Using network metrics to investigate football team players’ connections : a pilot study

Detalhes bibliográficos
Autor(a) principal: Manuel Clemente, Filipe
Data de Publicação: 2014
Outros Autores: Couceiro, Micael, M. L. Martins, Fernando, 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/10400.26/46784
Resumo: The aim of this pilot study was propose a set of network methods to measure the specific properties of football teams. These metrics were organized on “meso” and “micro” analysis levels. Five official matches of the same team on the First Portuguese Football League were analyzed. An overall of 577 offensive plays were analyzed from the five matches. From the adjacency matrices developed per each offensive play it were computed the scaled connectivity, the clustering coefficient and the centroid significance and centroid conformity. Results showed that the highest values of scaled connectivity were found in lateral defenders and central and midfielder players and the lowest values were found in the striker and goalkeeper. The highest values of clustering coefficient were generally found in midfielders and forwards. In addition, the centroid results showed that lateral and central defenders tend to be the centroid players in the attacking process. In sum, this study showed that network metrics can be a powerful tool to help coaches to understanding the specific team’s properties, thus supporting decision-making and improving sports training based on match analysis.
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spelling Using network metrics to investigate football team players’ connections : a pilot studymatch analysisfootballnetworkmetricsperformanceanálise de jogofutebolnetworkmétricasrendimentoThe aim of this pilot study was propose a set of network methods to measure the specific properties of football teams. These metrics were organized on “meso” and “micro” analysis levels. Five official matches of the same team on the First Portuguese Football League were analyzed. An overall of 577 offensive plays were analyzed from the five matches. From the adjacency matrices developed per each offensive play it were computed the scaled connectivity, the clustering coefficient and the centroid significance and centroid conformity. Results showed that the highest values of scaled connectivity were found in lateral defenders and central and midfielder players and the lowest values were found in the striker and goalkeeper. The highest values of clustering coefficient were generally found in midfielders and forwards. In addition, the centroid results showed that lateral and central defenders tend to be the centroid players in the attacking process. In sum, this study showed that network metrics can be a powerful tool to help coaches to understanding the specific team’s properties, thus supporting decision-making and improving sports training based on match analysis.UNESPRepositório ComumManuel Clemente, FilipeCouceiro, MicaelM. L. Martins, FernandoMendes, Rui2023-09-27T09:40:51Z20142014-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.26/46784engdx.doi.org/10.1590/S1980-65742014000300004info: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:RCAAP2023-09-28T02:17:17Zoai:comum.rcaap.pt:10400.26/46784Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:31:35.480676Repositório 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 Using network metrics to investigate football team players’ connections : a pilot study
title Using network metrics to investigate football team players’ connections : a pilot study
spellingShingle Using network metrics to investigate football team players’ connections : a pilot study
Manuel Clemente, Filipe
match analysis
football
network
metrics
performance
análise de jogo
futebol
network
métricas
rendimento
title_short Using network metrics to investigate football team players’ connections : a pilot study
title_full Using network metrics to investigate football team players’ connections : a pilot study
title_fullStr Using network metrics to investigate football team players’ connections : a pilot study
title_full_unstemmed Using network metrics to investigate football team players’ connections : a pilot study
title_sort Using network metrics to investigate football team players’ connections : a pilot study
author Manuel Clemente, Filipe
author_facet Manuel Clemente, Filipe
Couceiro, Micael
M. L. Martins, Fernando
Mendes, Rui
author_role author
author2 Couceiro, Micael
M. L. Martins, Fernando
Mendes, Rui
author2_role author
author
author
dc.contributor.none.fl_str_mv Repositório Comum
dc.contributor.author.fl_str_mv Manuel Clemente, Filipe
Couceiro, Micael
M. L. Martins, Fernando
Mendes, Rui
dc.subject.por.fl_str_mv match analysis
football
network
metrics
performance
análise de jogo
futebol
network
métricas
rendimento
topic match analysis
football
network
metrics
performance
análise de jogo
futebol
network
métricas
rendimento
description The aim of this pilot study was propose a set of network methods to measure the specific properties of football teams. These metrics were organized on “meso” and “micro” analysis levels. Five official matches of the same team on the First Portuguese Football League were analyzed. An overall of 577 offensive plays were analyzed from the five matches. From the adjacency matrices developed per each offensive play it were computed the scaled connectivity, the clustering coefficient and the centroid significance and centroid conformity. Results showed that the highest values of scaled connectivity were found in lateral defenders and central and midfielder players and the lowest values were found in the striker and goalkeeper. The highest values of clustering coefficient were generally found in midfielders and forwards. In addition, the centroid results showed that lateral and central defenders tend to be the centroid players in the attacking process. In sum, this study showed that network metrics can be a powerful tool to help coaches to understanding the specific team’s properties, thus supporting decision-making and improving sports training based on match analysis.
publishDate 2014
dc.date.none.fl_str_mv 2014
2014-01-01T00:00:00Z
2023-09-27T09:40:51Z
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/10400.26/46784
url http://hdl.handle.net/10400.26/46784
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv dx.doi.org/10.1590/S1980-65742014000300004
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.publisher.none.fl_str_mv UNESP
publisher.none.fl_str_mv UNESP
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
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
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