Explaining soccer match outcomes with goal scoring opportunities predictive analytics - Eggels, H.; van Elk, R.; Pechenizkiy, M. (Machine Learning and Data Mining for Sports Analytics ECML/PKDD 2016 workshop, 2016)
In elite soccer, decisions are often based on recent results and emotions. In this paper, we propose a method to determine the expected winner of a match in elite soccer. The expected result of a soccer match is determined by estimating the probability of scoring for the individual goal scoring opportunities. The outcome of a match is then obtained by integrating these probabilities. In our experimental study, we show that the probabilities of goal scoring opportunities accurately match reality