DOI
10.1002/nav.20170
Abstract
Each year, more than $3 billion is wagered on the NCAA Division I men’s basketball tournament. Most of that money is wagered in pools where the object is to correctly predict winners of each game, with emphasis on the last four teams remaining (the Final Four). In this paper, we present a combined logistic regression/Markov chain model for predicting the outcome of NCAA tournament games given only basic input data. Over the past 6 years, our model has been significantly more successful than the other common methods such as tournament seedings, the AP and ESPN/USA Today polls, the RPI, and the Sagarin ratings.
Document Type
Post-print Article
Publication Date
2006
Publisher Statement
Copyright © 2006 Wiley Periodicals, Inc.
DOI: 10.1002/nav.20170
The definitive version is available at: https://onlinelibrary.wiley.com/doi/abs/10.1002/nav.20170
Full Citation:
Kvam, Paul H., and Joel S. Sokol. "A Logistic Regression/Markov Chain Model for NCAA Basketball." Naval Research Logistics 53, no. 8 (2006): 788-803. doi:10.1002/nav.20170.
Recommended Citation
Kvam, Paul H. and Sokol, Joel, "A Logistic Regression/Markov Chain Model for NCAA Basketball" (2006). Department of Math & Statistics Faculty Publications. 200.
https://scholarship.richmond.edu/mathcs-faculty-publications/200