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Choosing Opponents in Skiing Sprint Elimination Tournaments

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Abstract

In this study we analyse data from world cup cross-country skiing sprint elimination tournaments for men and women in 2015-2020. Instead of being assigned a quarterfinal according to a seeding scheme, prequalified athletes choose themselves in sequential order in which of five quarterfinals to compete. Due to a time constraint on the day the competition is held, the recovery time between the knockout heats varies. This implies a clear advantage for the athlete to race in an early rather than in a late quarterfinal to maximize her probability of reaching the podium. The purpose of the paper is to analyse the athletes’ choices facing the trade-off between recovery time and expected degree of competition when choosing in which quarterfinal to compete. We find empirical support for the prediction that higher ranked athletes from the qualification round prefer to compete in early quarterfinals, despite facing expected harder competition. Nevertheless, our results also suggest that athletes underestimate the value of choosing an early quarterfinal. In addition, we propose a seeding scheme capturing the fundamental disparity across quarterfinals using the estimates from a logistic regression model.

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  • 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.
    • Handle: RePEc:hhs:oruesi:2020_006
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    1. 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.
    2. Christian Groh & Benny Moldovanu & Aner Sela & Uwe Sunde, 2012. "Optimal seedings in elimination tournaments," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 49(1), pages 59-80, January.
    3. Dmitry Ryvkin, 2011. "Fatigue in Dynamic Tournaments," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 20(4), pages 1011-1041, December.
    4. Rick Harbaugh & Tilman Klumpp, 2005. "Early Round Upsets and Championship Blowouts," Economic Inquiry, Western Economic Association International, vol. 43(2), pages 316-329, April.
    5. Amegashie, J. Atsu & Cadsby, C. Bram & Song, Yang, 2007. "Competitive burnout: Theory and experimental evidence," Games and Economic Behavior, Elsevier, vol. 59(2), pages 213-239, May.
    6. 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.
    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.
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    1. Karlsson, Niklas & Lunander, Anders, 2022. "Are Some Athletes More Cognitive Skilled than Others when Choosing their Opponents in Skiing-Sprint Elimination Tournaments?," Working Papers 2022:13, Örebro University, School of Business, revised 14 Dec 2022.

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    More about this item

    Keywords

    choosing opponent; sequential choise; seeding; skiing sprint;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • Z20 - Other Special Topics - - Sports Economics - - - General

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