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The Sensitivity of College Football Rankings to Several Modeling Choices
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Andrew T. Karl
Published/Copyright:
October 9, 2012
Abstract
This paper proposes a multiple-membership generalized linear mixed model for ranking college football teams using only their win/loss records. The model results in an intractable, high-dimensional integral due to the random effects structure and nonlinear link function. We use recent data sets to explore the effect of the choice of integral approximation and other modeling assumptions on the rankings. Varying the modeling assumptions sometimes leads to changes in the team rankings that could affect bowl assignments.
Keywords: BCS; EM algorithm; fully exponential Laplace approximation; generalized linear mixed model; multiple membership
Published Online: 2012-10-9
©2012 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
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Keywords for this article
BCS;
EM algorithm;
fully exponential Laplace approximation;
generalized linear mixed model;
multiple membership
Articles in the same Issue
- Article
- Models for Third Down Conversion in the National Football League
- A Comparison of the Autocorrelation and Variance of NFL Team Strengths Over Time using a Bayesian State-Space Model
- The Sensitivity of College Football Rankings to Several Modeling Choices
- The Individual Factors of Successful Free Throw Shooting
- New Insights on the Tendency of NCAA Basketball Officials to Even Out Foul Calls
- Was There a Structural Break in Barry Bonds's Bat?
- Estimating Fielding Ability in Baseball Players Over Time
- Adjusted Plus-Minus for NHL Players using Ridge Regression with Goals, Shots, Fenwick, and Corsi
- An Analysis of Curling Strategy
