![]() Irrespective of the used model, most of the relevant information is embedded in the betting markets, and adding other match- and player-specific data does not lead to any significant improvement. ![]() The paper shows that the average prediction accuracy cannot be increased to more than about 70%. On the example of tennis, this paper extends previous research by conducting one of the most extensive studies of its kind and applying a wide range of machine learning techniques to male and female professional singles matches. Several attempts have been made to apply machine learning to the prediction of the outcome of professional sports events and to exploit “inefficiencies” in the corresponding betting markets. ![]() Machine learning and its numerous variants have meanwhile become established tools in many areas of society.
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