IDEAS home Printed from https://ideas.repec.org/a/wly/mgtdec/v31y2010i7p431-452.html
   My bibliography  Save this article

Evidence of bias in NCAA tournament selection and seeding

Author

Listed:
  • B. Jay Coleman

    (Department of Management, Coggin College of Business, University of North Florida, Jacksonville, FL, USA)

  • J. Michael DuMond

    (Charles River Associates, Tallahassee, FL, USA)

  • Allen K. Lynch

    (Stetson School of Business and Economics, Mercer University, Macon, GA, USA)

Abstract

We investigate bias in the selection and seeding decisions of the NCAA Division I Men's Basketball Committee. Using data on 910 teams associated with the ten tournaments from 1999 to 2008, we test for bias toward teams from seven 'major' conferences and six 'mid-major' conferences, as well as for bias toward teams represented on the Committee. We find substantial support for the hypothesis of bias in favor of virtually all major and mid-major conferences in selection and|or seeding, as well as evidence of bias toward majors over mid-majors. We also find substantial evidence of bias toward teams with some type of Committee representation. Copyright © 2010 John Wiley & Sons, Ltd.

Suggested Citation

  • 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.
  • Handle: RePEc:wly:mgtdec:v:31:y:2010:i:7:p:431-452
    DOI: 10.1002/mde.1499
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1002/mde.1499
    File Function: Link to full text; subscription required
    Download Restriction: no

    File URL: https://libkey.io/10.1002/mde.1499?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
    ---><---

    References listed on IDEAS

    as
    1. repec:ebl:ecbull:v:4:y:2007:i:34:p:1-7 is not listed on IDEAS
    2. Todd Kuethe & Timothy Zimmer, 2008. "Major Conference Bias and the NCAA Men's Basketball Tournament," Economics Bulletin, AccessEcon, vol. 12(17), pages 1-6.
    3. 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.
    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. 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.
    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.
    7. repec:ebl:ecbull:v:12:y:2008:i:17:p:1-6 is not listed on IDEAS
    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. 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.
    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. Daniel C. Hickman, 2020. "Efficiency in the madness? examining the betting market for the ncaa men’s basketball tournament," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 44(3), pages 611-626, July.

    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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. repec:ebl:ecbull:v:4:y:2007:i:34:p:1-7 is not listed on IDEAS
    8. 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.
    9. 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.
    10. Bryan Clair & David Letscher, 2007. "Optimal Strategies for Sports Betting Pools," Operations Research, INFORMS, vol. 55(6), pages 1163-1177, December.
    11. 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.
    12. Daniel C. Hickman & Andrew G. Meyer, 2017. "Does Athletic Success Influence Persistence At Higher Education Institutions? New Evidence Using Panel Data," Contemporary Economic Policy, Western Economic Association International, vol. 35(4), pages 658-676, October.
    13. 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.
    14. 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.
    15. 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.
    16. Florios, Kostas & Skouras, Spyros, 2008. "Exact computation of max weighted score estimators," Journal of Econometrics, Elsevier, vol. 146(1), pages 86-91, September.
    17. Michael Cary & Heather Stephens, 2023. "Gendered Consequences of COVID-19 Among Professional Tennis Players," Journal of Sports Economics, , vol. 24(2), pages 241-266, February.
    18. Kovalchik Stephanie Ann, 2016. "Searching for the GOAT of tennis win prediction," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 12(3), pages 127-138, September.
    19. 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.
    20. Franceschet Massimo & Bozzo Enrico & Vidoni Paolo, 2017. "The temporalized Massey’s method," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 13(2), pages 37-48, June.
    21. McHale, Ian & Morton, Alex, 2011. "A Bradley-Terry type model for forecasting tennis match results," International Journal of Forecasting, Elsevier, vol. 27(2), pages 619-630, April.

    More about this item

    Statistics

    Access and download statistics

    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:wly:mgtdec:v:31:y:2010:i:7:p:431-452. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www3.interscience.wiley.com/cgi-bin/jhome/7976 .

    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.