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Defining the Performance Coefficient in Golf: A Case Study at the 2009 Masters

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  • Hoegh Andrew

    (Independent Researcher)

Abstract

Unlike many other sports where only the top ten or twenty participants have a realistic shot at victory, when 144 players tee it up at a PGA tournament every participant has a legit chance at winning. In golf, even the greatest players lose more often than they win, and long-shots and unknowns win some of the most prestigious events. With such parity, random chance plays a large part in determining the winner. This is evident by the world ranking of four major champions in the 2009: 69th, 71st, 33rd, and 110th. While statistical modeling is commonplace in many sports, particularly baseball, the golf world is largely untapped. Using historical data from one of golf's major championships, the Masters, this paper establishes a technique for modeling hole-by-hole results. This research has two major benefits: the opportunity to calculate real-time winning percentages and definition of the performance coefficient--which quantifies the level of performance within the player's capability. For instance, 2009 Masters winner, the 69th rated Angel Cabrera, only had a seven percent chance of defeating both Phil Mickelson and Tiger Woods over 72 holes. However, his performance coefficient of .01 signifies that he performed close to his optimal performance. While Tiger Woods and Phil Mickelson performed above average with performance coefficients of .37 and .17, respectively, on this given week they were unable to better Cabrera.

Suggested Citation

  • Hoegh Andrew, 2011. "Defining the Performance Coefficient in Golf: A Case Study at the 2009 Masters," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 7(2), pages 1-11, May.
    • Handle: RePEc:bpj:jqsprt:v:7:y:2011:i:2:n:12
    DOI: 10.2202/1559-0410.1331
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    References listed on IDEAS

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    1. Connolly, Robert A. & Rendleman, Richard J., 2008. "Skill, Luck, and Streaky Play on the PGA Tour," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 74-88, March.
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