Abstract
This study identifies dominant and intermediary players in football 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.
Highlights
Football teams are described as groups that interact in a dynamic and interdependent way to achieve their common goal (Ribeiro et al, 2017)
We focus on the different outcomes of a play, instead of only assessing successful play outcomes such as Mclean et al (2018) did or relating individual match-level metrics to match outcomes which accepts potential noise in the analysis
Flow-based metrics quantify the proportional prevalence or intermediary role of players in a match. They appear most fitting in a football context as they are robust to the short plays in football, allow a consideration of the temporal order of passing as proposed through flow betweenness and offer a suitable connection to performance outcomes on play-level
Summary
Football teams are described as groups that interact in a dynamic and interdependent way to achieve their common goal (Ribeiro et al, 2017). The intermediary role of players to connect their team mates as bridging players by distributing the ball is frequently assessed by applying betweenness and closeness measures to the overall passing interaction between players across a match (Clemente et al, 2015, 2016a; Aquino et al, 2018; Castellano and Echeazarra, 2019) Based on these existing studies that apply SNA in football, Ramos et al (2018) demand a breakdown of the analysis to a playby-play level to consider the temporal character of football. Flow-based metrics quantify the proportional prevalence or intermediary role of players in a match They appear most fitting in a football context as they are robust to the short plays in football, allow a consideration of the temporal order of passing as proposed through flow betweenness and offer a suitable connection to performance outcomes on play-level
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