IDEAS home Printed from https://ideas.repec.org/a/bpj/jqsprt/v8y2012i1n3.html
   My bibliography  Save this article

Predicting the Outcomes of NCAA Basketball Championship Games

Author

Listed:
  • Stekler Herman O.

    (George Washington University)

  • Klein Andrew

    (George Washington University)

Abstract

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.

Suggested Citation

  • Stekler Herman O. & Klein Andrew, 2012. "Predicting the Outcomes of NCAA Basketball Championship Games," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 8(1), pages 1-10, March.
  • Handle: RePEc:bpj:jqsprt:v:8:y:2012:i:1:n:3
    DOI: 10.1515/1559-0410.1373
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/1559-0410.1373
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.

    File URL: https://libkey.io/10.1515/1559-0410.1373?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 look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Bryan Clair & David Letscher, 2007. "Optimal Strategies for Sports Betting Pools," Operations Research, INFORMS, vol. 55(6), pages 1163-1177, December.
    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. Edward H. Kaplan & Stanley J. Garstka, 2001. "March Madness and the Office Pool," Management Science, INFORMS, vol. 47(3), pages 369-382, March.
    4. 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.
    5. 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.
    6. 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.
    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. David Bergman & Jason Imbrogno, 2017. "Surviving a National Football League Survivor Pool," Operations Research, INFORMS, vol. 65(5), pages 1343-1354, October.
    2. Manner Hans, 2016. "Modeling and forecasting the outcomes of NBA basketball games," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 12(1), pages 31-41, March.

    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. Bryan Clair & David Letscher, 2007. "Optimal Strategies for Sports Betting Pools," Operations Research, INFORMS, vol. 55(6), pages 1163-1177, December.
    2. Paul Kvam & Joel S. Sokol, 2006. "A logistic regression/Markov chain model for NCAA basketball," Naval Research Logistics (NRL), John Wiley & Sons, vol. 53(8), pages 788-803, December.
    3. Stekler, H.O. & Sendor, David & Verlander, Richard, 2010. "Issues in sports forecasting," International Journal of Forecasting, Elsevier, vol. 26(3), pages 606-621, July.
      • Herman O. Stekler & David Sendor & Richard Verlander, 2009. "Issues in Sports Forecasting," Working Papers 2009-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    4. Nicholas G. Hall & Chris N. Potts, 2012. "A Proposal for Redesign of the FedEx Cup Playoff Series on the PGA TOUR," Interfaces, INFORMS, vol. 42(2), pages 166-179, April.
    5. David Bergman & Jason Imbrogno, 2017. "Surviving a National Football League Survivor Pool," Operations Research, INFORMS, vol. 65(5), pages 1343-1354, October.
    6. 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.
    7. B. Jay Coleman & J. Michael DuMond & Allen K. Lynch, 2010. "Evidence of bias in NCAA tournament selection and seeding," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 31(7), pages 431-452.
    8. Ludden Ian G. & Khatibi Arash & King Douglas M. & Jacobson Sheldon H., 2020. "Models for generating NCAA men’s basketball tournament bracket pools," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 16(1), pages 1-15, March.
    9. David Bergman & Carlos Cardonha & Jason Imbrogno & Leonardo Lozano, 2023. "Optimizing the Expected Maximum of Two Linear Functions Defined on a Multivariate Gaussian Distribution," INFORMS Journal on Computing, INFORMS, vol. 35(2), pages 304-317, March.
    10. Phillip E. Pfeifer, 2016. "The promise of pick-the-winners contests for producing crowd probability forecasts," Theory and Decision, Springer, vol. 81(2), pages 255-278, August.
    11. del Corral, Julio & Prieto-Rodríguez, Juan, 2010. "Are differences in ranks good predictors for Grand Slam tennis matches?," International Journal of Forecasting, Elsevier, vol. 26(3), pages 551-563, July.
    12. Martin B. Haugh & Raghav Singal, 2021. "How to Play Fantasy Sports Strategically (and Win)," Management Science, INFORMS, vol. 67(1), pages 72-92, January.
    13. Manner Hans, 2016. "Modeling and forecasting the outcomes of NBA basketball games," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 12(1), pages 31-41, March.
    14. Lopez Michael J. & Matthews Gregory J., 2015. "Building an NCAA men’s basketball predictive model and quantifying its success," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 11(1), pages 5-12, March.
    15. 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.
    16. Vaughan Williams, Leighton & Stekler, Herman O., 2010. "Sports forecasting," International Journal of Forecasting, Elsevier, vol. 26(3), pages 445-447, July.
      • Herman O. Stekler, 2007. "Sports Forecasting," Working Papers 2007-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting, revised Jan 2007.
    17. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.
    18. repec:ebl:ecbull:v:4:y:2007:i:34:p:1-7 is not listed on IDEAS
    19. 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.
    20. Angelini, Giovanni & Candila, Vincenzo & De Angelis, Luca, 2022. "Weighted Elo rating for tennis match predictions," European Journal of Operational Research, Elsevier, vol. 297(1), pages 120-132.
    21. Andrew J. Leach, 2003. "SubGame, set and match. Identifying Incentive Response in a Tournament," Cahiers de recherche 04-02, HEC Montréal, Institut d'économie appliquée.

    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:8:y:2012:i:1:n:3. 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.