Predicting the Outcomes of NCAA Basketball Championship Games
This paper uses the difference in seeding ranks to predict the outcome of March Madness games. It updates the Boulier-Stekler method by predicting the outcomes by rounds. We also use the consensus rankings obtained from individuals, systems and poll. We conclude that the consensus rankings were slightly better predictors in the early rounds but had the same limitations as the seedings in the later rounds.
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Volume (Year): 8 (2012)
Issue (Month): 1 (March)
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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Edward H. Kaplan & Stanley J. Garstka, 2001. "March Madness and the Office Pool," Management Science, INFORMS, vol. 47(3), pages 369-382, March.
- 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.
- Metrick, Andrew, 1996. "March madness? Strategic behavior in NCAA basketball tournament betting pools," Journal of Economic Behavior & Organization, Elsevier, vol. 30(2), pages 159-172, August.
- 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.
- 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.
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