Smart Data Scouting in Professional Soccer: Evaluating Passing Performance Based on Position Tracking Data

Abstract

Sports analytics in general and soccer analytics, in particular, have evolved in recent years due to the increased availability of large data amounts of (tracking) data. Especially in terms of evaluating tactical behavior, data science could change the way we think about soccer. In this study, we evaluate passing performance in soccer to prove the hypothesis that tactical behavior in team sports can be analyzed based exclusively on tracking data. To prove this point, we explore the relationship between changes in spatiotemporal variables in relation to passing and key performance indicators. Based on our results that demonstrate the ability of spatiotemporal variables to predict pass accuracy and key performances indicators on an individual level, we confirmed our hypothesis. Furthermore, we calculated a simple composite performance indicator to evaluate passes and players based on tracking data. In conclusion, our results can be used as an approach for real-time evaluation of tactical behavior and as a new method to scout and evaluate players in soccer and team sports in general.