Manuel Clemente, FilipeM. L. Martins, FernandoKalamaras, DimitrisMendes, Rui2023-09-222023-09-222015http://hdl.handle.net/10400.26/46710The 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.engcollective behaviourmatch analysisnetworkmetricstechnical performancebasketballNetwork analysis in basketball : inspecting the prominent players using centrality metricsjournal article