A New Iterative Method for Ranking College Football Teams
Wigness Maggie B,
Williams Chadd C and
Rowell Michael J
Additional contact information
Wigness Maggie B: Pacific University
Williams Chadd C: Pacific University
Rowell Michael J: Pacific University
Journal of Quantitative Analysis in Sports, 2010, vol. 6, issue 2, 15
Abstract:
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.
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://doi.org/10.2202/1559-0410.1242 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bpj:jqsprt:v:6:y:2010:i:2:n:7
Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/jqas/html
DOI: 10.2202/1559-0410.1242
Access Statistics for this article
Journal of Quantitative Analysis in Sports is currently edited by Mark Glickman
More articles in Journal of Quantitative Analysis in Sports from De Gruyter
Bibliographic data for series maintained by Peter Golla ().