Network analysis in basketball : inspecting the prominent players using centrality metrics

Detalhes bibliográficos
Autor(a) principal: Manuel Clemente, Filipe
Data de Publicação: 2015
Outros Autores: 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/10400.26/46710
Resumo: The aim of this study was to analyse the team-members cooperation in basketball by using centrality metrics of network. Different ages were compared in this study. Forty players (10 players of under-14; 10 players of under16; 10 players of under-18 and 10 players in amateurs with more than 20 years) voluntarily participated in this study. A total of 326 units of attack were generated based on the team-members interactions and then converted in final graphs. The one-way ANOVA for the factor tactical position found statistical differences in the dependent variables of %DCentrality (F(4,15) = 13.622; p-value = 0.001; n2 = 0.784; Large Effect Size) and %DPrestige (F(4,15) = 20.590; p-value = 0.001; n2 = 0.846; Large Effect Size). In conclusion this study showed that point guard was the prominent position during the attacking organization and that social network analysis it is a useful approach to identify the patterns of interactions in the game of basketball.
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spelling Network analysis in basketball : inspecting the prominent players using centrality metricscollective behaviourmatch analysisnetworkmetricstechnical performancebasketballThe aim of this study was to analyse the team-members cooperation in basketball by using centrality metrics of network. Different ages were compared in this study. Forty players (10 players of under-14; 10 players of under16; 10 players of under-18 and 10 players in amateurs with more than 20 years) voluntarily participated in this study. A total of 326 units of attack were generated based on the team-members interactions and then converted in final graphs. The one-way ANOVA for the factor tactical position found statistical differences in the dependent variables of %DCentrality (F(4,15) = 13.622; p-value = 0.001; n2 = 0.784; Large Effect Size) and %DPrestige (F(4,15) = 20.590; p-value = 0.001; n2 = 0.846; Large Effect Size). In conclusion this study showed that point guard was the prominent position during the attacking organization and that social network analysis it is a useful approach to identify the patterns of interactions in the game of basketball.Editura Universitatea din PitestRepositório ComumManuel Clemente, FilipeM. L. Martins, FernandoKalamaras, DimitrisMendes, Rui2023-09-22T12:00:32Z20152015-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.26/46710enginfo: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:RCAAP2023-09-28T02:16:47Zoai:comum.rcaap.pt:10400.26/46710Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:31:33.146375Repositório 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 Network analysis in basketball : inspecting the prominent players using centrality metrics
title Network analysis in basketball : inspecting the prominent players using centrality metrics
spellingShingle Network analysis in basketball : inspecting the prominent players using centrality metrics
Manuel Clemente, Filipe
collective behaviour
match analysis
network
metrics
technical performance
basketball
title_short Network analysis in basketball : inspecting the prominent players using centrality metrics
title_full Network analysis in basketball : inspecting the prominent players using centrality metrics
title_fullStr Network analysis in basketball : inspecting the prominent players using centrality metrics
title_full_unstemmed Network analysis in basketball : inspecting the prominent players using centrality metrics
title_sort Network analysis in basketball : inspecting the prominent players using centrality metrics
author Manuel Clemente, Filipe
author_facet Manuel Clemente, Filipe
M. L. Martins, Fernando
Kalamaras, Dimitris
Mendes, Rui
author_role author
author2 M. L. Martins, Fernando
Kalamaras, Dimitris
Mendes, Rui
author2_role 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
Mendes, Rui
dc.subject.por.fl_str_mv collective behaviour
match analysis
network
metrics
technical performance
basketball
topic collective behaviour
match analysis
network
metrics
technical performance
basketball
description The aim of this study was to analyse the team-members cooperation in basketball by using centrality metrics of network. Different ages were compared in this study. Forty players (10 players of under-14; 10 players of under16; 10 players of under-18 and 10 players in amateurs with more than 20 years) voluntarily participated in this study. A total of 326 units of attack were generated based on the team-members interactions and then converted in final graphs. The one-way ANOVA for the factor tactical position found statistical differences in the dependent variables of %DCentrality (F(4,15) = 13.622; p-value = 0.001; n2 = 0.784; Large Effect Size) and %DPrestige (F(4,15) = 20.590; p-value = 0.001; n2 = 0.846; Large Effect Size). In conclusion this study showed that point guard was the prominent position during the attacking organization and that social network analysis it is a useful approach to identify the patterns of interactions in the game of basketball.
publishDate 2015
dc.date.none.fl_str_mv 2015
2015-01-01T00:00:00Z
2023-09-22T12:00:32Z
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url http://hdl.handle.net/10400.26/46710
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language eng
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dc.publisher.none.fl_str_mv Editura Universitatea din Pitest
publisher.none.fl_str_mv Editura Universitatea din Pitest
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
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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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