This paper presents a novel framework for evaluating players in association football (soccer). Our method uses possession sequences, i.e. sequences of consecutive on-ball actions, for deriving estimates for player strengths. On the surface, the methodology is similar to classical adjusted plus-minus rating models using mainly regularized regression techniques. However, by analyzing possessions, our framework is able to distinguish on-ball and off-ball contributions of players to the game. From a methodological viewpoint, the framework explores four different penalization schemes, which exploit football-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.

翻译：本文提出了一种评估足球运动员的新颖框架。该方法利用控球序列（即连续的持球动作序列）来推导球员能力估计值。从表面上看，该方法与主要采用正则化回归技术的经典调整正负值评级模型相似。然而，通过分析控球过程，本框架能够区分球员在比赛中的有球贡献与无球贡献。从方法论视角，该框架探索了四种不同的惩罚方案，这些方案利用了足球特有的结构特征，例如将球员按位置分组以及按能力等级分组。这四种模型通过考虑各模型对应球员的相应估计值，形成了四种球员评级方式。我们运用这些评级分析了2017/18赛季西班牙足球甲级联赛的数据。通过比较各惩罚模型的相似性及特定应用场景，为实践者使用不同模型规范提供了指导。最后，我们构建了一个领域特定的统计评估框架作为分析总结，该框架凸显了惩罚回归方法在球员评估中的潜力。