Using ELO ratings for match result prediction in association football

Sports betting markets are becoming increasingly competitive. These markets are of interest when testing new ideas for quantitative prediction models. This paper examines the value of assigning ratings to teams based on their past performance in order to predict match results in association football. The ELO rating system is used to derive covariates that are then used in ordered logit regression models. In order to make informed statements about the relative merit of the ELO-based predictions compared to those from a set of six benchmark prediction methods, both economic and statistical measures are used. The results of large-scale computational experiments are presented.