Citation

Korte F, Link D, Groll J, Lames M. Front. Psychol. 2019; 10: e1738.

Affiliation

Chair of Performance Analysis and Sports Informatics, Technical University of Munich, Munich, Germany.

Copyright

(Copyright © 2019, Frontiers Research Foundation)

DOI

10.3389/fpsyg.2019.01738

PMID

31402892

PMCID

PMC6669815

Abstract

This study identifies dominant and intermediary players in football [soccer] by applying a play-by-play social network analysis (SNA) on 70 professional matches from the 1. and 2. German Bundesliga during the 2017/2018 season. SNA provides a quantification of the complex interaction patterns between players in team sports. So far, the individual contributions and roles of players in football have only been studied at match-level considering the overall passing of a team. In order to consider the real structure of football, a play-by-play network analysis is needed that reflects actual interplay. Moreover, a distinction between plays of certain characteristics is important to qualify different interaction phases. As it is often impossible to calculate well known network metrics such as betweenness on play-level, new adequate metrics are required. Therefore, flow betweenness is introduced as a new playmaker indicator on play-level and computed alongside flow centrality. The data on passing and the position of players was provided by the Deutsche Fußball Liga (DFL) and gathered through a semi-automatic multiple-camera tracking system. Central defenders are identified as dominant and intermediary players, however, mostly in unsuccessful plays. Offensive midfielders are most involved and defensive midfielders are the main intermediary players in successful plays. Forward are frequently involved in successful plays but show negligible playmaker status. Play-by-play network analysis facilitates a better understanding of the role of players in football interaction.

Language: en

Keywords

flow centrality; football; intermediary player; performance analysis; temporal networks