IDEAS home Printed from https://ideas.repec.org/a/bpj/jqsprt/v4y2008i3n2.html
   My bibliography  Save this article

Reweighting the Bowl Championship Series

Author

Listed:
  • Buchman Susan

    (Carnegie Mellon University)

  • Kadane Joseph B.

    (Carnegie Mellon University)

Abstract

The majority of statistical work on college football's Bowl Championship Series (BCS) has involved proposing or categorizing computer ratings of teams. Computer algorithms, a coaches' poll, and a media poll make up the three ratings systems that are currently equally weighted to produce an overall BCS rating, which ultimately determines which schools will compete in lucrative post-season BCS bowls. We focus on investigating the performance of the BCS as implemented for the 2004, 2005, and 2006 seasons to determine whether equal weights are appropriate. Our Bayesian analysis shows that while the posterior mode places more than half the weight on the media poll, the 95% HPD credible interval contains the equally-weighted scheme. We relate our work to the ongoing controversies over the BCS.

Suggested Citation

  • Buchman Susan & Kadane Joseph B., 2008. "Reweighting the Bowl Championship Series," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 4(3), pages 1-13, July.
    • Handle: RePEc:bpj:jqsprt:v:4:y:2008:i:3:n:2
    DOI: 10.2202/1559-0410.1123
    as

    Download full text from publisher

    File URL: https://doi.org/10.2202/1559-0410.1123
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.2202/1559-0410.1123?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. B. Jay Coleman, 2005. "Minimizing Game Score Violations in College Football Rankings," Interfaces, INFORMS, vol. 35(6), pages 483-496, December.
    2. Stern H S, 2006. "In Favor of A Quantitative Boycott of the Bowl Championship Series," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 2(1), pages 1-6, January.
    3. 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.
    4. Stern, Hal S., 2004. "Statistics and the College Football Championship," The American Statistician, American Statistical Association, vol. 58, pages 179-185, August.
    5. Joseph Martinich, 2002. "College Football Rankings: Do the Computers Know Best?," Interfaces, INFORMS, vol. 32(5), pages 85-94, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. B. Jay Coleman, 2014. "Minimum violations and predictive meta‐rankings for college football," Naval Research Logistics (NRL), John Wiley & Sons, vol. 61(1), pages 17-33, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. 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.
    3. B. Jay Coleman, 2014. "Minimum violations and predictive meta‐rankings for college football," Naval Research Logistics (NRL), John Wiley & Sons, vol. 61(1), pages 17-33, February.
    4. Sebastián Cea & Guillermo Durán & Mario Guajardo & Denis Sauré & Joaquín Siebert & Gonzalo Zamorano, 2020. "An analytics approach to the FIFA ranking procedure and the World Cup final draw," Annals of Operations Research, Springer, vol. 286(1), pages 119-146, March.
    5. B. Jay Coleman & Andres Gallo & Paul M. Mason & Jeffrey W. Steagall, 2010. "Voter Bias in the Associated Press College Football Poll," Journal of Sports Economics, , vol. 11(4), pages 397-417, August.
    6. Annis David H. & Craig Bruce A., 2005. "Hybrid Paired Comparison Analysis, with Applications to the Ranking of College Football Teams," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 1(1), pages 1-33, October.
    7. C. Richard Cassady & Lisa M. Maillart & Sinan Salman, 2005. "Ranking Sports Teams: A Customizable Quadratic Assignment Approach," Interfaces, INFORMS, vol. 35(6), pages 497-510, December.
    8. Lenten, Liam J.A., 2011. "The extent to which unbalanced schedules cause distortions in sports league tables," Economic Modelling, Elsevier, vol. 28(1), pages 451-458.
    9. Miles William W & Fowks Gary T & Coulter Lisa O, 2010. "AccuV College Football Ranking Model," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 6(3), pages 1-17, July.
    10. Clive B Beggs & Alexander J Bond & Stacey Emmonds & Ben Jones, 2019. "Hidden dynamics of soccer leagues: The predictive ‘power’ of partial standings," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-28, December.
    11. Csató, László, 2013. "Rangsorolás páros összehasonlításokkal. Kiegészítések a felvételizői preferencia-sorrendek módszertanához [Paired comparisons ranking. A supplement to the methodology of application-based preferenc," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(12), pages 1333-1353.
    12. B. Jay Coleman, 2005. "Minimizing Game Score Violations in College Football Rankings," Interfaces, INFORMS, vol. 35(6), pages 483-496, December.
    13. Koopmeiners Joseph S., 2012. "A Comparison of the Autocorrelation and Variance of NFL Team Strengths Over Time using a Bayesian State-Space Model," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 8(3), pages 1-19, October.
    14. G Kendall, 2008. "Scheduling English football fixtures over holiday periods," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(6), pages 743-755, June.
    15. Kovalchik, Stephanie, 2020. "Extension of the Elo rating system to margin of victory," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1329-1341.
    16. Shai Bernstein & Eyal Winter, 2012. "Contracting with Heterogeneous Externalities," American Economic Journal: Microeconomics, American Economic Association, vol. 4(2), pages 50-76, May.
    17. Burer Samuel, 2012. "Robust Rankings for College Football," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 8(2), pages 1-22, June.
    18. Jarrod Olson & Daniel F. Stone, 2014. "Suspense-Optimal College Football Play-Offs," Journal of Sports Economics, , vol. 15(5), pages 519-540, October.
    19. N. Winchester & R. T. Stefani, 2013. "An innovative approach to National Football League standings using bonus points," Applied Economics, Taylor & Francis Journals, vol. 45(1), pages 123-134, January.
    20. Beaudoin, David & Swartz, Tim, 2018. "A computationally intensive ranking system for paired comparison data," Operations Research Perspectives, Elsevier, vol. 5(C), pages 105-112.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bpj:jqsprt:v:4:y:2008:i:3:n:2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.