The social network analysis of Switzerland football team on FIFA World Cup 2014
Autor(a) principal: | |
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Data de Publicação: | 2015 |
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/10400.26/46749 |
Resumo: | The aim of this study was to apply the social network analysis approach to the football match analysis case. For such, it was analyzed the Switzerland national football team during the FIFA World Cup 2014 tournament. Two general network metrics (total links and network density) and two centrality metrics (degree centrality and degree prestige) were computed. Four matches from Switzerland in FIFA World Cup 2014 were analysed in this study. A total of 334 adjacency matrices corresponding to 334 units of attack were generated based on the teammates’ interactions and then converted in 4 network graphs. A total of 1129 passes were analysed. The greatest value of total links and network density was achieved in the first match (88 total links and 0.80 of density value). Degree centrality revealed that the defenders and midfielders were the players with greatest prominent values in the attacking building. Degree prestige showed that midfielders were the main targets of the team to pass the ball in the attacking process. In summary, this study showed that centrality metrics can be an important tool in match analysis to identify the style of play of football teams, revealing the most prominent tactical roles in the attacking process. |
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The social network analysis of Switzerland football team on FIFA World Cup 2014match analysisfootballnetworkcooperationperformanceThe aim of this study was to apply the social network analysis approach to the football match analysis case. For such, it was analyzed the Switzerland national football team during the FIFA World Cup 2014 tournament. Two general network metrics (total links and network density) and two centrality metrics (degree centrality and degree prestige) were computed. Four matches from Switzerland in FIFA World Cup 2014 were analysed in this study. A total of 334 adjacency matrices corresponding to 334 units of attack were generated based on the teammates’ interactions and then converted in 4 network graphs. A total of 1129 passes were analysed. The greatest value of total links and network density was achieved in the first match (88 total links and 0.80 of density value). Degree centrality revealed that the defenders and midfielders were the players with greatest prominent values in the attacking building. Degree prestige showed that midfielders were the main targets of the team to pass the ball in the attacking process. In summary, this study showed that centrality metrics can be an important tool in match analysis to identify the style of play of football teams, revealing the most prominent tactical roles in the attacking process.[Editura Universitatea din Pitesti]Repositório ComumManuel Clemente, FilipeM. L. Martins, FernandoKalamaras, DimitrisOliveira, JoanaOliveira, PatríciaMendes, Rui2023-09-26T10:35:42Z20152015-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.26/46749eng10.7752/jpes.2015.01022info: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:RCAAP2023-09-28T02:17:04Zoai:comum.rcaap.pt:10400.26/46749Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:31:34.703015Repositório 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 |
The social network analysis of Switzerland football team on FIFA World Cup 2014 |
title |
The social network analysis of Switzerland football team on FIFA World Cup 2014 |
spellingShingle |
The social network analysis of Switzerland football team on FIFA World Cup 2014 Manuel Clemente, Filipe match analysis football network cooperation performance |
title_short |
The social network analysis of Switzerland football team on FIFA World Cup 2014 |
title_full |
The social network analysis of Switzerland football team on FIFA World Cup 2014 |
title_fullStr |
The social network analysis of Switzerland football team on FIFA World Cup 2014 |
title_full_unstemmed |
The social network analysis of Switzerland football team on FIFA World Cup 2014 |
title_sort |
The social network analysis of Switzerland football team on FIFA World Cup 2014 |
author |
Manuel Clemente, Filipe |
author_facet |
Manuel Clemente, Filipe M. L. Martins, Fernando Kalamaras, Dimitris Oliveira, Joana Oliveira, Patrícia Mendes, Rui |
author_role |
author |
author2 |
M. L. Martins, Fernando Kalamaras, Dimitris Oliveira, Joana Oliveira, Patrícia Mendes, Rui |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
Repositório Comum |
dc.contributor.author.fl_str_mv |
Manuel Clemente, Filipe M. L. Martins, Fernando Kalamaras, Dimitris Oliveira, Joana Oliveira, Patrícia Mendes, Rui |
dc.subject.por.fl_str_mv |
match analysis football network cooperation performance |
topic |
match analysis football network cooperation performance |
description |
The aim of this study was to apply the social network analysis approach to the football match analysis case. For such, it was analyzed the Switzerland national football team during the FIFA World Cup 2014 tournament. Two general network metrics (total links and network density) and two centrality metrics (degree centrality and degree prestige) were computed. Four matches from Switzerland in FIFA World Cup 2014 were analysed in this study. A total of 334 adjacency matrices corresponding to 334 units of attack were generated based on the teammates’ interactions and then converted in 4 network graphs. A total of 1129 passes were analysed. The greatest value of total links and network density was achieved in the first match (88 total links and 0.80 of density value). Degree centrality revealed that the defenders and midfielders were the players with greatest prominent values in the attacking building. Degree prestige showed that midfielders were the main targets of the team to pass the ball in the attacking process. In summary, this study showed that centrality metrics can be an important tool in match analysis to identify the style of play of football teams, revealing the most prominent tactical roles in the attacking process. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015 2015-01-01T00:00:00Z 2023-09-26T10:35:42Z |
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/10400.26/46749 |
url |
http://hdl.handle.net/10400.26/46749 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.7752/jpes.2015.01022 |
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 |
[Editura Universitatea din Pitesti] |
publisher.none.fl_str_mv |
[Editura Universitatea din Pitesti] |
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 |
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RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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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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1799133584005529600 |