Quantifying the value of sprints in elite football using spatial cohesive networks

Emre Külah and Hande Alemdar

Chaos, Solitons & Fractals, 2020, vol. 139, issue C

Abstract: Football players are on the move during games and the sprint is one of the distinctive type of those movements. In this study, we focus on quantifying the value of the sprints using the spatial data of players and the collective movements of the teams during the game. We first propose a method to quantify the dispersion of the teams, namely, the weighted team spread. In order to find the weights of the team spread, we use individual players’ interaction behavior, using spatial cohesion matrices. Spatial features of the pitch such as the pitch value and the pass probability value are also used together with the weighted team spread to quantify the value of the sprints. These models are used to understand sprint character of the players according to their role and teams’ collective movements depending on their tactics. The proposed method applied on 306 Turkish first division games from 2018/2019. The sprint analysis results show that attackers have greater sprint averages than midfielders and defenders based on 5498 sprints from corresponding games. Full-backs and attacking midfielders are positions with the best sprint averages other than attacking players. Center backs and defensive midfielders are the weakest positions in sprinting. The results further show that the teams that are focused on having the possession of the ball have less average sprint value than teams playing counter-attack style.

Keywords: Team sport; Sprint analysis; Collective movement; Data mining; Performance analysis (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:139:y:2020:i:c:s0960077920307025

DOI: 10.1016/j.chaos.2020.110306

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