Plus-minus models for evaluating and scouting soccer players using possession sequences

Abstract Accepted by: Prof. Phil Scarf This paper presents a novel framework for evaluating association football (soccer) players using possession sequences to estimate player strengths. The methodology is similar to classical plus–minus rating models, primarily employing regularized regression techniques. By analyzing possessions, our framework distinguishes on-ball and off-ball contributions of players to the game. The framework explores four different penalization schemes, which exploit soccer-specific structures such as the grouping of players into position groups as well as into common strength groups. These four models lead to four ways to rate players by considering the respective estimate of each model corresponding to the player. The ratings are used to analyze the 2017/18 season of the Spanish La Liga. We compare similarities as well as particular use cases of each of the penalized models and provide guidance for practitioners when using the individual model specifications. Finally, we conclude our analysis by providing a domain-specific statistical evaluation framework, which highlights the potential of the penalized regression approaches for evaluating players.