Characterizing different team sports using network analysis

  • Florian Korte Center for Digital Technology and Management, Munich
  • Martin Lames Department of Sport and Health Sciences, Technical University of Munich
Keywords: social network analysis, team sports, interaction matrices, minimum spanning trees


Team sports are complex dynamic systems based on the frequent interaction of various players. Recently, social network analysis has been introduced to the study of sports dynamics in order to quantify the involvement of individual players in the interplay and to characterize the organizational processes used by teams. Nonetheless, only a limited set of team sports has been assessed to date, and the focus of most studies has been on the application of small sets of network metrics to a single sport. Our study aims at comparing the network patterns of different team sports in order to contribute to the understanding of their underlying nature. It considers three invasion games, namely professional matches from basketball, football and handball. By applying relevant centrality measures and minimum spanning trees a first comparison between the nature of interplay in various team sports is offered as well as a deeper understanding of the role of different tactical positions in each sport. The point guard in basketball, defensive midfielder in football and center in handball are identified as the most central tactical positions. Direct interplay is most balanced in football followed by basketball and handball. A visualization of the basic structure of interplay for each sport is achieved through minimum spanning trees.

How to Cite
Korte, F., & Lames, . M. (2018). Characterizing different team sports using network analysis. Current Issues in Sport Science (CISS), 3, 005.
Movement & Exercise Science