JSM 2004 - Toronto

Abstract #301333

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Activity Number: 410
Type: Contributed
Date/Time: Thursday, August 12, 2004 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics in Sports
Abstract - #301333
Title: Probability Models for 64-Team NCAA Tournaments
Author(s): Scott Stewart*+ and Christopher R. Bilder
Companies: University of Arkansas for Medical Sciences and University of Nebraska, Lincoln
Address: , , ,
Keywords: logistic regression ; NCAA tournament ; Sagarin
Abstract:

The Division I men's NCAA basketball tournament has been studied and analyzed extensively in recent years. There are several other tournaments in college athletics that warrant investigation. Probability models are built here as a function of team strength information, such as team seeds. Four different tournaments are used to build models: men's basketball, women's basketball, women's volleyball, and men's baseball. The fit and assumptions of the models suggest that the logistic regression model is preferred over other types of models. Findings suggest that there is more competitive balance, or parity, in some tournaments than others. In the women's volleyball tournament, the best teams advance further than the best teams in the other tournaments. In men's basketball, models based on Sagarin ratings are useful predictor models and findings suggest that they may be better than models based on seed strength information. Interestingly, and in contrast to what many have assumed true, there is an insignificant change over time across all four tournaments studied.

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