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A New Iterative Method for Ranking College Football Teams

Listed author(s):
  • Wigness Maggie B

    (Pacific University)

  • Williams Chadd C

    (Pacific University)

  • Rowell Michael J

    (Pacific University)

Registered author(s):

    This paper introduces a new iterative model for ranking college football teams. It is first presented as a general model with a number of parameters. We then introduce two learning methods that use past data to predict the optimal values of the parameters for the model. Our learning algorithms are then implemented using data from 1998-2008. We analyze the accuracy of our rankings by considering bowl game outcomes for each season. We also compare our results with the Bowl Championship Series computer ranking system. We close with a discussion of possible directions for future work.

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    File URL: https://www.degruyter.com/view/j/jqas.2010.6.2/jqas.2010.6.2.1242/jqas.2010.6.2.1242.xml?format=INT
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    Article provided by De Gruyter in its journal Journal of Quantitative Analysis in Sports.

    Volume (Year): 6 (2010)
    Issue (Month): 2 (April)
    Pages: 1-15

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    Handle: RePEc:bpj:jqsprt:v:6:y:2010:i:2:n:7
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    1. Itay Fainmesser & Chaim Fershtman & Neil Gandal, 2009. "A Consistent Weighted Ranking Scheme With an Application to NCAA College Football Rankings," Journal of Sports Economics, , vol. 10(6), pages 582-600, December.
    2. Steven Caudill, 2009. "OSU and LSU: easy to spell but did they belong? Using the method of paired comparisons to evaluate the BCS rankings and the NCAA football championship game 2007-08," Applied Economics, Taylor & Francis Journals, vol. 41(25), pages 3225-3230.
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