Performance analysis tool for network analysis on team sports: a case study of FIFA Soccer World Cup 2014

Detalhes bibliográficos
Autor(a) principal: Manuel Clemente, Filipe
Data de Publicação: 2016
Outros Autores: G. M. Silva, Frutuoso, M. L. Martins, Fernando, Kalamaras, Dimitris, Mendes, Rui
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.26/46736
Resumo: The study of teammates’ interaction on team sports has been growing in the last few years. Nevertheless, no specific software has been developed so far to do this in a user-friendly manner. Therefore, the aim of this study was to introduce a software called the Performance Analysis Tool that allows the user to quickly record the teammates’ interaction and automatically generate the outputs in adjacency matrices that can then be imported by social network analysis software such as SocNetV. Moreover, it was also the aim of this study to process the data in a real-life scenario, thus the seven matches of the German national soccer team in the FIFA World Cup 2014 were used to test the software and then compute the network metrics. A dataset of 3032 passes between teammates in seven soccer matches was generated with the Performance Analysis Tool software, which permitted a study of the network structure. The analysis of variance of centrality metrics between different tactical positions was made. The two-way multivariate analysis of variance revealed that the strategic position (γ=1.305 ; F = 24.394; p = 0.001; η2p=0.652 ; large effect size) had significant main effects on the centrality measures. No statistical differences were found in the phase of competition (γ=0.003 ; F = 0.097; p = 0.907; η2p=0.003 ; very small effect size). The network approach revealed that the German national soccer team based their attacking process on positional attacks and not in counter-attack, and the midfielders were the prominent players followed by the central defenders. The Performance Analysis Tool software allowed the user to quickly identify the teammates’ interactions and extract the network data for process and analysis.
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spelling Performance analysis tool for network analysis on team sports: a case study of FIFA Soccer World Cup 2014Match analysissoftwaregraphical applicationgraphical user interfaceGerman national teamThe study of teammates’ interaction on team sports has been growing in the last few years. Nevertheless, no specific software has been developed so far to do this in a user-friendly manner. Therefore, the aim of this study was to introduce a software called the Performance Analysis Tool that allows the user to quickly record the teammates’ interaction and automatically generate the outputs in adjacency matrices that can then be imported by social network analysis software such as SocNetV. Moreover, it was also the aim of this study to process the data in a real-life scenario, thus the seven matches of the German national soccer team in the FIFA World Cup 2014 were used to test the software and then compute the network metrics. A dataset of 3032 passes between teammates in seven soccer matches was generated with the Performance Analysis Tool software, which permitted a study of the network structure. The analysis of variance of centrality metrics between different tactical positions was made. The two-way multivariate analysis of variance revealed that the strategic position (γ=1.305 ; F = 24.394; p = 0.001; η2p=0.652 ; large effect size) had significant main effects on the centrality measures. No statistical differences were found in the phase of competition (γ=0.003 ; F = 0.097; p = 0.907; η2p=0.003 ; very small effect size). The network approach revealed that the German national soccer team based their attacking process on positional attacks and not in counter-attack, and the midfielders were the prominent players followed by the central defenders. The Performance Analysis Tool software allowed the user to quickly identify the teammates’ interactions and extract the network data for process and analysis.IMechERepositório ComumManuel Clemente, FilipeG. M. Silva, FrutuosoM. L. Martins, FernandoKalamaras, DimitrisMendes, Rui2023-09-25T11:48:25Z20162016-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.26/46736enghttps://doi.org/10.1177/1754337115597335info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-09-28T02:17:00Zoai:comum.rcaap.pt:10400.26/46736Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:31:34.198740Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Performance analysis tool for network analysis on team sports: a case study of FIFA Soccer World Cup 2014
title Performance analysis tool for network analysis on team sports: a case study of FIFA Soccer World Cup 2014
spellingShingle Performance analysis tool for network analysis on team sports: a case study of FIFA Soccer World Cup 2014
Manuel Clemente, Filipe
Match analysis
software
graphical application
graphical user interface
German national team
title_short Performance analysis tool for network analysis on team sports: a case study of FIFA Soccer World Cup 2014
title_full Performance analysis tool for network analysis on team sports: a case study of FIFA Soccer World Cup 2014
title_fullStr Performance analysis tool for network analysis on team sports: a case study of FIFA Soccer World Cup 2014
title_full_unstemmed Performance analysis tool for network analysis on team sports: a case study of FIFA Soccer World Cup 2014
title_sort Performance analysis tool for network analysis on team sports: a case study of FIFA Soccer World Cup 2014
author Manuel Clemente, Filipe
author_facet Manuel Clemente, Filipe
G. M. Silva, Frutuoso
M. L. Martins, Fernando
Kalamaras, Dimitris
Mendes, Rui
author_role author
author2 G. M. Silva, Frutuoso
M. L. Martins, Fernando
Kalamaras, Dimitris
Mendes, Rui
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Repositório Comum
dc.contributor.author.fl_str_mv Manuel Clemente, Filipe
G. M. Silva, Frutuoso
M. L. Martins, Fernando
Kalamaras, Dimitris
Mendes, Rui
dc.subject.por.fl_str_mv Match analysis
software
graphical application
graphical user interface
German national team
topic Match analysis
software
graphical application
graphical user interface
German national team
description The study of teammates’ interaction on team sports has been growing in the last few years. Nevertheless, no specific software has been developed so far to do this in a user-friendly manner. Therefore, the aim of this study was to introduce a software called the Performance Analysis Tool that allows the user to quickly record the teammates’ interaction and automatically generate the outputs in adjacency matrices that can then be imported by social network analysis software such as SocNetV. Moreover, it was also the aim of this study to process the data in a real-life scenario, thus the seven matches of the German national soccer team in the FIFA World Cup 2014 were used to test the software and then compute the network metrics. A dataset of 3032 passes between teammates in seven soccer matches was generated with the Performance Analysis Tool software, which permitted a study of the network structure. The analysis of variance of centrality metrics between different tactical positions was made. The two-way multivariate analysis of variance revealed that the strategic position (γ=1.305 ; F = 24.394; p = 0.001; η2p=0.652 ; large effect size) had significant main effects on the centrality measures. No statistical differences were found in the phase of competition (γ=0.003 ; F = 0.097; p = 0.907; η2p=0.003 ; very small effect size). The network approach revealed that the German national soccer team based their attacking process on positional attacks and not in counter-attack, and the midfielders were the prominent players followed by the central defenders. The Performance Analysis Tool software allowed the user to quickly identify the teammates’ interactions and extract the network data for process and analysis.
publishDate 2016
dc.date.none.fl_str_mv 2016
2016-01-01T00:00:00Z
2023-09-25T11:48:25Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.26/46736
url http://hdl.handle.net/10400.26/46736
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://doi.org/10.1177/1754337115597335
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dc.publisher.none.fl_str_mv IMechE
publisher.none.fl_str_mv IMechE
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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