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

Wei Gu (), Thomas L. Saaty () and Rozann Whitaker ()
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Wei Gu: Donlinks School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, China
Thomas L. Saaty: Joseph M. Katz Graduate School of Business, University of Pittsburgh, Pittsburgh 15206, PA, USA
Rozann Whitaker: Creative Decisions Foundation, Pittsburgh 15213, PA, USA

International Journal of Information Technology & Decision Making (IJITDM), 2016, vol. 15, issue 04, 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; data analysis; judgment (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (3)

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DOI: 10.1142/S0219622016400022

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