Defining the Performance Coefficient in Golf: A Case Study at the 2009 Masters
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Andrew Hoegh
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.
©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
Articles in the same Issue
- Conference Paper
- Uncovering Europe's Best Goalscorers from the 2009-2010 Season
- Dynamic Effort, Sustainability, Myopia, and 110% Effort
- The Intra-Match Home Advantage in Australian Rules Football
- The Relationship between Leader Experience and Team Performance in Cross-Sectional and Longitudinal Designs
- Stratified Odds Ratios for Evaluating NBA Players Based on their Plus/Minus Statistics
- Dependence Relationships between On Field Performance, Wins, and Payroll in Major League Baseball
- Optimal Dynamic Clustering Through Relegation and Promotion: How to Design a Competitive Sports League
- Perception ? Reality: Analyzing Specific Allegations of NBA Referee Bias
- NFL Prediction using Committees of Artificial Neural Networks
- An Alternative to the NFL Draft Pick Value Chart Based upon Player Performance
- Monte Carlo Simulation for High School Football Playoff Seed Projection
- Defining the Performance Coefficient in Golf: A Case Study at the 2009 Masters
- Reconsideration of the Best Batting Order in Baseball: Is the Order to Maximize the Expected Number of Runs Really the Best?
- Never Too Late to Win
- An Extension of the Pythagorean Expectation for Association Football
- Pitcher Accuracy Through Catcher Spotting: Assessing Rater Reliability
- Valuing Nostalgia: The Case of the Topps 1957 Baseball Cards
Articles in the same Issue
- Conference Paper
- Uncovering Europe's Best Goalscorers from the 2009-2010 Season
- Dynamic Effort, Sustainability, Myopia, and 110% Effort
- The Intra-Match Home Advantage in Australian Rules Football
- The Relationship between Leader Experience and Team Performance in Cross-Sectional and Longitudinal Designs
- Stratified Odds Ratios for Evaluating NBA Players Based on their Plus/Minus Statistics
- Dependence Relationships between On Field Performance, Wins, and Payroll in Major League Baseball
- Optimal Dynamic Clustering Through Relegation and Promotion: How to Design a Competitive Sports League
- Perception ? Reality: Analyzing Specific Allegations of NBA Referee Bias
- NFL Prediction using Committees of Artificial Neural Networks
- An Alternative to the NFL Draft Pick Value Chart Based upon Player Performance
- Monte Carlo Simulation for High School Football Playoff Seed Projection
- Defining the Performance Coefficient in Golf: A Case Study at the 2009 Masters
- Reconsideration of the Best Batting Order in Baseball: Is the Order to Maximize the Expected Number of Runs Really the Best?
- Never Too Late to Win
- An Extension of the Pythagorean Expectation for Association Football
- Pitcher Accuracy Through Catcher Spotting: Assessing Rater Reliability
- Valuing Nostalgia: The Case of the Topps 1957 Baseball Cards
