A Simple and Flexible Rating Method for Predicting Success in the NCAA Basketball Tournament: Updated Results from 2007

This 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 from 2006 and 2007. Given that the proposed method can incorporate several different predictors of success in the NCAA tournament when calculating a rating, and is shown to have better predictive power than a model-based approach, it should be considered as an alternative to other rating methods currently used to assign seeds and regions to the teams selected to play in the tournament. The predictive power of the model-based simulation approach is also discussed, given the success of this approach in 2007. The paper concludes with limitations and directions for future work in this area.