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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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    1. Trono John A., 2010. "Rating/Ranking Systems, Post-Season Bowl Games, and "The Spread"," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 6(3), pages 1-20, July.
    2. Stefani Ray & Pollard Richard, 2007. "Football Rating Systems for Top-Level Competition: A Critical Survey," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 3(3), pages 1-22, July.
    3. Raymond Stefani, 1997. "Survey of the major world sports rating systems," Journal of Applied Statistics, Taylor & Francis Journals, vol. 24(6), pages 635-646.
    4. Ruth N. Bolton & Randall G. Chapman, 2008. "Searching For Positive Returns At The Track: A Multinomial Logit Model For Handicapping Horse Races," World Scientific Book Chapters, in: Donald B Hausch & Victor SY Lo & William T Ziemba (ed.), Efficiency Of Racetrack Betting Markets, chapter 17, pages 151-171, World Scientific Publishing Co. Pte. Ltd..
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