IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/13596.html
   My bibliography  Save this paper

Whoa, Nellie! Empirical Tests of College Football's Conventional Wisdom

Author

Listed:
  • Trevon D. Logan

Abstract

College football fans, coaches, and observers have adopted a set of beliefs about how college football poll voters behave. I document three pieces of conventional wisdom in college football regarding the timing of wins and losses, the value of playing strong opponents, and the value of winning by wide margins. Using a unique data set with 25 years of AP poll results, I test college football's conventional wisdom. In particular, I test (1) whether it is better to lose early or late in the season, (2) whether teams benefit from playing stronger opponents, and (3) whether teams are rewarded for winning by large margins. Contrary to conventional wisdom, I find that (1) it is better to lose later in the season than earlier, (2) AP voters do not pay attention to the strength of a defeated opponent, and (3) the benefit of winning by a large margin is negligible. I conclude by noting how these results inform debates about a potential playoff in college football.

Suggested Citation

  • Trevon D. Logan, 2007. "Whoa, Nellie! Empirical Tests of College Football's Conventional Wisdom," NBER Working Papers 13596, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:13596
    Note: DAE
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w13596.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. James Buchanan & Yong Yoon, 2006. "All voting is strategic," Public Choice, Springer, vol. 129(1), pages 159-167, October.
    2. George Loewenstein & Ted O'Donoghue & Matthew Rabin, 2003. "Projection Bias in Predicting Future Utility," The Quarterly Journal of Economics, Oxford University Press, vol. 118(4), pages 1209-1248.
    3. Noel D. Campbell & Tammy M. Rogers & R. Zachary Finney, 2007. "Evidence of Television Exposure Effects in AP Top 25 College Football Rankings," Journal of Sports Economics, , vol. 8(4), pages 425-434, August.
    4. Guillaume R. Fréchette & Alvin E. Roth & M. Utku Ünver, 2007. "Unraveling yields inefficient matchings: evidence from post-season college football bowls," RAND Journal of Economics, RAND Corporation, vol. 38(4), pages 967-982, December.
    5. Matthew Rabin, 2002. "Inference by Believers in the Law of Small Numbers," The Quarterly Journal of Economics, Oxford University Press, vol. 117(3), pages 775-816.
    6. Ray C. Fair & John F. Oster, 2002. "College Football Rankings and Market Efficiency," Cowles Foundation Discussion Papers 1381, Cowles Foundation for Research in Economics, Yale University, revised Mar 2005.
    7. Ray Fair & John Oster, 2002. "College Football Rankings and Market Efficiency," Yale School of Management Working Papers amz2377, Yale School of Management, revised 01 Aug 2007.
    8. George Langelett, 2003. "The Relationship between Recruiting and Team Performance in Division 1A College Football," Journal of Sports Economics, , vol. 4(3), pages 240-245, August.
    9. Ray C. Fair & John F. Oster, 2007. "College Football Rankings and Market Efficiency," Journal of Sports Economics, , vol. 8(1), pages 3-18, February.
    10. Matthew Rabin & Joel L. Schrag, 1999. "First Impressions Matter: A Model of Confirmatory Bias," The Quarterly Journal of Economics, Oxford University Press, vol. 114(1), pages 37-82.
    11. Lebovic, James H. & Sigelman, Lee, 2001. "The forecasting accuracy and determinants of football rankings," International Journal of Forecasting, Elsevier, vol. 17(1), pages 105-120.
    Full references (including those not matched with items on IDEAS)

    More about this item

    JEL classification:

    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • D7 - Microeconomics - - Analysis of Collective Decision-Making

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:nbr:nberwo:13596. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (). General contact details of provider: http://edirc.repec.org/data/nberrus.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.