Match Play: Using Statistical Methods to Categorize PGA Tour Players' Careers

This paper uses K-means cluster analysis and multinomial mixture models to categorize professional golfer performance for the period 1980 to 2006. We collected, cleaned and analyzed final annual money list standings for PGA Tour players from www.pgatour.com. Correlation patterns between other measures suggested that career performance was well described by the proportion of years a player finished in specific meaningful money list categories such as Top 10 or outside the top 125. Using both clustering methods, we found that players divide into five natural and interpretable groupings, one being a small `Elite' group and four others which we refer to as `Distinguished,' `Established,' `Journeymen' and `Grinders.' We used analysis of variance to compare groups on the basis of other career performance measures including consistency, streakiness, longevity, and others as well as to investigate differences in the clusters produced by the two methods. A summary of these measures for the entire set gives a bleak outlook for any prospective professional golfer and singles out the greatness of the elite few, epitomized by Tiger Woods. This methodology extends to any sport or endeavor in which performance is measured in terms of end of year rankings or money lists.