. M. Zaal
Tese especialmente elaborada para obtenção do grau de Doutor em Motricidade Humana, na Especialidade de Treino Desportivo
Júri:
Presidente: Doutor Francisco José Bessone Ferreira Alves
Professor Catedrático e Presidente do Conselho Científico Faculdade de Motricidade Humana da Universidade de Lisboa
Vogais: Doutora Isabel Maria Ribeiro Mesquita Professora Associada com Agregação
Faculdade de Desporto da Universidade do Porto
Doutor Duarte Fernando da Rosa Belo Patronilho de Araújo Professor Associado com Agregação
Faculdade de Motricidade Humana da Universidade de Lisboa
Doutor Ralf Krede Professor Associado
Institute of Sport Science of the University of Bern (Suiça)
Doutor Jorge Manuel Castanheira Infante Professor Auxiliar
Faculdade de Motricidade Humana da Universidade de Lisboa
Doutor João Herculano Pessanha de Carvalho Professor Adjunto
Escola Superior de Educação e Comunicação da Universidade do Algarve
A presente tese foi financiada pela Fundação para a Ciência e a Tecnologiamediante a bolsa individual SFRH/BD/68692/2010 outorgada a Ana Paulo.
Agradecimentos
A lista de pessoas a agradecer é longa e considero-me muito afortunada por isso. Tenho de começar por agradecer àqueles que contribuíram para que o voleibol fosse uma parte tão marcante da minha vida, na definição dos meus valores, da minha profissão e da minha vida académica. Agradeço ao meu primeiro treinador, o Sr. Diamantino e à minha grande amiga e parceira de voleibóis Inês Vaz, a oportunidade e a partilha dos primeiros passos como atleta de voleibol. Agradeço aos treinadores marcantes, António Ferreira, Jorge Martins, Luís Lucas, José Machado, Carlos Dias, António Guerra, Alberto Carvalho e Juan Diaz pelas oportunidades, ensinamentos, mas acima de tudo pela cultura da superação pessoal e da amizade que incutiram em cada treino e em cada jogo. Agradeço a atletas extraordinárias com quem tive o privilégio de partilhar o campo, Cristina Pereira – o meu modelo a seguir, e Filipa Duarte. Foi uma aprendizagem constante, obrigada. Ficou a amizade e a lição de que as nossas maiores limitações são as que colocamos a nós mesmos. Tudo é possível.
Fico grata ao José Afonso pela amizade, e pela partilha da paixão pelo voleibol, e consequentes discussões acesas das quais tenho saudades.
Se estou aqui hoje devo-o à Professora Doutora Isabel Mesquita. Agradeço-lhe os primeiros passos dados na investigação. Agradeço-lhe esta outra forma de olhar para o desporto, para o voleibol, que marcou profundamente a minha vida e as minhas opções/oportunidades profissionais.
Agradeço à Faculdade de Educação Física e Desporto da Universidade Lusófona, na pessoa do professor doutor Jorge Proença, onde fui docente durante grande parte do tempo em que durou a feitura desta tese. Agradeço o incentivo e o apoio incondicional, formal e informal, que me ajudaram enormemente a conciliar a função de docente com a de investigadora. Agradeço ainda aos meus colegas e amigos Ana Margarida Sousa e António Lopes pelos momentos de encorajamento, pelas trocas de ideias e pelo questionamento. Agradeço particularmente à professora doutora Sofia Fonseca, minha co-autora, pela amizade e pelo apoio em parte das análises dos estudos experimentais. Sem ti teria sido muito mais difícil. Obrigada!
vadias”, o incentivo ao pensamento crítico e ao autoquestionamento. Guardo o profundo saber fazerque tiveram a generosidade de partilhar comigo.
Agradeço ao clube Sport Lisboa e Benfica, na pessoa do professor José Jardim, treinador da equipa sénior masculina, pela possibilidade de recolha de imagens e dados referentes ao meu primeiro estudo experimental. Agradeço no mesmo sentido à Federação Portuguesa de Voleibol pela disponibilidade em colaborar nos segundo e terceiros estudos experimentais, mais particularmente, agradeço ao director técnico nacional (à época) Daniel Lacerda, e aos seleccionadores nacionais (à época) Juan Diaz e Hugo Silva.
Agradeço à Maria Carlos a ajuda preciosa dada na recolha de dados referente ao segundo estudo experimental. Agradeço também à professora Francisca Esteves pela ajuda nos procedimentos de fiabilidade da observação realizados no segundo estudo da tese.
Agradeço a ajuda pontual mas incisiva do professor doutor Orlando Fernandes na operacionalização do software Labbio e, no que concerne ao último estudo experimental, na obtenção dos dados. Obrigada pela paciência e disponibilidade.
Estou muito agradecida aos membros e ex-membros do Laboratório de perícia no desporto – Anna Volossovitch, Leonor Moniz Pereira, António Paulo Ferreira, Francesca Pecorella, João Carvalho, Vanda Correia, Pedro Esteves, José Lopes, Ricardo Duarte, Luís Vilar e Bruno Travassos. Agradeço a generosidade na partilha, o debate, o questionamento, e acima de tudo a amizade. Um muito obrigado especial ao professor Jorge Infante e ao Paulo Caldeira pela partilha do bichinhodo voleibol que alimentou algumas conversas de que tenho saudades. À Inês Santos tenho de agradecer duplamente, já que para além do anteriormente mencionado esteve sempre disponível para ouvir, incentivar, ajudar, … Não vou esquecer e ficarei para sempre agradecida.
Agradeço também ao Professores Pedro Passos e Pedro Mil-Homens, elementos das minhas CATs os comentários assertivos que contribuíram para a melhoria do trabalho aqui apresentado.
Quero ainda agradecer ao meu orientador professor doutor Duarte Araújo pela oportunidade de me deixar trilhar o meu caminho, por me permitir desenvolver a minha autonomia enquanto investigadora, sem nunca me ter sentido desamparada. Ficarei para sempre agradecida.
Acknowledgements
On the international side there are also a few people that I have to acknowledge. First, of course I would like to thank Professor Frank Zaal for accepting the challenge of co-advising me. But beyond that I have to acknowledge the attentive, assertive, and constructive approach he took during that process. I will be forever in debt to you.
Secondly, I would like to thank Professor Ludovic Seifert for receiving me so generously in Rouen, and for the relevant addition that my opportunity to collaborate with you brought to my training as a researcher.
I would also like to thank Jelle Bruinberg for the kindness and availability to have some very interesting discussions, and for the invitation to participate, with some of the work included here, in the Satellite Symposium: "Skilled Action as a Complex System: Affordances and Social Coordination", withheld in the Conference on Complex Systems 2016 in Amsterdam, The Netherlands. It was not only a privilege for me to share the floor with such prestigious company – you, Professor Erik Rietveld, Professor Mike Richardson, and Professor Ralph Cox, but it was also a boost of confidence in a moment when I really needed it. So, thank you very much. On the same note I have to also thank Professors Mike Richardson and Rachel Kallen for the feedback offered on the work I presented.
Note:
This thesis is based on the following work:
Publications:
Paulo, A., Seifert, L., & Araújo, D. (to-be-submitted). Theoretically grounding performance analysis for team sports: Volleyball as an example.
Paulo, A. Davids, K., & Araújo, D. (accepted for publication). Co-adaptation of ball reception to the serve constrains outcomes in elite competitive volleyball. International Journal of Sports Science & Coaching.
Paulo, A., Zaal, F., Fonseca, S., & Araújo, D. (2016). Predicting Volleyball Serve-Reception. [Original Research]. Frontiers in Psychology, 7(1694). doi:
10.3389/fpsyg.2016.01694
Paulo, A., Zaal, Frank T.J.M., Seifert, L., Fonseca, S. & Araújo, D. (accepted for publication). Predicting volleyball serve-reception at group level. Journal of Sports Sciences.
Paulo, A., Zaal, Frank T.J.M., Fonseca, S., Fernandes, O., & Araújo, D. (to-be-submitted). Skilled adaptation to task constraints in expert volleyball serve-reception at the individual
Congress Presentations:
Some exploratory results of this thesis have been presented in international scientific congresses with refereeing and published in abstract books:
Paulo, A., Zaal, F., & Araújo, D. (2013). Informational constraints to the decision of passing a volleyball serve. In P. Passos, J. Barreiros, R. Cordovil, D. Araújo & F. Melo (Eds.), XVIIth International Conference on Perception and Action(pp. 49). Estoril, Portugal: Edições FMH.
URL: http://www.fmh.utl.pt/icpa17/images/doc/BAICPAXVII2013_1.pdf
Paulo, A., Araújo, D., & Zaal, F. T. J. M. (2014). Predictive models of Volleyball serve-reception's efficacy and action mode. In H. J. de Poel, C. J. C. Lamoth & F. T. J. M. Zaal (Eds.), 4th International Congress on Complex Systems in Sports & Healthy Ageing(pp. 32). Groningen, The Netherlands: University of Groningen.
URL: http://www.ic
css-groningen2014.com/uploads/1/8/1/1/18119635/abstractbook_iccssha_2014_afterconf.pdf
Paulo, A; Zaal, F.; Seifert, L.; Fonseca, S.; Araújo, D. (2016, July 6-8 July) Predicting Volleyball Serve-reception at group level. Accepted oral presentation at the 14 European Workshop on Ecological Psychology, Groningen, The Netherlands. Oral presentation included in the Symposium Ecological psychology as a basis for the study of sport expertise, co-organized by A. Paulo, M. Dicks, B. Guignard, and D. Orth.
URL(Workshop): http://ewep14.nl/
Paulo, A., Zaal, F., Fonseca, S., & Araújo, D. (2016, 19-22 September). Skilled
collaboration in Volleyball reception. Oral presentation at the Conference on Complex Systems 2016, Amsterdam, The Netherlands. URL:
Visiting Research:
Between the fourth and the 14th June, 2011, I visited the Center for Human Movement Sciences of the University Medical Center – University of Groningen, in Groningen, The Netherlands. This visit and the opportunity to accompany the ongoing research projects of the institute contributed to my training in what concerns the dynamics of perception and action, particularly with respect to object interception. It also permitted relevant discussions on the subject, and the particular applications to my research project, with my co-advisor professor Frank Zaal and professor Gert-Jan Pepping, a known author on decision making in sport.
Decision making in Volleyball’s serve reception
Abstract
We aimed at investigating decision making in volleyball serve-reception. Grounded in the ecological dynamics framework, we focused on task constraints. First, in a systematic review we discussed the relevance of functionally-relevant tasks for performance analysis. This notion was developed with respect to relevant sources of constraint and behavioral variables for team sports performance analysis in general, and for volleyball in particular. Next, in an observational study of an expert-level competition we showed that, in serve-reception, adaptive flexibility in action-mode selection relates to competitive outcomes. The three experimental studies that followed involved manual-tracking of ball and receiver(s) and 3D world-coordinates reconstruction. First, we used an individual serve-reception task, in two delimited zones on-court. The receiver’s initial position was the stronger predictor of the action mode selected and for the effectiveness of the serve-reception. In a second study we used a three-man serve-reception task. The definition of the receivers’ reception-areas at the ecological scale was highly accurate in selecting “who” receives a given serve. Also, variables related to the serve, and to the relative position of the receiver, of other receivers, the ball, and the target contributed to a very strong model for action-mode selection. Furthermore, only the underhand-lateral pass, not the overhand or the underhand-frontal passes, increased the odds of less effective serve-receptions. A final experimental study focused on both the individual (receiver) and the group (three-receivers-system) levels of analysis of serve-reception performance. Receivers were differently constrained, individually and collectively, by relevant sources of constraint (on-court position, role, and serve mode). Adaptation to the task at the individual (initial position) and at the collective (receiver area) levels allowed the prediction of the action-mode selected but not reception efficacy. Overall, adaptive flexibility, through action mode selection, was supported as a way to deal with task constrains in order to remain effective.
Tomada de decisão na recepção ao serviço em voleibol
Resumo
Com a dinâmica ecológica como referencial teórico, estudámos a influência dos constrangimentos da tarefa na tomada de decisão na recepção ao serviço em voleibol. Primeiro, numa revisão sistemática da literatura discutimos a relevância de tarefas funcionalmente relevantes. Esta noção foi desenvolvida quanto a fontes de constrangimento e variáveis comportamentais relevantes para a análise da performance em desportos de equipa em geral, e no voleibol em particular. Seguidamente, num estudo observacional de uma competição de peritos, mostrámos, para a recepção ao serviço, que a flexibilidade adaptativa na selecção do modo de acção se associa ao resultado competitivo. Nos três estudos experimentais que se seguiram digitalizámos manualmente a bola e o(s) recebedor(es), e subsequentemente reconstruímos em 3D as suas coordenadas reais. Numa tarefa de recepção individual, em duas zonas delimitadas no campo, a posição inicial do recebedor foi o maior preditor do modo de acção seleccionado e da eficácia da recepção ao serviço. Numa segunda tarefa com três recebedores, a definição das áreas de recepção à escala ecológica foi altamente precisa na selecção de “quem” recebe o serviço. Variáveis relacionadas com o serviço e com a relação do receptor com outros recebedores, com a bola e com o alvo contribuíram para um forte modelo de selecção do modo de acção. Ainda, a manchete-lateral, não o passe ou a manchete-frontal, aumentou as chances de recepções do serviço menos eficazes. Por último, abordámos ambos os níveis de análise individual (receptor) e grupal (sistema de três receptores) na recepção ao serviço. Os receptores foram constrangidos diferentemente, individual e colectivamente, por fontes de constrangimento relevantes (posição no campo, papel, e tipo de serviço). A adaptação individual (posição individual) e colectiva (área de recepção) à tarefa permitiu a predição do modo de acção seleccionado mas não da eficácia da recepção ao serviço. No geral, a flexibilidade adaptativa, através da selecção do modo de acção, demonstrou ser uma forma de lidar com os constrangimentos da tarefa no sentido de manter a eficácia.
Table of Contents
4.3.5 Analysis ... 82 4.4 Results... 82 4.5 Discussion ... 85 4.6 Conclusion ... 90 4.7 Conflict of Interest... 90 4.8 Author Contributions ... 90 4.9 Funding ... 90 4.10 Acknowledgments ... 90 4.11 References... 91 5 Predicting volleyball serve-reception at group level... 94 5.1 Abstract... 95 5.2 Introduction ... 96 5.3 Methods ... 99 5.3.1 Sample ... 99 5.3.2 Experimental task... 99 5.3.3 3D reconstruction ... 99 5.3.4 Variables... 100 5.3.5 Analysis ... 103 5.4 Results... 104 5.4.1 Selection of “who” receives the serve ... 104 5.4.2 “How” the serve is received ... 104 5.4.3 Action mode selection and reception efficacy... 109 5.5 Discussion ... 110 5.5.1 Selection of “who” receives the serve ... 110 5.5.2 “How” the serve is received ... 110 5.5.3 Action mode selection and reception efficacy... 112 5.6 Conclusions... 113 5.7 Acknowledgments ... 114 5.8 Disclosure of interest ... 114 5.9 References... 114 6 Skilled adaptation to task constraints in expert volleyball serve-reception at the individual and receivers-system levels ... 119
List of Figures
Figures were numbered following chapter number.
Figure 2.1 Exemple of play dynamics in team sports. Throughout a match, tasks can be defined at the individual/dyadic level of behavioral analysis – (a) reaching/steering to the goal, (b) interacting (collaboration/opposition) with nearby agents, and (c) intercepting/avoiding the ball/opponents; and at the group level (social synergy) – (d) collaborating with teammates to reach the target, or avoid opponets to do so, (e) collaborating with teammates to intercept the ball, and (in the right side of the figure) team-team interaction. The actions within these tasks are also constrained organismically (e.g., players action capabilities) and environmentally (e.g., target position or court boundaries), and by relevant events(e.g., last play of the set) and time. Also the collective level increases or limits the action possibilities locally, and the players, by engaging with their surroundings (acting on affordances) given their task goals, shape the behavior of the collective, throughout the match... 35
Figure 2.2Flow diagram of the methodology used for the search and selection of articles. ... 38
Figure 2.3Synthesis of the tasks selected in the sample of articles. Values in brackets stand for the frequency in the article-sample. There were cases (see Supplemental material Appendix B, Online resource 2) where more than one task was targeted in the article. KI: complex I; KII: complex II. ... 39
Figure 3.1 ROC curve representation of the co-adaptation of serve and reception action modes discriminative power between won and lost sets. Sensitivity = 1 if model selects all wins; 1-Specificity = 1 if model selects only wins... 66
Figure 4.1Experimental set-up. The two reception zones are labelled as z1 (zone 1) and z5 (zone 5). ... 80
Figure 4.2Depiction, case-by-case, of the relation of the modelled type of pass prediction with the receiver’s initial position (distance from the net). In the Y axis “1” corresponds to predicting the underhand pass and “0” to predicting the overhand pass. Cases are labelled by the direction of the receiver’s displacement (to the front or to the back) and panelled by reception zone – zone 1 (A) and zone 5 (B)... 88
Figure 5.1 Representation of a volleyball half-court (the net is the bottom line). (A) Depiction of individual areas as indicated in the coaching literature (Coaches Manual, 2011; González-Silva, et al., 2016; USA Volleyball, 2009) and (B) GVD-based court-assigned “dominant regions”, to a three-man volleyball reception line-up. From the receiver’s perspective, R5: receiver in the left-side of the court, R1: receiver on the right-side, and R6: receiver in the middle. ... 97
Figure 5.3 Diagrams showing the relationship between serve initial velocity and time of maximum ball height for every serve (N = 181). In panel A, only serves received by overhand pass (N = 20) or underhand-frontal pass (N = 100, model’s reference category) predicted by the model are presented. In panel B, only serves received by underhand-lateral (N = 61) and underhand-frontal passes predicted by the model are presented... 106
Figure 5.4 Relation of the receiver’s longitudinal target-distance with the BRT angle’s values at the serve net-crossing. (A) Depiction of this relation for every trial (N = 120); the model predicted the overhand (N = 20) and the underhand-frontal (N = 100) passes, paneled by the receiver’s on-court position – R5 (N = 40), R1 (N = 40), and R6 (N = 40). (B) Depiction of the same relation but only when R5 was the receiver (N = 40), paneled by the provenance of the serve – from in front of R5 (N = 19); from a mid-court position (N = 13), and from across-court position (N = 8). Reference lines were added to the x axis (at 35º) and the y axis (at 4.5m)... 107
Figure 5.5 Relationship between changes in BRT angle from initial-to-final values with changes in RBA angle from net-to-final values for every trial (N = 181). The model predicted the overhand (N = 20), underhand-lateral (N = 61), and underhand-frontal (N = 100) passes. This relationship is paneled by the receiver’s on-court position – R5, R1, and R6. Reference lines were added to the x axis (at 30º) and the y axis (at 20º). Based on these reference lines four quadrants were established: Q1, Q2, Q3, and Q4... 108
Figure 6.1Representations of the volleyball court. In the first court (S1), on the top half-court, the rotation of the players on-court is illustrated. In the six court-representations, on the bottom half-court, the reception line-up in the rule-allowed six possible conditions is depicted. The setter (S) on-court position (from positions “1” to “6”) was used as reference (e.g., S1 displays the receivers’ on-court relative positions when the setter is in position “1”. In every case there are two attacker-receivers (FR: front-row attacker-receiver; BR: back-row attacker-receiver) and one libero (L) in the reception line-up. The arrows express where the FR and the BR attack; i.e. near the net and behind the three-meter line, respectively. The FR attack takes place in the left-side of the court (receivers’ perspective) in every condition with the exception of S1. This also means that the front-row receiver is never in the middle position. To be noted also that the libero never receives in the left-side of the court. ... 125
Figure 6.2Depiction of the initial position of the receivers (distance from the net), per the on-court position of the receivers (A) and their role (B). The initial position of the receivers is compared per the type of serve faced (JFS: jump-float serve; PJS: power-jump serve). Error bars stand for standard deviation... 130
Figure 6.3 Depiction of the size of the reception-areas of the receivers (percentage of the half-court area), per the on-court position of the receivers (A) and their role (B). The size of the reception-areas is compared per the type of serve faced (JFS: jump-float serve; PJS: power-jump serve). Error bars stand for standard deviation. ... 132
Figure 6.5 Depiction of receivers’ initial positions (x,y) in every trial (N = 195), projected in a volleyball half-court (9mx9m) labelled by the type of serve faced. JFS: jump-float serve (N = 114); PJS: power-jump serve (N = 81). ... 136
List of Tables
Tables were numbered following chapter number.
Table 2.1Sources of constraint mentioned in the article-sample... 41
Table 2.2 Illustration of the behavioral variables mentioned in the article-sample... 43
Table 3.1Description of the variables in the study and of their categories. ... 63
Table 3.2 Binary Logistic regression results on set outcome a in 363 receptions, with the co-adaptation of serve and reception action modes as predictor. ... 67
Table 3.3 Association of the co-adaptation of serve and reception’s modes with the set result for the total sample, and for the first and last sets. ... 68
Table 4.1Characterization of serve and receiver’s potential predictor-variables ... 83
Table 4.2Final Binary Logistic Regression model of type of pass... 84
Table 4.3Final multinomial Logistic Regression model of reception efficacy ... 85
Table 5.1Multinomial logistic regression analysis of the reception technique in 182 receptions ... 105
Table 5.2Multinomial logistic regression analysis of the efficacy in 182 receptions with reception technique used as predictor... 109
List of Abbreviations
FR-tasks: functionally relevant tasks
KI: complex I
KII: complex II
Reception: serve-reception JFS: jump-float serve
PJS: power-jump serve
FB: forward-backward (displacement) GVD: generalized Voronoi diagram
R1: receiver in the right-side of the court (receiver perspective) R5: receiver in the left-side of the court (receiver perspective) R6: receiver in the middle
RBA: receiver’s ball alignment (angle) BRT: ball-receiver-target (angle)
ROC: receiver operating characteristics (curve) IQR: interquartile range
OR: odds ratio
1.1 Introduction
In volleyball, as in other team sports, a key topic in the study of the game has been understanding how the efficacy of game actions – the serve, the serve-reception, the attack, the block, etc., relates to competitive performance (see for reviews Mesquita, Palao, Marcelino, & Afonso, 2013; Silva, Marcelino, Lacerda, & João, 2016). As an example, recently, Silva, Lacerda, and João (2014) assessed which game-related skills discriminated winning from losing in top-level competitive volleyball. They found that serve points and reception errors were the two key variables that best discriminated between winning and losing a match. However, in their study, these game actions were assessed separately as if their performance was independent of each other. Assessing serve and serve-reception efficacy as they are usually assessed (rating scales, e.g., Eom & Schutz, 1992) leaves unclear the co-adaptive nature of the interactions between the receivers and the server in the emergence of performance outcomes (see also Afonso, Moraes, Mesquita, Marcelino, & Duarte, 2009). A serve-reception outcome, whether effective or ineffective, emerges from the constraints posed by the serve, among other constraints. Moreover, to advance the understanding of the game, we must go beyond the efficacy of game actions and try to understand how and why they become effective. This implies a theoretical framework for guiding research.
making here is seen as an integral part of goal-directed behavior. Decisions are grounded, i.e. expressed behaviorally through actions in performance contexts (Araújo, Davids, & Hristovski, 2006). Within the ecological dynamics framework, decision making emerges at the ecological scale from the interaction of individual, environmental, and task constraints (see Newell, 1986; Newell & Jordan, 2007) over time towards the reaching of specific task goals (Araújo, et al., 2006). Following this approach, here we are focused on understanding serve-reception decision making. The receiver is constantly challenged for making decision on how to act given his/her position in relation to the court, to the serve, to the other receivers in the team, and/or to his/her following actions (e.g., attacking). We hypothesize that the presence/absence of these sources of constraint in reception tasks influence the emergent behavior. Understanding how reception performance changes (action mode selected and reception efficacy) in these different tasks can be relevant for future practices entailing the manipulation of these task constraints in order to magnify/decline their allure.
the receivers-system behavior and at the same time remodels continually those boundaries, with respect to other relevant constraints and the behavior afforded, towards a task goal.
1.2 Outline of the present thesis: A Preview
This thesis is comprised by five articles: i) a systematic review article, ii) an observational study; and iii) three experimental studies. These studies are published, in press, under review, submitted, or to be submitted for publication in peer-review journals with WoS Impact Factor. Each article represents a chapter in the thesis structure. Each chapter is presented as an individual article following the format requested by the journal of submission/publication in respect to its sections (i.e., abstract, introduction, methods, results, discussion and references). The references for the general introduction and the general discussion are presented at the end of the thesis (section 8).
not a priori defined they emerge from the interaction with the constraints of the performance environment.
The first chapter is a review article (Theoretically grounding performance analysis for team sports: Volleyball as an example) focused on performance analysis in team sports. A reflection is presented on the merits of an empirically-based versus a data-based research paradigm. Ecological dynamics was offered as the framework to lead research in performance analysis in team sports. The premise of the emergence of the performance at the ecological scale was discussed based in the different levels of perception-action systems– individual, group and team, and how they interact in functionally-relevant tasks for team sports. Functionally-relevant tasks were defined as those where the task-goal, the time-frame, and the emergent behavioral patterns relate to successful performance in a given team sport. With respect to the operationalization of future performance-analysis research in team sports, grounded in the ecological dynamics, it should integrate theoretical knowledge, empirical data and research methodology, as well as experiential knowledge from pedagogical practice and application (Davids, 2016). Following this rationale, we performed a systematic review on Volleyball performance analysis research. The 40-years article-sample was analyzed with respect to the tasks considered, the constraints to the performance mentioned, and the behavioral variables used to capture volleyball performance. This information was the base for suggestions offered for future ecological-dynamics-driven research in volleyball performance analysis.
action mode over the others. This co-adaptation was hypothesized to have implications on competitive performance.
In chapter three (Predicting Volleyball Serve-Reception) we performed a first experimental approach to the study of volleyball serve-reception decision making, and focused on an individual serve-reception task with simplified task constraints: two delimited reception areas on the court; and the serve mode used by the servers was only the jump-float serve coming from a frontal position to the receiver. We aimed at understanding how the interaction between the serve and the actions of the receiver determines the action mode selected in serve-reception and its efficacy.
But in expert competition the serve-reception task is undertaken by three receivers. So, in a second study we used a three-man reception task. At this level, another aspect is present that adds to the questions razed in the previous study setting. Who, from the three receivers will intercept the serve? The generalized Voronoi diagram (see Fonseca et al., 2014) was proposed as a more adequate measure for how the receivers share the court space, as in the definition of their assigned reception areas, than the “corridor-approach” suggested in volleyball coaching literature (Coaches Manual I, 2011; González-Silva, Moreno Domínguez, Fernández-Echeverría, Claver Rabaz, & Moreno Arroyo, 2016; USA Volleyball, 2009). So in this fourth chapter (Predicting volleyball serve-reception at group level) we aimed to understand how a reception comes to be effective by addressing questions including “who” receives/passes the ball, what task-related variables predict the action mode selected and whether the action mode selected predicts reception efficacy.
In the final experimental study, in chapter five, we included both the individual (receiver) and the collective (receivers-system) in the analysis of the skilled adaptation of expert receivers to their performance environment (Skilled adaptation to task constraints in expert volleyball serve-reception at the individual and receivers-system levels). We set out to study how expert receivers adapt to relevant sources of constraint (serve mode; receiver on-court position; and receiver role) in volleyball serve-reception at both the individual and receivers-system level, and whether that adaptation would relate to the action mode selected and the efficacy of the reception action.
2 Theoretically grounding performance analysis
for team sports: Volleyball as an example
2.1 Abstract
Performance analysis has been used for long to overcome limitations of personal perspectives and to provide more unbiased information in the understanding of sport performance. Here we are focused on team-sports performance where the inference of causality of the performance is difficult to establish due to the complexity of interactive behaviors that characterizes it. We propose that performance-analysis research can benefit from having the ecological dynamics framework guiding the research. Five points are developed on that argument. First, that performance rests in the assumption of behavioral dependence, thus that performance analysis must focus on interactions and relations. Second, that the perceptual-action system must be analyzed at the ecological scale: i) taking into account different sources of constraint (individual, environmental, and task); and ii) allowing the analysis at different levels (individual, group, and teams) to contribute to the performance understanding. Third, this analysis must take place in functionally-relevant tasks. These are defined as those tasks where the goal, the time-frame, and the emergent behavioral patterns relate to successful performance in a given team sport. Four, we advocate for adaptive flexibility as the way to potentiate performance in team sports. Adaptive flexibility is seen as more functional, since a robust competitive outcome can be achieved consistently by different movement patterns, and the same perception-action system is able to undertake diverse functions. Finally, five, we explored in a systematic review, exemplarily, previous performance-analysis research in Volleyball in light of the previously stated arguments, to fuel future performance-analysis research grounded in the ecological dynamics framework.
2.2 Introduction
Performance analysis has been recurrently used in team sports for a long time. The rationale for using it is to overcome the limitations of personal perspectives and to provide more unbiased information to achieve a greater understanding of sport performance (O'Donoghue, 2009). But in our view the dominance of data-driven research, and therefore, the lack of a theoretical framework supporting the research, has been limiting the intervention potential of performance analysis research.
In the present paper, we are focused on team sports performance where the inference of causality of the performance is difficult to establish due to the complexity of interactive behaviors that characterizes it, where a large number of factors can be relevant to the results (Hughes, 2004). The recent technological advancements have impacted performance analysis research. The large improvements in terms of data gathering, storing and analysis allow for more studies, with a substantial reduction in the time consumed (O'Donoghue, 2009). But there are concerns regarding the impact of Big Data, Datafication or Dataveillance (Komar, 2015; Williams & Manley, 2014) on athlete behaviors during practice, training and competition, as well as pedagogical practice (Davids, 2016). In our view it is not the data available that relates to adequate practical applications; it is the theoretically-grounded, evidence-based research. Performance analysis research has been fueled until recently by the biomechanics-notation methods dichotomy (Hughes & Bartlett, 2008), and a lack of theoretical foundation has been a recurrent criticism (O'Donoghue, 2009). So, as an alternative to research datification and methods-based approaches, we understand that performance analysis research needs a theoretical framework to guide the way the performance is conceptualized. Importantly, and as Sparkes (2015) clarifies, a framework is different from methods; methods are techniques or procedural tools used for generating and analyzing data, whereas a framework links epistemology and methods, sustaining why specific methods and procedures are used in a given research. We follow previous contributions (Araújo & Davids, 2016; Araújo, Ramos, & Lopes, 2016; Travassos, Araújo, Correia, & Esteves, 2010; Travassos, Davids, Araújo, & Esteves, 2013; Vilar, Araújo, Davids, & Button, 2012) that suggested the ecological dynamics framework as a suitable candidate for the understanding of team sports performance analysis.
approach in neurobiology (Edelman & Gally, 2001; Price & Friston, 2002; Seifert, Komar, Araújo, & Davids, 2016) have been integrated in this framework to explain sport performance. Team sport competitions are conceptualized as complex dynamical systems composed of many interacting parts (e.g., Passos et al., 2011). This approach describes how movement coordination patterns emerge persist and change (Araújo, Passos, & Volossovitch, 2017) with respect to opportunities for action (affordances, Gibson, 1986) offered by the environment. With respect to performance analysis, this approach focuses on understanding how successful action emerges with respect to a set of constraints such as the complex interaction of physical (e.g., surfaces, areas) and social (e.g., rules) constraints specific to each sport (Araújo & Davids, 2016).
Within the ecological dynamics framework behavior arises at the ecological scale (Araújo, Davids, & Hristovski, 2006), which implies that the performance emerges from the interaction of different sources of constraint – individual, environment, and task (Newell, 1986; Newell & Jordan, 2007). In this review we highlight the importance of the task as a key source of constraints for performance in team sports. In interpreting what we capture we have to attend not only to the more general theoretical conceptualization of the behavior but also to the particularities of each sport as the specific form of life it is (see Davids, 2017; Erik Rietveld & Kiverstein, 2014). Team sports are human activities characterized by a particular organization and functioning in given performance contexts; though there are commonalities, each team-sport’s ecology is distinguished by physical characteristics of locations where the players’ activity takes place, by its social characteristics and cultural aspects (Araújo & Davids, 2016; Araújo, et al., 2017). So it is important to have a solid theoretical basis to define behavior and then to understand it, performance-wise, in a particular team sport, beaconing how to design performance analysis research programs. This ecological scale of analysis also allows the conceptualization of the perception-action system at different levels, e.g., individual-environment, individual-individual-individual-environment, or team-team, depending on the task at hand, as it is discussed in the next section.
illustrate an implementation of this perspective by performing a systematic review on volleyball performance analysis research over a 50 years period (1963-2013). We select volleyball, because, reviewing all team sports was an unfeasible task. Another reason was that most work in team sports performance analysis within the ecological dynamics framework focused on invasion sports, which does not include volleyball. We find relevant to extend the applied scope of the framework to other team sports.
2.3 Team sports performance: Perceiving and acting together
In the ecological dynamics perspective, the world is perceived in terms of affordances (Gibson, 1986). The players move to pick up information for action and to control further movement that generates more information and so on iteratively until the goal is reached or the attempt aborted (Shaw, 2001). This expresses the dynamical feature of affordances, they come and go in a moment-to-moment basis (Fajen, Riley, & Turvey, 2009). Affordances can be seen as invitations for action in situations in which different affordances can be utilized (Reed, 1993; Withagen, de Poel, Araújo, & Pepping, 2012). In a match the player is constantly challenged decision-wise, to dribble or to pass, to respect the defense formation or to go for the ball-interception. Bruineberg and Rietveld (2014) define the multitude of affordances present in a given context a field of affordances, i.e. those affordances that stand out as relevant for a particular player in a particular situation. Skilled interaction with the environment can be understood as responsiveness to such affordances (Bruineberg & Rietveld, 2014; Rietveld, 2013). The specific structure of the field of affordances of a particular individual is dependent on the current concerns and abilities of that player and the current situation (Bruineberg & Rietveld, 2014) (e.g., as the ball changes possession, the field of affordances is influenced by defending or attacking a target). An important part of skilled interaction is therefore not only being skillfully responsive to one affordance (e.g., dribbling towards the target), but also being open to changes in the match-context (e.g., perceiving a better-placed colleague) and adequately engaging with these affordances (e.g., changing from dribbling to passing to that colleague).
common goals (Araújo, et al., 2015). The group/team as an interpersonal perception-action system can be seen as a new entity with new abilities – a social synergy (Marsh, Richardson, Baron, & Schmidt, 2006). The emergence of this social synergy rests in three perceptual premises: i) players perceive affordances for themselves; ii) players perceive affordances of others; and iii) players perceive affordances for others (Fajen, et al., 2009; Marsh & Meagher, 2016; Silva, Garganta, Araújo, Davids, & Aguiar, 2013). So, new affordances become available to individuals operating as a team (shared affordances) (Marsh & Meagher, 2016; Silva, et al., 2013). Skilled interaction at the group/team level rests in the way shared practices and shared task goals develop the team as a perception-action system (i.e. a social synergy), sensitive to such shared affordances, given the team’s abilities and the current situation.
Importantly, a synergy is a task-specific organization of elements such that the degrees of freedom (DoF) of each component are coupled, enabling the DoF to regulate each other (Araújo, et al., 2016; Bernstein, 1967). In other words, the players in a group coordinate their actions in an inter-related manner; they form a higher-order control system by the adaptive fit of the players to each other and to the system as a whole (Araújo & Davids, 2016; Turvey & Fonseca, 2014). In this social synergy the players’ coordination is not predicated on a cooperation of individual structural components, but rather on the cooperation of their functional roles. Synergies are not pre-arranged but emerge from a set of constraints, they are context-dependent. So in a match, players can form and dissolve social synergies with respect to the ever changing demands of their performance environment towards a team goal. Research has already shown that team behavior can be captured as a social synergy (see Silva et al., 2016).
system is adaptable since one synergetic structure may perform many functions (Mason, 2010; Seifert, et al., 2016). In our view Adaptive flexibility is the way to potentiate performance in team sports. The players and the teams need to exhibit flexibility in their actions. The match is a constantly-changing environment, so an adequate decision in one moment may prove inappropriate in another. Within the ecological dynamics framework, behavioral variability is seen as adaptive flexibility, and this view contrasts to that of some other perspectives that see variability as evidence of noise or random fluctuations. Contrastingly, adaptive flexibility is seen as more functional, since a robust competitive outcome can be achieved consistently by different movement patterns (Davids, Glazier, Araújo, & Bartlett, 2003), and the same perception-action system is able to undertake diverse functions. Contributions in the literature, especially related to physical education intervention have shown that a pedagogical approach advocating exploration and behavioral variability relates to performance enhancement (Lee, Chow, Komar, Tan, & Button, 2014). As for team sports performance, Chow et al. (2009) reported on a skill intervention program implemented in water polo to develop adaptive movement behavior (shooting ability and decision making in attack) of elite athletes (bronze-medalist team in the 2008 Olympic Games). Results of such program included valuable development of players’ shooting and decision making behavior, and the understanding that players that better adapted to high variability/uncertainty were those more able to exploit any instabilities created. More importantly, these athletes were instrumental in the success of the decision making process at critical periods within the games. This type of analysis in team sports can, and should, also be taken to the collective level – social synergy, by looking at the system’s (group/team) adaptive flexibility.
the notion of how the team (social synergy) adjusts to its elements (the players) and to external perturbations and vice-versa. The way players engage with their surroundings locally is bounded by the group/team behavior and at the same time remodels those boundaries with respect to other relevant constraints in a given task.
2.4 Communalities and particularities in team sports
Team sports, despite the huge variety of sources of constraints (organismic, environmental, and task) (Newell, 1986; Newell & Jordan, 2007), share the need for highly coordinated actions (Araújo, et al., 2017) to reach task goals. Constraints are defined as boundaries that limit action possibilities of the system in a given task (Kugler, Kelso, & Turvey, 1980). The organismic constraints are those that reside within the boundaries of an individual movement system (player), and the environmental constraints are physical boundary conditions that are external to the player (Newell, 1986; Newell & Jordan, 2007). Here we focus on task constraints.
successful performance in a given team sport. We suggest that the definition of FR-tasks is paramount to adequately engage in performance analysis in team sports, since interpreting systems’ dynamics is highly influenced by the initial conditions of the system, as well as the interacting components that define the system.
As exemplified in Figure 2.1, performance can be analyzed at local (a, band c) and group levels (d, e and right hand-side of the figure) (Araújo, et al., 2017). The way a team organizes itself shapes the landscape of affordances (Bruineberg & Rietveld, 2014), broadening or limiting locally the opportunities for the players’ actions. The collective expands or constrains the action possibilities of the players locally, and how they act on their field of affordances reshapes continuously their action possibilities. Therefore, both teams’ actions globally shape the match landscape of affordances which in turn change the players’ local affordances, in a cyclical process (see for example in basketball, Bourbousson, Deschamps, & Travassos, 2014; Bourbousson, Seve, & McGarry, 2010a, 2010b).
Figure 2.1 Example of play dynamics in team sports. Throughout a match, tasks can be defined at the individual/dyadic level of behavioral analysis – (a) reaching/steering to the goal, (b) interacting (collaboration/opposition) with nearby agents, and (c) intercepting/avoiding the ball/opponents; and at the group level (social synergy) – (d) collaborating with teammates to reach the target, or avoid opponets to do so, (e) collaborating with teammates to intercept the ball, and (in the right side of the figure) team-team interaction. The actions within these tasks are also constrained organismically (e.g., players action capabilities) and environmentally (e.g., target position or court boundaries), and by relevant events(e.g., last play of the set) and time. Also the collective level increases or limits the action possibilities locally, and the players, by engaging with their surroundings (acting on affordances) given their task goals, shape the behavior of the collective, throughout the match.
key-implications: determining the initial state of the system and the final condition of the FR-task.
The match dynamics are specific to each sport, due to the particularities of the rules of the game, where, wining is determined by one team scoring more (points/sets, goals, baskets) than the other team. For example, in volleyball, the fact that every rally played results in a point scored by one of the two teams suggests that the rally is potentially a FR-task; it is relevant to comprehend howand whythe “game system” shifts to one side or the other of the net, according to the team that won the point. But in time-dependent games, like American football, basketball or hockey, the play is continuous throughout each period of the game. Merritt and Clauset (2014) found that for such time-dependent sports, scoring events are largely memoryless, i.e. the timing of scoring events early in the game has little or no impact on the timing of future scoring events. Thus, performance analysis in these sports can focus on shorter time-frames than the period when defining FR-tasks. For example in handball the dynamics of each play can be affected by the different throws to (re)start the game (the initial conditions of the system): free-throw, goalkeeper throw, the throw-off, the throw-in and the seven-meter throw (EHF, 2008). Or in football literature the match play (players/teams interaction) can be sub-divided into different types of team ball-possession: elaborate attack, counterattack, and set-play attack (Tenga, Holme, Ronglan, & Bahr, 2010). For instance, it is possible to move from a comparison between counterattacks and elaborate attacks of a team with respect to different defenses (Tenga, et al., 2010). We can analyze the dynamics of the play, locally (attacker-defender) and collectively (attacking-defending teams), in the different types of ball-possession and understand how the dynamics unfolded and why, for instances, counterattacks are more effective than elaborate attacks when playing against an imbalanced defense (Tenga, et al., 2010).
The coordinated behavior was captured at the ecological scale, depending on the task, by: distance to the target (Vilar, et al., 2014); interpersonal distance measures (Travassos, et al., 2012; Vilar, et al., 2014); teams geometrical centers (Bourbousson, et al., 2014); or angles between players (Travassos, Araújo, Esteves, et al., 2010).
We have discussed how ecological dynamics helps unveil what are the potentially relevant sources of constraint for individual and team behavior, which is highly task-dependent. Davids (2016) has stated that research in performance analysis in the future should integrate theoretical knowledge, empirical data and research methodology, as well as experiential knowledge from pedagogical practice and application. Previous research in team sports performance analysis, as well as experiential knowledge from pedagogical practice and application (expert-coaches interviews, coaching-manuals, etc.) can help in defining what might be FR-tasks within the match, and how to represent them in experiments. For example, Carvalho et al. (2013) focused on the notion of positional advantage in baseline rallies in tennis, a notion sustained by tennis coaching literature. They used expert coaches’ insight to select baseline rallies in tennis, (i.e., task definition). These rallies (FR-tasks) were further studied and a model was developed, that explained the emergent behavior of the player-player system, within an ecological dynamics framework.
Next we illustrate how previous performance analysis research can be useful for future performance analysis research guided by the ecological dynamics framework. It was an unfeasible task to address all team sports, so we focused only on volleyball, a team sport that is not invasive bout which examples can be found (see Vilar, et al., 2012).
2.5 The volleyball example: a systematic review
observational, which lead us to use the STROBE Statement checklist (Von Elm et al., 2008) as a baseline in the elaboration of the synthesis of the results (Appendix A, Online Resource 1). In the quality assessment of the studies included in our sample, we followed the recommendations of Sanderson, Tatt, and Higgins (2007) and selected the Health Evidence Bulletin (HEB) checklist (National Public Health Service for Wales, 2004) from the ones listed in the article.
We explored the sample of articles with respect to the types of task considered, the sources of constraint mentioned and the behavioral variables used to convey performance. A synthesis table that reports for each of the studies, the task(s), the sources of constraint and the behavioral variable(s) is available as an online resource (Appendix B, Online Resource 2).
Figure 2.2Flow diagram of the methodology used for the search and selection of articles.
We found 67 articles that covered 40 years of performance analysis in volleyball (1974-2013). We found evidence of data-driven research (nine of the 67 articles) that used databases of competitions (e.g., García-Hermoso, Dávila-Romero, & Saavedra, 2013; Marcelino, Mesquita, Palao, & Sampaio, 2009), or international federations (e.g., Bozhkova, 2013; Rodriguez-Ruiz et al., 2011).
2005) the task was the entire competitive event (World Championship and Olympic Games, e.g Yiannis & Panagiotis, 2005).
The particular organization of play in volleyball influenced the tasks chosen in the analyzed studies. In volleyball the play is not continuous throughout the match. The rally starts with a serving action by one of the teams and counts for a point. The rally was selected as the task seven times in our sample of articles. When one of the teams reaches 25 points (or 15 for the final set), this team wins one of the three sets it needs to win the match. So the set was also a frequently selected task in this sample of articles (N = 12). Game-action sequencing is very consistent in volleyball defining two offensive organizations based on the ball net-crossing – complex I, and complex II. The complex I refers to the offensive organization that unfolds to respond to the opponents serve (serve-reception, set, and attack), and the complex II refers to the offensive organization to an opposing team attack (serve, block/defense, set, and counterattack). These two tasks were the most frequent after the match (complex I: N = 14; complex II: N = 15). More vestigial was the selection of particular game actions as tasks – serve(Quiroga et al., 2012), serve-reception, attack, blockand defense(Bozhkova, 2013), and also the team configuration on-court in terms of offensive and defensive play (Jäger, Perl, & Schöllhorn, 2007). The consideration of a periodof 15 points in the beginning and in the end of the match was also found in the present article-sample (Marcelino, Sampaio, & Mesquita, 2012).
The analysis of the present sample of articles resulted in a total of 143 mentions of constraints. A synthesis-table was organized per organismic, environmental and task-related sources of constraint (see Table 2.1). Organismic constraints were task-related to sex (e.g., João, Leite, Mesquita, & Sampaio, 2010), level of expertise (e.g., Patsiaouras, Moustakidis, Charitonidis, & Kokaridas, 2010), general and volleyball-specific motor skills (Marey, Boleach, Mayhew, & McDole, 1991), in a total of 15 sources of constraint (10.5%). The environmental constraints mentioned related to the match (N = 8; 5.59%), specifically its location, status and period.
team-level of analysis, there were studies that analyzed how the players’ on-court positions related to the team offense and defense (Jäger, et al., 2007; Jäger & Schöllhorn, 2012). Other task constraints considered were related to the sequential-aspect of the game actions and how a previous/subsequent game-action was a constraint on the performance (e.g., Marcelino, Mesquita, & Sampaio, 2011). Also, 22 per cent of the articles in the present sample (N = 15 articles) did not attend to any sources of constraint in their reported performance analysis.
Table 2.1Sources of constraint mentioned in the article-sample
Type of constraint
N %
Organismic Action capabilities Sex 6 4.2%
Expertise 6 4.2%
General 2 1.4%
Volleyball-specific 1 0.7%
Environmental Match Location 3 2.1%
Period 1 0.7%
Status 4 2.8%
Set number 2 1.4%
Quality of opposition For serve 1 0.7%
For attack 1 0.7%
Task Scoring system 2 1.4%
Rotation All six rotations 3 2.1%
For receivers 1 0.7%
For setter 3 2.1%
Ball possession 2 1.4%
Players on-court positions Offense 1 0.7%
Defense 2 1.4%
Play-phase KI 8 5.59%
KII 10 6.99%
For attack 5 3.5%
Serve-reception For setting 1 0.7%
Zone 2 1.4%
Setting Zone 2 1.4%
Attack For serve-reception 2 1.4%
Tempo 13 9.09
Zone 8 5.59
Nattackers available 2 1.4%
Middle attacker availability 2 1.4%
Block For attackers 3 2.1%
Collaboration 3 2.1%
N 4 2.8%
Strategy & tactics 7 4.9%
Zone 1 0.7%
Middle blocker position/movement For setting 1 0.7%
Defense For attacking 4 2.8%
For setting 1 0.7%
Zone 1 0.7%
Player role For serve 2 1.4%
For serve-reception 2 1.4%
For defense 1 0.7%
Collaborative behavior For serve-reception 1 0.7%
For defense 1 0.7%
Not attended to 15 10.49%
Table 2.2Illustration of the behavioral variables mentioned in the article-sample.
Behavioral variables N %
Individual Serve Efficacy 33 14.8%
Mode 11 4.93%
Depth 2 0.9%
Direction 2 0.9%
Serve-reception Efficacy 24 10.76%
Mode 3 1.35%
Set Efficacy 12 5.38%
Mode 3 1.35%
Time 1 0.45%
Direction 1 0.45%
Attack Efficacy 46 20.63%
Mode 8 3.59%
Zone 6 2.69%
Tempo 3 1.35%
Direction 3 1.35%
Block Tactics 1 0.45%
Defense Mode 2 0.9%
Free-ball passing Efficacy 1 0.45%
Errors 4 1.79%
Collective Attack coverage Efficacy 1 0.45%
Block Efficacy 24 10.76%
N 2 0.9%
Cohesiveness 1 0.45%
Defense Efficacy 19 8.52%
Team Efficacy 1 0.45%
Collaboration 2 0.9%
Pattern (on-court positions) 3 1.35%
Match outcome 2 0.9%
Not attended to 2 0.9%
TOTAL 223 100%
2.5.1 Theoretically grounding future performance analysis for Volleyball
In our article sample 72.2 per cent of the behavioral variables entries related to game actions efficacy. Portraying behavior by how effective it is, in our view bounds the research to a narrow description of the performance, not explaining the how, and why it came to be effective. The ecological dynamics framework can be helpful in taking the next step into explanation.
different initial conditions for the system, the opponent serve (complex I) or attack (complex II), influences the unfolding of the organizations of the offense in each game complex.
With respect to the ecological scale two aspects should be highlighted. First, conceiving behavior as emergent at the ecological scale implies that the different sources of constraint – individual, environmental, and task, should be considered in behavioral variables aiming at conveying the performance. Grounded in the ecological dynamics framework, we consider there is behavioral dependence, so in future research we should focus on interpersonal interactions, i.e. the exploration of the relations, instead of focusing on the system components separately or in the actions cumulatively (e.g., frequencies) (see Davids, 2016). The article-sample already highlights the association between sequential game actions, but mostly with respect to their efficacies (e.g., serve-reception efficacy on attack efficacy, Patsiaouras, Moustakidis, Charitonidis, & Kokaridas, 2011) or to their ability to constrain the performance (e.g., block constraint on attack efficacy, Marcelino, et al., 2011). Second, it is important to highlight that the task-goal definition is critical to understanding the unfolding of performance. For example, in volleyball it is easy to identify the system states “having possession of the ball” from “not having possession of the ball”, based on which side of the net the ball is. But to what concerns defense and offense, drawing the line can be challenging if not impossible, or actually undesirable. An attack in difficult conditions can be aimed at maintain ball possession (hitting the ball against the block to recover it through attack-coverage). Also, the defense/serve-reception constrains setting and consequentially the attacking action, not only collectively but also individually. There are dual-task demands to the players, i.e., in most cases who receives/defends also attacks in a volleyball team. We can hypothesize, based on Wagman, Caputo, and Stoffregen (2016), that the players behave not just on the basis of immediate task demands (e.g., receiving/defending) but also on the basis of the next task to be performed (e.g., attacking). So we can conceive of first-order planning – shaping the behavior according to immediate task demands (i.e. receiving/defending), but also of second-order planning, i.e. altering the behavior not just on the basis of immediate task demands but also on the basis of the next task to be performed (receiving/defending in order to attack).
organizes in order to meet the tasks demands. At another, we could see how players adjust to each other and to other sources of constraint in order to keep their action-needs within their action boundaries. A hint on this assessment in the article-sample was the example of the middle-attacker’s availability constraint on block cohesiveness (Afonso & Mesquita, 2011). Having to perceptually deal with multiple affordances (multiple possible attackers to block) might influence the blockers ability to act together in the blocking action (i.e. more or less cohesive block). Future work can look into ecological variables that portray how the interaction (e.g., between blockers and attackers) unfolds throughout the task. They can express how the teams adapt to each other, what frailties are portrayed/explored at the different levels of analysis (individual-environment, individual-individual-environment, team-team) giving stronger insight into whyone team outperforms the other.
developments can focus, performance-wise, on the adapted and adaptable characteristics of the perception-action system we have highlighted before.
Finally, we highlight as potentially relevant sources of constraint to attend to in the definition of behavioral variables to convey the performance: i) the court, since it is the “target” the teams attack/defend; ii) the ball since in this no-invasion sport, it is the way the teams physically interact; iii) the net, as the obstacle to be transposed and avoided; and iv) the players themselves – positions and movements, with respect to each other and/or to the court, given their competitive (opponents) and collaborative (teammates) relations.
2.6 Final considerations
The relevance of the role of performance analysis research to team sports performance has been for long accepted. Here we have highlighted the way the ecological dynamics framework conceptualizes the emergence of behavior in team sports at the ecological scale by the interaction of different sources of constraint. This understanding allows the conception of the perception-action system at the collective level – as a social synergy. We have clarified how the ecological dynamics defined relevant sources of constraint and how behavior can be understand performance-wise by the intertwined view of local and collective levels of analysis. We have highlighted the high task-dependency of the performance and subsequent need to base the analysis in theoretically grounded notions of goal-directed behavior. But the high task-dependency demands the analysis to include each sport’s particularities.
We considered that previous research on performance analysis could be a good starting point to conceive of potential FR-tasks in team sports. Consequentially, this analysis would allow the identification of potentially relevant sources of constraint to attend to in performance analysis. These can be used in the definition of variables capturing the performance in future team sports ecological-dynamics-guided performance analysis research. Exemplarily we performed a systematic review on volleyball performance analysis, and discussed how it can feed future research on that sport, within an ecological dynamics framework.
2.7 Compliance with Ethical Standards
