Beat the Bookmaker – Winning Football Bets with Machine Learning (Best Application Paper)

Over the past decades, football (soccer) has continued to draw more and more attention from people all over the world. Meanwhile, the appearance of the internet led to a rapidly growing market for online bookmakers, companies which offer sport bets for specific odds. With numerous matches every week in dozens of countries, football league matches hold enormous potential for developing betting strategies. In this context, a betting strategy beats the bookmaker if it generates positive average profits over time. In this paper, we developed a data-driven framework for predicting the outcome of football league matches and generating meaningful profits by betting accordingly. Conducting a simulation study based on the matches of the five top European football leagues from season 2013/14 to 2017/18 showed that economically and statistically significant returns can be achieved by exploiting large data sets with modern machine learning algorithms. Furthermore, it turned out that these results cannot be reached with a linear regression model or simple betting strategies, such as always betting on the home team.