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A comparative study of scoring systems by simulations

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  • László Csató

Abstract

We study the trade-off between two risks for scoring rules used in sports competitions containing multiple contests: (1) the threat of early clinch when the title is clinched before the last contest(s) of the competition take place; and (2) the danger of winning the competition without finishing first in any contest. Four historical points scoring systems of the Formula One World Championship are compared with the family of geometric scoring rules. The current scheme seems to be a reasonable compromise close to the Pareto frontier. Our results contribute to the issue of choosing an optimal set of point values.

Suggested Citation

  • László Csató, 2023. "A comparative study of scoring systems by simulations," Journal of Sports Economics, , vol. 24(4), pages 526-545, May.
  • Handle: RePEc:sae:jospec:v:24:y:2023:i:4:p:526-545
    DOI: 10.1177/15270025221134241
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    References listed on IDEAS

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    1. Shmuel Nitzan & Ariel Rubinstein, 1981. "A further characterization of Borda ranking method," Public Choice, Springer, vol. 36(1), pages 153-158, January.
    2. Vincent Merlin, 2003. "The axiomatic characterization of majority voting and scoring rules," Post-Print halshs-00069506, HAL.
    3. Pedro Garcia-del-Barrio & J. James Reade, 2022. "Does certainty on the winner diminish the interest in sport competitions? The case of formula one," Empirical Economics, Springer, vol. 63(2), pages 1059-1079, August.
    4. Pavel Yu. Chebotarev & Elena Shamis, 1998. "Characterizations of scoring methodsfor preference aggregation," Annals of Operations Research, Springer, vol. 80(0), pages 299-332, January.
    5. Corona Francisco & Wiper Michael Peter & Horrillo Juan de Dios Tena, 2017. "On the importance of the probabilistic model in identifying the most decisive games in a tournament," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 13(1), pages 11-23, March.
    6. Stein, William E. & Mizzi, Philip J. & Pfaffenberger, Roger C., 1994. "A stochastic dominance analysis of ranked voting systems with scoring," European Journal of Operational Research, Elsevier, vol. 74(1), pages 78-85, April.
    7. Llamazares, Bonifacio & Peña, Teresa, 2013. "Aggregating preferences rankings with variable weights," European Journal of Operational Research, Elsevier, vol. 230(2), pages 348-355.
    8. J Bekker & W Lotz, 2009. "Planning Formula One race strategies using discrete-event simulation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(7), pages 952-961, July.
    9. Geenens, Gery, 2014. "On the decisiveness of a game in a tournament," European Journal of Operational Research, Elsevier, vol. 232(1), pages 156-168.
    10. Brams, Steven J. & Fishburn, Peter C., 2002. "Voting procedures," Handbook of Social Choice and Welfare, in: K. J. Arrow & A. K. Sen & K. Suzumura (ed.), Handbook of Social Choice and Welfare, edition 1, volume 1, chapter 4, pages 173-236, Elsevier.
    11. Smith, John H, 1973. "Aggregation of Preferences with Variable Electorate," Econometrica, Econometric Society, vol. 41(6), pages 1027-1041, November.
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    More about this item

    Keywords

    competition design; Formula One; OR in sports; rank aggregation; scoring system;
    All these keywords.

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • Z20 - Other Special Topics - - Sports Economics - - - General

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