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Anomalies in Tournament Design: The Madness of March Madness

Author

Listed:
  • Baumann Robert

    (College of the Holy Cross)

  • Matheson Victor A.

    (College of the Holy Cross)

  • Howe Cara A.

    (College of the Holy Cross)

Abstract

Tournament design is of crucial importance in competitive sports. The primary goal of effective tournament design is to provide incentives for the participants to maximize their performance both during the tournament and in the time period leading up to the tournament. In spectator sports, a secondary goal of tournament design is to also promote interesting match ups that generate fan interest. Seeded tournaments, in general, promote both goals. Teams or individuals with strong performances leading up to a tournament receive higher seeds which increase their chances of progressing further in the tournament. Furthermore, seeding ensures that the strongest teams or players are most likely to meet in the final rounds of the tournament when fan interest is at its peak. Under some distributions of team or player skill, however, a seeding system can introduce anomalies that could affect incentives.Our analysis of the NCAA men's basketball tournament uncovers such an anomaly. The seeding system in this tournament gives teams with better success in the regular season more favorable first round match ups, but the tournament is not reseeded as the games progress. Therefore, while higher seeds progress to the 2nd round of the tournament at uniformly higher rates than lower seeds, this relationship breaks down in later rounds. We find that 10th and 11th seeds average more wins and typically progress farther in the tournament than 8th and 9th seeds. This finding violates the intended incentive structure of seeded tournaments.

Suggested Citation

  • 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.
  • Handle: RePEc:bpj:jqsprt:v:6:y:2010:i:2:n:4
    DOI: 10.2202/1559-0410.1233
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    References listed on IDEAS

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    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. Dmitry Dagaev & Alex Suzdaltsev, 2015. "Seeding, Competitive Intensity and Quality in Knock-Out Tournaments," HSE Working papers WP BRP 91/EC/2015, National Research University Higher School of Economics.
    3. 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.
    4. Arlegi, Ritxar & Dimitrov, Dinko, 2020. "Fair elimination-type competitions," European Journal of Operational Research, Elsevier, vol. 287(2), pages 528-535.
    5. repec:awi:wpaper:0600 is not listed on IDEAS
    6. 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.
    7. 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.
    8. Dmitry Dagaev & Konstantin Sonin, 2018. "Winning by Losing," Journal of Sports Economics, , vol. 19(8), pages 1122-1146, December.
    9. 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.
    10. 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.
    11. Stanton Isabelle & Williams Virginia Vassilevska, 2013. "The structure, efficacy, and manipulation of double-elimination tournaments," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 9(4), pages 319-335, December.
    12. 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.
    13. Wright, Mike, 2014. "OR analysis of sporting rules – A survey," European Journal of Operational Research, Elsevier, vol. 232(1), pages 1-8.

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    More about this item

    JEL classification:

    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism
    • D02 - Microeconomics - - General - - - Institutions: Design, Formation, Operations, and Impact

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