How team sports behave as a team? : general network metrics applied to sports analysis

Detalhes bibliográficos
Autor(a) principal: Manuel Clemente, Filipe
Data de Publicação: 2015
Outros Autores: 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/10400.26/46713
Resumo: The aim of this study was to analyse the general properties of networks in different team sports. Therefore, the analysis of variance to the general network properties between different team sports and different competitive levels was carried out. Sixty-six official matches (from Handball, Basketball, Football, Futsal, Rink-Hockey and Volleyball) were observed in five possible competitive levels (U12, U14, U16, U18 and Amateurs with more than 20 years). Analysis of variance revealed that the type of sport (p = 0.001; ��=0.647; moderate effect size) and competitive level(p = 0.001; �� = 0.355; small effect size)had significant statistical differences in the general network metrics. It was also found that football generates more connections between teammates but basketball and volleyball promote better results of density and clustering coefficient.
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spelling How team sports behave as a team? : general network metrics applied to sports analysisGraph TheoryAdjacency MatricesNetwork AnalysisPerformanceTeam SportsThe aim of this study was to analyse the general properties of networks in different team sports. Therefore, the analysis of variance to the general network properties between different team sports and different competitive levels was carried out. Sixty-six official matches (from Handball, Basketball, Football, Futsal, Rink-Hockey and Volleyball) were observed in five possible competitive levels (U12, U14, U16, U18 and Amateurs with more than 20 years). Analysis of variance revealed that the type of sport (p = 0.001; ��=0.647; moderate effect size) and competitive level(p = 0.001; �� = 0.355; small effect size)had significant statistical differences in the general network metrics. It was also found that football generates more connections between teammates but basketball and volleyball promote better results of density and clustering coefficient.[Routledge]Repositório ComumManuel Clemente, FilipeM. L. Martins, FernandoMendes, Rui2023-09-22T14:34:05Z20152015-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.26/46713enginfo: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:RCAAP2023-09-28T02:16:49Zoai:comum.rcaap.pt:10400.26/46713Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:31:33.290352Repositório 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 How team sports behave as a team? : general network metrics applied to sports analysis
title How team sports behave as a team? : general network metrics applied to sports analysis
spellingShingle How team sports behave as a team? : general network metrics applied to sports analysis
Manuel Clemente, Filipe
Graph Theory
Adjacency Matrices
Network Analysis
Performance
Team Sports
title_short How team sports behave as a team? : general network metrics applied to sports analysis
title_full How team sports behave as a team? : general network metrics applied to sports analysis
title_fullStr How team sports behave as a team? : general network metrics applied to sports analysis
title_full_unstemmed How team sports behave as a team? : general network metrics applied to sports analysis
title_sort How team sports behave as a team? : general network metrics applied to sports analysis
author Manuel Clemente, Filipe
author_facet Manuel Clemente, Filipe
M. L. Martins, Fernando
Mendes, Rui
author_role author
author2 M. L. Martins, Fernando
Mendes, Rui
author2_role author
author
dc.contributor.none.fl_str_mv Repositório Comum
dc.contributor.author.fl_str_mv Manuel Clemente, Filipe
M. L. Martins, Fernando
Mendes, Rui
dc.subject.por.fl_str_mv Graph Theory
Adjacency Matrices
Network Analysis
Performance
Team Sports
topic Graph Theory
Adjacency Matrices
Network Analysis
Performance
Team Sports
description The aim of this study was to analyse the general properties of networks in different team sports. Therefore, the analysis of variance to the general network properties between different team sports and different competitive levels was carried out. Sixty-six official matches (from Handball, Basketball, Football, Futsal, Rink-Hockey and Volleyball) were observed in five possible competitive levels (U12, U14, U16, U18 and Amateurs with more than 20 years). Analysis of variance revealed that the type of sport (p = 0.001; ��=0.647; moderate effect size) and competitive level(p = 0.001; �� = 0.355; small effect size)had significant statistical differences in the general network metrics. It was also found that football generates more connections between teammates but basketball and volleyball promote better results of density and clustering coefficient.
publishDate 2015
dc.date.none.fl_str_mv 2015
2015-01-01T00:00:00Z
2023-09-22T14:34:05Z
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/10400.26/46713
url http://hdl.handle.net/10400.26/46713
dc.language.iso.fl_str_mv eng
language eng
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 [Routledge]
publisher.none.fl_str_mv [Routledge]
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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