A logistic regression/Markov chain model for NCAA basketball

A Logistic Regression / Markov Chain Model For NCAA Basketball

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 (LRMC) model for predicting the outcome of NCAA tournament games ...

Exploring Chance in NCAA Basketball

There seems to be an upper limit to predicting the outcome of matches in (semi-)professional sports. Recent work has proposed that this is due to chance and attempts have been made to simulate the distribution of win percentages to identify the most likely proportion of matches decided by chance. We argue that the approach that has been chosen so far makes some simplifying assumptions that caus...

Predicting Outcomes of NCAA Basketball Tournament Games

Seed distributions for the NCAA men’s basketball tournament

Bracketology, the art of successfully picking all the winners in the National Collegiate Athletic Association’s (NCAA) annual men’s Division I college basketball championship tournament, has become a favorite national activity. In spite of the challenges and uncertainty faced in this endeavor, patterns exist in how the seeds appear in each round, particularly the later rounds. This paper statis...

Predicting the Outcomes of NCAA Basketball Championship Games