A Simple and Flexible Rating Method for Predicting Success in the NCAA Basketball Tournament
AbstractThis paper first presents a brief review of potential rating tools and methods for predicting success in the NCAA basketball tournament, including those methods (such as the Ratings Percentage Index, or RPI) that receive a great deal of weight in selecting and seeding teams for the tournament. The paper then proposes a simple and flexible rating method based on ordinal logistic regression and expectation (the OLRE method) that is designed to predict success for those teams selected to participate in the NCAA tournament. A simulation based on the parametric Bradley-Terry model for paired comparisons is used to demonstrate the ability of the computationally simple OLRE method to predict success in the tournament, using actual NCAA tournament data. Given that the proposed method can incorporate several different predictors of success in the NCAA tournament when calculating a rating, and has better predictive power than a model-based approach, it should be strongly considered as an alternative to other rating methods currently used to assign seeds and regions to the teams selected to play in the tournament.
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Bibliographic InfoArticle provided by De Gruyter in its journal Journal of Quantitative Analysis in Sports.
Volume (Year): 2 (2006)
Issue (Month): 3 (July)
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Web page: http://www.degruyter.com
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- B. Jay Coleman & J. Michael DuMond & Allen K. Lynch, 2010. "Evidence of bias in NCAA tournament selection and seeding," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 31(7), pages 431-452.
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