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NCAA Tournament Games: The Real Nitty-Gritty

Author

Listed:
  • Coleman Jay

    (University of North Florida)

  • Lynch Allen K

    (Mercer University)

Abstract

The NCAA Division I Men's Basketball Committee annually selects its national championship tournament's at-large invitees, and assigns seeds to all participants. As part of its deliberations, the Committee is provided a so-called "nitty-gritty report" for each team, containing numerous team performance statistics. Many elements of this report receive a great deal of attention by the media and fans as the tournament nears, including a team's Ratings Percentage Index (or RPI), overall record, conference record, non-conference record, strength of schedule, record in its last 10 games, etc. However, few previous studies have evaluated the degree to which these factors are related to whether a team actually wins games once the tournament begins. Using nitty-gritty information for the participants in the 638 tournament games during the 10 seasons from 1999 through 2008, we use stepwise binary logit regression to build a model that includes only eight of the 32 nitty-gritty factors we examined. We find that in some cases factors that receive a great deal of attention are not related to game results, at least in the presence of the more highly related set of factors included in the model.

Suggested Citation

  • Coleman Jay & Lynch Allen K, 2009. "NCAA Tournament Games: The Real Nitty-Gritty," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 5(3), pages 1-27, July.
    • Handle: RePEc:bpj:jqsprt:v:5:y:2009:i:3:n:8
    DOI: 10.2202/1559-0410.1165
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    References listed on IDEAS

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    1. West Brady T., 2008. "A Simple and Flexible Rating Method for Predicting Success in the NCAA Basketball Tournament: Updated Results from 2007," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 4(2), pages 1-18, April.
    2. Boulier, Bryan L. & Stekler, H. O., 1999. "Are sports seedings good predictors?: an evaluation," International Journal of Forecasting, Elsevier, vol. 15(1), pages 83-91, February.
    3. Harville D.A., 2003. "The Selection or Seeding of College Basketball or Football Teams for Postseason Competition," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 17-27, January.
    4. West Brady T, 2006. "A Simple and Flexible Rating Method for Predicting Success in the NCAA Basketball Tournament," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 2(3), pages 1-16, July.
    5. Caudill, Steven B., 2003. "Predicting discrete outcomes with the maximum score estimator: the case of the NCAA men's basketball tournament," International Journal of Forecasting, Elsevier, vol. 19(2), pages 313-317.
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    Cited by:

    1. Morris Tracy L. & Bokhari Faryal H., 2012. "The Dreaded Middle Seeds - Are They the Worst Seeds in the NCAA Basketball Tournament?," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 8(2), pages 1-13, June.
    2. Grimshaw Scott D. & Sabin R. Paul & Willes Keith M., 2013. "Analysis of the NCAA Men’s Final Four TV audience," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 9(2), pages 115-126, June.

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