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

Clemente, F.M.C. ; Martins, F. ; Mendes, R.

Sport Science Vol. 8, Nº 2, pp. 81 - 87, August, 2015.

ISSN (print): 1840-3662
ISSN (online): 1840-3670

Scimago Journal Ranking: 0,42 (in 2015)

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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; η_p^2= 0.647; moderate effect size) and competitive level (p = 0.001; η_p^2= 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.

Keywords: Graph Theory; Adjacency Matrices; Network Analysis; Performance; Team Sports.