Player skill estimation for soccer match prediction. (26th December 2019) - Lopez, Juan Pablo Maldonado; Jindra, Vojtěch
In this paper we propose two algorithms for assessing skill of soccer players. We introduce an adaptation of the Elo rating algorithm, which is widely used in chess, to handle teams. A different approach is proposed to assess player skill as a function of the proportion of matches won. Since it is hard to measure skill directly, to estimate the performance of our approach we propose as a proxy the number of correctly predicted match outcomes of a classifier that takes as input our algorithms' output. Numerical experiments suggest that our approach is competitive with book-keeper's estimates, even though we rely only on historical game outcome data.