Performance analysis tool for network analysis on team sports: a case study of FIFA Soccer World Cup 2014
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , , |
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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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 |
status_str |
publishedVersion |
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 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
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 |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
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 |
repository.mail.fl_str_mv |
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1799133583325003776 |