The Application of Machine Learning Techniques for Predicting Results in Team Sport: A Review Rory Bunker a,* , Teo Susnjak b a Nagoya Institute of Technology. Gokisocho, Showa Ward, Nagoya, Aichi, 466-8555, Japan b Massey University. Massey University East Precinct, Dairy Flat Highway (SH17), 0632, New Zealand Abstract Over the past two decades, Machine Learning (ML) techniques have been increasingly utilized for the purpose of predicting outcomes in sport. In this paper, we provide a review of studies that have used ML for predicting results in team sport, covering studies from 1996 to 2019. We sought to answer five key research questions while extensively surveying papers in this field. This paper offers insights into which ML algorithms have tended to be used in this field, as well as those that are beginning to emerge with successful out- comes. Our research highlights defining characteristics of successful studies and identifies robust strategies for evaluating accuracy results in this applica- tion domain. Our study considers accuracies that have been achieved across different sports and explores the notion that outcomes of some team sports could be inherently more difficult to predict than others. Finally, our study uncovers common themes of future research directions across all surveyed pa- pers, looking for gaps and opportunities, while proposing recommendations for future researchers in this domain. Keywords: Machine Learning, Sport Result Prediction, Literature Review, Expert System, Team Sport * Corresponding author Email addresses: rorybunker@gmail.com (Rory Bunker), t.susnjak@massey.ac.nz (Teo Susnjak) Preprint submitted to arXiv December 30, 2019 arXiv:1912.11762v1 [cs.LG] 26 Dec 2019