Data Mining in Elite Sports: A Review and a Framework

Abstract

Sophisticated data analytical methods such as data mining, where the focus is upon exploration and developing new insights, are becoming increasingly useful tools in analysing elite sports performance data and supporting decision making that is crucial to gaining success. In this article, we investigate the different data mining demands of elite sports with respect to a number of features that describe sport competitions. The aim is to more structurally connect the sports and data mining domains through: (a) describing a framework for categorizing elite sports, and (b) understanding the analytical demands of different performance analysis problems. Therefore, we review different aspects such as sport categories and performance analysis requirements that influence each stage in sports data mining. We also present a model bringing together performance analysis requirements, data mining methods, data mining techniques, and technique characteristics. This will assist both data scientists and sport professionals to more effectively collaborate and contribute to success in elite sport events.

Keywords:

• data mining
• elite sport
• performance analysis

ACKNOWLEDGEMENTS

We thank the Institute of Sport, Exercise, and Active Living at Victoria University, Melbourne, Australia, for funding this research project. We also thank a number of sport scientists at the Victorian Institute of Sport, Australia, for their great support.