Expert System for Ice Hockey Game Prediction: Data Mining with Human Judgment

Wei Gu
Donlinks School of Economics and Management
University of Science and Technology Beijing
Thomas Saaty
Joseph M. Katz Graduate School of Business
University of Pittsburgh
United States
Rozann Whitaker
Creative Decisions Foundation
United States

Publication date: Jul, 2016

Journal: International Journal of Information Technology & Decision Making
Vol.: 15- Issue: 4- Pages: 763-789

Abstract: This paper describes an expert system to predict National Hockey League (NHL) game outcome. A new method based on both data and judgments is used to estimate the hockey game performance. There are many facts and judgments that could influence an outcome. We employed the support vector machine to determine the importance of these factors before we incorporate them into the prediction system. Our system combines data and judgments and used them to predict the win–lose outcome of all the 89 post-season games before they took place. The accuracy of our prediction with the combined factors was 77.5%. This is to date the best accuracy reported of hockey games prediction.

Keywords: Prediction, Expert system, Hockey game, Judgments