Graph theory and social network analysis applied to the study of young basketball players: Variance of centrality levels
Sport Science Vol. 9, Nº 3, pp. 1 - 10, September, 2016.
ISSN (print): 1840-3662
ISSN (online): 1840-3670
Journal Impact Factor: 1,550 (in 2014)
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Graph theory and social network analysis have been used in match analysis to identify some properties of the team. In this study, our aim was to characterize the centrality levels of young basketball players and analyse the differences between positions of the court. Thirty-two young basketball players (11.56 ± 0.68 years old; 2.97 ± 0.35 years of practice) participated in this study. The one-way ANOVA tested the variance between positions for the %ODC, %IDC and %BC variables. Statistical differences were found in %ODC (p = 0.001; ES = 0.63; minimum effect), %BC (p = 0.001; ES = 0.81; minimum effect) and %IDC (p = 0.001; ES = 0.52; minimum effect). Results suggest that guards are the positions with greater participation and more relevant centralities on the game.
Keywords: applied mathematics; graph theory; network analysis; centrality measures; match analysis; basketball.