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The Methodology of Officially Recognized International Sports Rating Systems

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  • Stefani Ray

    (California State University, Long Beach)

Abstract

A comprehensive comparative survey is presented, covering official rating systems as published by internationally recognized sports federations. Mind sports and physical sports are both included. As of November 2010, competitions in 159 international sports are organized by sports federations recognized by the IOC, Sport Accord and by Wikipedia identified under "List of International Sport Federations." Of the 159 sports, 18 are combat sports in which opponents are in direct physical contact as in boxing and wrestling, 74 are independent sports in which significant contact is not allowed as in swimming and archery and 67 are object sports in which indirect contact is allowed while opponents attempt to control an object as in basketball and chess. Of the 159 sports, 60 sports have no rating system, two combat sports have a subjective rating system, 84 sports have an accumulative system in which points accrue non-decreasingly over some window of time, and 13 sports have an adjustive system in which a rating self adjusts based on the difference between some observed result and a prediction of that result based on past performance. For accumulative rating systems, features include converting results to points, ageing results more than one year old, and possibly adjusting points using other performance measures. Such systems are favored by tournament organizers who want to encourage many top competitors to enter as for skiing and tennis. The adjustive systems include Elo, probit and averaging methods. These systems are favored for their technical sophistication by sports such as chess, draughts, go, cricket, and women's soccer. This study thus identifies the observed successful methodology used by the various sports federations to publish comparative ratings. Predictive success of certain rating systems are tabulated for FIBA world championship basketball, Grand Slam tennis and FIFA men's world cup soccer.

Suggested Citation

  • Stefani Ray, 2011. "The Methodology of Officially Recognized International Sports Rating Systems," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 7(4), pages 1-22, October.
    • Handle: RePEc:bpj:jqsprt:v:7:y:2011:i:4:n:10
    DOI: 10.2202/1559-0410.1347
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    References listed on IDEAS

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    Cited by:

    1. Kovalchik, Stephanie, 2020. "Extension of the Elo rating system to margin of victory," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1329-1341.
    2. 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.
    3. Subhasis Ray, 2021. "Identification of Research Paradigms for Managing the Cricketing Ecosystem Using Stakeholder Analysis and Text Mining," Management and Labour Studies, XLRI Jamshedpur, School of Business Management & Human Resources, vol. 46(3), pages 289-312, August.
    4. Lasek, Jan & Gagolewski, Marek, 2021. "Interpretable sports team rating models based on the gradient descent algorithm," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1061-1071.
    5. Kovalchik, Stephanie & Reid, Machar, 2019. "A calibration method with dynamic updates for within-match forecasting of wins in tennis," International Journal of Forecasting, Elsevier, vol. 35(2), pages 756-766.
    6. Collingwood, James A.P. & Wright, Michael & Brooks, Roger J, 2022. "Evaluating the effectiveness of different player rating systems in predicting the results of professional snooker matches," European Journal of Operational Research, Elsevier, vol. 296(3), pages 1025-1035.
    7. Barrow Daniel & Drayer Ian & Elliott Peter & Gaut Garren & Osting Braxton, 2013. "Ranking rankings: an empirical comparison of the predictive power of sports ranking methods," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 9(2), pages 187-202, June.
    8. Devlin Stephen & Treloar Thomas & Creagar Molly & Cassels Samuel, 2021. "An iterative Markov rating method," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 17(2), pages 117-127, June.

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