Loading...
2 results
Search Results
Now showing 1 - 2 of 2
- Network analysis in basketball : inspecting the prominent players using centrality metricsPublication . Manuel Clemente, Filipe; M. L. Martins, Fernando; Kalamaras, Dimitris; Mendes, RuiThe 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.
- The social network analysis of Switzerland football team on FIFA World Cup 2014Publication . Manuel Clemente, Filipe; M. L. Martins, Fernando; Kalamaras, Dimitris; Oliveira, Joana; Oliveira, Patrícia; Mendes, RuiThe aim of this study was to apply the social network analysis approach to the football match analysis case. For such, it was analyzed the Switzerland national football team during the FIFA World Cup 2014 tournament. Two general network metrics (total links and network density) and two centrality metrics (degree centrality and degree prestige) were computed. Four matches from Switzerland in FIFA World Cup 2014 were analysed in this study. A total of 334 adjacency matrices corresponding to 334 units of attack were generated based on the teammates’ interactions and then converted in 4 network graphs. A total of 1129 passes were analysed. The greatest value of total links and network density was achieved in the first match (88 total links and 0.80 of density value). Degree centrality revealed that the defenders and midfielders were the players with greatest prominent values in the attacking building. Degree prestige showed that midfielders were the main targets of the team to pass the ball in the attacking process. In summary, this study showed that centrality metrics can be an important tool in match analysis to identify the style of play of football teams, revealing the most prominent tactical roles in the attacking process.