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Hypernetworks Reveal Compound Variables That Capture Cooperative and Competitive Interactions in a Soccer Match

The combination of sports sciences theorization and social networks analysis (SNA) has offered useful new insights for addressing team behavior. However, SNA typically represents the dynamics of team behavior during a match in dyadic interactions and in a single cumulative snapshot. This study aims...

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Autores principales: Ramos, João, Lopes, Rui J., Marques, Pedro, Araújo, Duarte
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5581353/
https://www.ncbi.nlm.nih.gov/pubmed/28894427
http://dx.doi.org/10.3389/fpsyg.2017.01379
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author Ramos, João
Lopes, Rui J.
Marques, Pedro
Araújo, Duarte
author_facet Ramos, João
Lopes, Rui J.
Marques, Pedro
Araújo, Duarte
author_sort Ramos, João
collection PubMed
description The combination of sports sciences theorization and social networks analysis (SNA) has offered useful new insights for addressing team behavior. However, SNA typically represents the dynamics of team behavior during a match in dyadic interactions and in a single cumulative snapshot. This study aims to overcome these limitations by using hypernetworks to describe illustrative cases of team behavior dynamics at various other levels of analyses. Hypernetworks simultaneously access cooperative and competitive interactions between teammates and opponents across space and time during a match. Moreover, hypernetworks are not limited to dyadic relations, which are typically represented by edges in other types of networks. In a hypernetwork, n-ary relations (with n > 2) and their properties are represented with hyperedges connecting more than two players simultaneously (the so-called simplex—plural, simplices). Simplices can capture the interactions of sets of players that may include an arbitrary number of teammates and opponents. In this qualitative study, we first used the mathematical formalisms of hypernetworks to represent a multilevel team behavior dynamics, including micro (interactions between players), meso (dynamics of a given critical event, e.g., an attack interaction), and macro (interactions between sets of players) levels. Second, we investigated different features that could potentially explain the occurrence of critical events, such as, aggregation or disaggregation of simplices relative to goal proximity. Finally, we applied hypernetworks analysis to soccer games from the English premier league (season 2010–2011) by using two-dimensional player displacement coordinates obtained with a multiple-camera match analysis system provided by STATS (formerly Prozone). Our results show that (i) at micro level the most frequently occurring simplices configuration is 1vs.1 (one attacker vs. one defender); (ii) at meso level, the dynamics of simplices transformations near the goal depends on significant changes in the players' speed and direction; (iii) at macro level, simplices are connected to one another, forming “simplices of simplices” including the goalkeeper and the goal. These results validate qualitatively that hypernetworks and related compound variables can capture and be used in the analysis of the cooperative and competitive interactions between players and sets of players in soccer matches.
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spelling pubmed-55813532017-09-11 Hypernetworks Reveal Compound Variables That Capture Cooperative and Competitive Interactions in a Soccer Match Ramos, João Lopes, Rui J. Marques, Pedro Araújo, Duarte Front Psychol Psychology The combination of sports sciences theorization and social networks analysis (SNA) has offered useful new insights for addressing team behavior. However, SNA typically represents the dynamics of team behavior during a match in dyadic interactions and in a single cumulative snapshot. This study aims to overcome these limitations by using hypernetworks to describe illustrative cases of team behavior dynamics at various other levels of analyses. Hypernetworks simultaneously access cooperative and competitive interactions between teammates and opponents across space and time during a match. Moreover, hypernetworks are not limited to dyadic relations, which are typically represented by edges in other types of networks. In a hypernetwork, n-ary relations (with n > 2) and their properties are represented with hyperedges connecting more than two players simultaneously (the so-called simplex—plural, simplices). Simplices can capture the interactions of sets of players that may include an arbitrary number of teammates and opponents. In this qualitative study, we first used the mathematical formalisms of hypernetworks to represent a multilevel team behavior dynamics, including micro (interactions between players), meso (dynamics of a given critical event, e.g., an attack interaction), and macro (interactions between sets of players) levels. Second, we investigated different features that could potentially explain the occurrence of critical events, such as, aggregation or disaggregation of simplices relative to goal proximity. Finally, we applied hypernetworks analysis to soccer games from the English premier league (season 2010–2011) by using two-dimensional player displacement coordinates obtained with a multiple-camera match analysis system provided by STATS (formerly Prozone). Our results show that (i) at micro level the most frequently occurring simplices configuration is 1vs.1 (one attacker vs. one defender); (ii) at meso level, the dynamics of simplices transformations near the goal depends on significant changes in the players' speed and direction; (iii) at macro level, simplices are connected to one another, forming “simplices of simplices” including the goalkeeper and the goal. These results validate qualitatively that hypernetworks and related compound variables can capture and be used in the analysis of the cooperative and competitive interactions between players and sets of players in soccer matches. Frontiers Media S.A. 2017-08-28 /pmc/articles/PMC5581353/ /pubmed/28894427 http://dx.doi.org/10.3389/fpsyg.2017.01379 Text en Copyright © 2017 Ramos, Lopes, Marques and Araújo. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Ramos, João
Lopes, Rui J.
Marques, Pedro
Araújo, Duarte
Hypernetworks Reveal Compound Variables That Capture Cooperative and Competitive Interactions in a Soccer Match
title Hypernetworks Reveal Compound Variables That Capture Cooperative and Competitive Interactions in a Soccer Match
title_full Hypernetworks Reveal Compound Variables That Capture Cooperative and Competitive Interactions in a Soccer Match
title_fullStr Hypernetworks Reveal Compound Variables That Capture Cooperative and Competitive Interactions in a Soccer Match
title_full_unstemmed Hypernetworks Reveal Compound Variables That Capture Cooperative and Competitive Interactions in a Soccer Match
title_short Hypernetworks Reveal Compound Variables That Capture Cooperative and Competitive Interactions in a Soccer Match
title_sort hypernetworks reveal compound variables that capture cooperative and competitive interactions in a soccer match
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5581353/
https://www.ncbi.nlm.nih.gov/pubmed/28894427
http://dx.doi.org/10.3389/fpsyg.2017.01379
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