IDEAS home Printed from https://ideas.repec.org/a/eee/jomega/v50y2015icp141-148.html
   My bibliography  Save this article

Modeling the winning seed distribution of the NCAA Division I men׳s basketball tournament

Author

Listed:
  • Khatibi, Arash
  • King, Douglas M.
  • Jacobson, Sheldon H.

Abstract

The National Collegiate Athletic Association׳s (NCAA) men׳s Division I college basketball tournament is an annual competition that draws widespread attention in the United States. Predicting the winner of each game is a popular activity undertaken by numerous websites, fans, and more recently, academic researchers. This paper analyzes the 29 tournaments from 1985 to 2013, and presents two models to capture the winning seed distribution (i.e., a probability distribution modeling the winners of each round). The Exponential Model uses the exponential random variable to model the waiting time between a seed׳s successive winnings in a round. The Markov Model uses Markov chains to estimate the winning seed distributions by considering a seed׳s total number of winnings in previous tournaments. The proposed models allow one to estimate the likelihoods of different seed combinations by applying the estimated winning seed distributions, which accurately summarize aggregate performance of the seeds. Moreover, the proposed models show that the winning rate of seeds is not a monotonically decreasing function of the seed number. Results of the proposed models are validated using a chi-squared goodness of fit test and compared to the frequency of observed events.

Suggested Citation

  • Khatibi, Arash & King, Douglas M. & Jacobson, Sheldon H., 2015. "Modeling the winning seed distribution of the NCAA Division I men׳s basketball tournament," Omega, Elsevier, vol. 50(C), pages 141-148.
    • Handle: RePEc:eee:jomega:v:50:y:2015:i:c:p:141-148
    DOI: 10.1016/j.omega.2014.08.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S030504831400098X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.omega.2014.08.004?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Baumann Robert & Matheson Victor A. & Howe Cara A., 2010. "Anomalies in Tournament Design: The Madness of March Madness," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 6(2), pages 1-11, April.
    2. Shishebor, Z. & Towhidi, M., 2004. "On the generalization of negative binomial distribution," Statistics & Probability Letters, Elsevier, vol. 66(2), pages 127-133, January.
    3. Jacobson, Sheldon H. & Nikolaev, Alexander G. & King, Douglas M. & Lee, Adrian J., 2011. "Seed distributions for the NCAA men's basketball tournament," Omega, Elsevier, vol. 39(6), pages 719-724, December.
    4. Koenker, Roger & Bassett Jr., Gilbert W., 2010. "March Madness, Quantile Regression Bracketology, and the Hayek Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 26-35.
    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. Fearnhead, Paul & Taylor, Benjamin M., 2010. "Calculating Strength of Schedule, and Choosing Teams for March Madness," The American Statistician, American Statistical Association, vol. 64(2), pages 108-115.
    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. Ira Horowitz, 2018. "Competitive Balance in the NBA Playoffs," The American Economist, Sage Publications, vol. 63(2), pages 215-227, October.
    2. Karlsson, Niklas & Lunander, Anders, 2020. "Choosing Opponents in Skiing Sprint Elimination Tournaments," Working Papers 2020:6, Örebro University, School of Business, revised 01 Sep 2020.
    3. Karpov, Alexander, 2015. "A theory of knockout tournament seedings," Working Papers 0600, University of Heidelberg, Department of Economics.
    4. Ilan Adler & Yang Cao & Richard Karp & Erol A. Peköz & Sheldon M. Ross, 2017. "Random Knockout Tournaments," Operations Research, INFORMS, vol. 65(6), pages 1589-1596, December.

    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. Jacobson, Sheldon H. & Nikolaev, Alexander G. & King, Douglas M. & Lee, Adrian J., 2011. "Seed distributions for the NCAA men's basketball tournament," Omega, Elsevier, vol. 39(6), pages 719-724, December.
    2. Oliver Engist & Erik Merkus & Felix Schafmeister, 2021. "The Effect of Seeding on Tournament Outcomes: Evidence From a Regression-Discontinuity Design," Journal of Sports Economics, , vol. 22(1), pages 115-136, January.
    3. Gupta Ajay Andrew, 2015. "A new approach to bracket prediction in the NCAA Men’s Basketball Tournament based on a dual-proportion likelihood," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 11(1), pages 53-67, March.
    4. Karpov, Alexander, 2015. "A theory of knockout tournament seedings," Working Papers 0600, University of Heidelberg, Department of Economics.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Jaiho Chung & Joon Ho Hwang, 2010. "An Empirical Examination of the Parimutuel Sports Lottery Market versus the Bookmaker Market," Southern Economic Journal, John Wiley & Sons, vol. 76(4), pages 884-905, April.
    10. Vellaisamy, P. & Upadhye, N.S., 2007. "On the negative binomial distribution and its generalizations," Statistics & Probability Letters, Elsevier, vol. 77(2), pages 173-180, January.
    11. Dmitry Dagaev & Konstantin Sonin, 2018. "Winning by Losing," Journal of Sports Economics, , vol. 19(8), pages 1122-1146, December.
    12. Arlegi, Ritxar & Dimitrov, Dinko, 2020. "Fair elimination-type competitions," European Journal of Operational Research, Elsevier, vol. 287(2), pages 528-535.
    13. Dmitry Dagaev & Alex Suzdaltsev, 2018. "Competitive intensity and quality maximizing seedings in knock-out tournaments," Journal of Combinatorial Optimization, Springer, vol. 35(1), pages 170-188, January.
    14. Marco Ottaviani & Peter Norman Sorensen, 2010. "Noise, Information, and the Favorite-Longshot Bias in Parimutuel Predictions," American Economic Journal: Microeconomics, American Economic Association, vol. 2(1), pages 58-85, February.
    15. 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.
    16. Galvao Jr., Antonio F., 2011. "Quantile regression for dynamic panel data with fixed effects," Journal of Econometrics, Elsevier, vol. 164(1), pages 142-157, September.
    17. Bryan Clair & David Letscher, 2007. "Optimal Strategies for Sports Betting Pools," Operations Research, INFORMS, vol. 55(6), pages 1163-1177, December.
    18. David Bergman & Jason Imbrogno, 2017. "Surviving a National Football League Survivor Pool," Operations Research, INFORMS, vol. 65(5), pages 1343-1354, October.
    19. B. Jay Coleman & Allen K. Lynch, 2001. "Identifying the NCAA Tournament “Dance Card”," Interfaces, INFORMS, vol. 31(3), pages 76-86, June.
    20. Komunjer, Ivana, 2013. "Quantile Prediction," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 961-994, Elsevier.

    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:eee:jomega:v:50:y:2015:i:c:p:141-148. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/375/description#description .

    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.