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The Sensitivity of College Football Rankings to Several Modeling Choices

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  • Karl Andrew T.

    (Arizona State University)

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.

Suggested Citation

  • Karl Andrew T., 2012. "The Sensitivity of College Football Rankings to Several Modeling Choices," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 8(3), pages 1-44, October.
    • Handle: RePEc:bpj:jqsprt:v:8:y:2012:i:3:n:3
    DOI: 10.1515/1559-0410.1471
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    References listed on IDEAS

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    1. Mease D., 2003. "A Penalized Maximum Likelihood Approach for the Ranking of College Football Teams Independent of Victory Margins," The American Statistician, American Statistical Association, vol. 57, pages 241-248, November.
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    6. West Brady T, 2006. "A Simple and Flexible Rating Method for Predicting Success in the NCAA Basketball Tournament," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 2(3), pages 1-16, July.
    7. West Brady T & Lamsal Madhur, 2008. "A New Application of Linear Modeling in the Prediction of College Football Bowl Outcomes and the Development of Team Ratings," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 4(3), pages 1-21, July.
    8. Dimitris Rizopoulos & Geert Verbeke & Emmanuel Lesaffre, 2009. "Fully exponential Laplace approximations for the joint modelling of survival and longitudinal data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(3), pages 637-654, June.
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