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Expectations and Voting in the NCAA Football Polls

Author

Listed:
  • Rodney J. Paul

    (St. Bonaventure University)

  • Andrew P. Weinbach

    (Coastal Carolina University)

  • Patrick Coate

    (University of Dayton)

Abstract

A week-to-week voting model for college football using voting points from the ESPN/USA Today and Associated Press polls is specified. The point spread differential, the score differential of the most recent game minus the point spread, is shown to have a positive and highly significant effect on votes in both polls. A team that covers the point spread will receive an increase in votes in both polls. A team that wins but does not cover the point spread will lose votes. This result shows the role of expectations in this market. If a team performs better than expected, it will receive more votes in the polls and possibly move up in the rankings. Television coverage is also examined, and voter reaction to team performance is found to be greater for those games that are televised, which could be due to the television exposure itself or the fact that televised coverage is a proxy for important games.

Suggested Citation

  • Rodney J. Paul & Andrew P. Weinbach & Patrick Coate, 2007. "Expectations and Voting in the NCAA Football Polls," Journal of Sports Economics, , vol. 8(4), pages 412-424, August.
  • Handle: RePEc:sae:jospec:v:8:y:2007:i:4:p:412-424
    DOI: 10.1177/1527002506287696
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    References listed on IDEAS

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    Cited by:

    1. Randall W. Bennett, 2019. "Holdover Bias in the College Football Betting Market," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 47(1), pages 103-110, March.
    2. Rodney J. Paul & Mark Wilson, 2015. "Political Correctness, Selection Bias, and the NCAA Basketball Tournament," Journal of Sports Economics, , vol. 16(2), pages 201-213, February.
    3. Rodney Paul & Andrew P. Weinbach & Eric Higger, 2013. "The “Large-Firm” Effect? Bettor Preferences And Market Prices In Ncaa Football," Journal of Prediction Markets, University of Buckingham Press, vol. 7(2), pages 29-41.
    4. Mark David Witte & McDonald Paul Mirabile, 2010. "Not So Fast, My Friend: Biases in College Football Polls," Journal of Sports Economics, , vol. 11(4), pages 443-455, August.
    5. Kotchen, Matthew J. & Potoski, Matthew, 2014. "Conflicts of interest distort public evaluations: Evidence from NCAA football coaches," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PA), pages 51-63.
    6. Stacey L. Brook & Xiaomin Gai, 2020. "How Do Outside Experts Evaluate Team Performance? An Empirical Analysis of Harris Poll Voting Behavior," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(8), pages 1590-1601, December.
    7. Trevon Logan, 2011. "Econometric tests of American college football's conventional wisdom," Applied Economics, Taylor & Francis Journals, vol. 43(20), pages 2493-2518.
    8. Trevon D. Logan, 2007. "Whoa, Nellie! Empirical Tests of College Football's Conventional Wisdom," NBER Working Papers 13596, National Bureau of Economic Research, Inc.
    9. 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.
    10. Justin M. Ross & Sarah E. Larson & Chad Wall, 2012. "Are Surveys Of Experts Unbiased? Evidence From College Football Rankings," Contemporary Economic Policy, Western Economic Association International, vol. 30(4), pages 502-522, October.
    11. B. Jay Coleman, 2017. "Team Travel Effects and the College Football Betting Market," Journal of Sports Economics, , vol. 18(4), pages 388-425, May.

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