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September 05, 2008
Undergraduate statistics seminar
Welcome back everyone,
This year we're going to start an occasional series of short talks for undergraduates interested in statistics.
The first talk will be given by Brady West. Brady is a graduate of our undergraduate and masters statistics programs from about 5 years ago. He then worked in UM (at CSCAR) as a statistical consultant, co-authored a book on mixed models, and is just beginning the UM PhD program in survey research methodology.
His talk we be about statistical analysis of basketball and football tournament results.
The talk will take place on September 18th in B760 East Hall at 5:45. Please join us in 470 West Hall at 5:30 for cookies and coffee.
The title and abstract are below. I hope to see many of you there.
Kerby
Title: Some New Applications of Statistical Methods to Hot Topics in NCAA Basketball and Football Post-Season Competition
ABSTRACT
This presentation 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 presentation then proposes a simple and flexible rating method based on ordinal logistic regression and expectation (the OLRE method; West, 2006) that is designed to predict success for those teams selected to participate in the NCAA tournament. Simulations based on the parametric Bradley-Terry model for paired comparisons are used to demonstrate the ability of the computationally simple OLRE method to predict success in the tournament, using actual NCAA tournament data from 2006-2008. 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 and 2008. Current limitations and directions for future work in this area will be discussed.
The presentation then considers a review of previous quantitative literature dedicated to the development of ratings for college and professional football teams, and also considers various methods that have been proposed for predicting the outcomes of future football games. Building on this literature, the presentation then discusses a straightforward application of linear modeling in the development of a predictive model for the outcomes of college football bowl games (West and Lamsal, 2008), and identifies important team-level predictors of actual bowl outcomes in 2007-2008 using real Football Bowl Subdivision (FBS) data from the recently completed 2004-2006 college football seasons. Given that Bowl Championship Series (BCS) ratings are still being used to determine the teams most eligible to play for a national championship and a playoff system for determining a national champion is not yet a reality, the predictive model is then applied in a novel method for the calculation of ratings for selected teams, based on a round-robin playoff scenario. The presentation also considers additional possible applications of the proposed methods, and concludes with current limitations and directions for future work in this area.
Posted by kshedden at September 5, 2008 02:38 PM