Golf Analytics

How Golfers Win

Predicting Professional Performance of Collegiate Players (REDUX)

Let’s start with some tough love. This was a laughably lazy attempt at performing this study. Hopefully this effort will be less awful, considering I think I have a somewhat proper sample.

Quickly, I’m looking for the correlation between Jeff Sagarin’s college golf rankings and my own Z-Score Model Ratings. Sagarin publishes the best (only?) math based ranking of college golfers. There’s obviously issues of sample size in the college game (most teams play <15 tournaments at normally three rounds), but Rankings are fairly strongly correlated between seasons (R=.62) even though players are in a volatile period in their golf development. To combat concerns about sample-size, I’ve averaged the golfer’s Ranking over their college career. This isn’t ideal either, but, again, a max of 45 rounds isn’t something I’m comfortable using.

Once I had those, I looked in my Z-Score database for the first instance of those players playing >20 rounds in one season and took their Z-Score from that season. A few concerns about this method of finding seasons: 1) if a golfer has less than 20 rounds in every season, they won’t show up at all, 2) if a golfer has less than 20 rounds before getting greater than 20 rounds in a subsequent season, that first season will be ignored, and 3) it can often be several years before a golfer accumulates >20 rounds on the PGA/ Tours (I do not have eGolf/NGA/Challenge/Asian/etc. Tour Ratings). Of these concerns, #1 isn’t that big of a deal. Plenty of collegians don’t have the game for high level pro golf – there are less than 1,000 guys who play regularly on the three Tours I track and I’ve gathered data on the top 500 golfers from each season. #2 isn’t very concerning. The sample has to be set somewhere. #3 concerns me the most because comparing a 26 year old with three seasons of minor tour golf to a 21 year old right out of college is kind of apples and oranges, but perhaps I’ll run another study in the future that excludes those data points.

First information about my sample. N=80, all but three golfers had at least 2 seasons of college golf (average was 3.2 seasons) – Spieth, Todd Baek, and Roger Sloan had the single seasons, the average performance in college was a 71.1, and the average performance in pro golf was a +0.15 Z-Score (below average). I’ve chosen to display the pro results in terms of strokes better than/worse than average. Divide by 3 to get the corresponding Z-Score.

The results were much less irrelevant than that turd I linked above:

college golf regression

The correlation was R=.49, which indicates that we can predict pro performance on a roughly 50% Sagarin/50% mean basis. The equation to use is y=0.47x-32.9 where y is pro performance in Strokes to average (divide by 3 to get Z-Score) and x is Sagarin Rating. For comparison, I’ve found that the correlation between back-to-back professional seasons is about 70% (70% Year 1 + 30% mean) and correlation between back-to-back college seasons is about 63% (63% Year 1 + 37% mean). Based on the concerns I laid out above, I think that’s not terrible.

Unsurprisingly, this method of predicting would have misses. Sagarin did not think highly of Keegan Bradley coming out of St. John’s. Whether it was poor play or an awful schedule, Keegan averaged a 72.5 over three years in school. Keegan was one of those guys who turned pro and who took several seasons to record Major Tour rounds. He graduated in 2008 and didn’t record a Major Tour round until 2010.

I do take solace in the fact that no golfer who averaged better than a 70.0 (basically in the top 15 each season) failed to perform better than the sample average in their first season. This indicates that success in college is correlated with success in professional golf. In fact, only a single player with a Sagarin below 70.0 in the entire 2005-2013 sample (who has graduated) has failed to record 20 or more Major Tour rounds – (Arnond Vongvanij, who has exclusively played on the Asian Tour, has a professional win, and is ranked 218th by the Official World Goal Ranking).

This method predicts success for the best collegian golfer not currently in pro golf, Justin Thomas (69.2), who plans to turn pro after the Walker Cup. He’s recorded a -0.06 Z-Score in 12 rounds dating back to 2012.


2 responses to “Predicting Professional Performance of Collegiate Players (REDUX)

  1. Pingback: Predicting Professional Performance of Collegiate Golfers (Part II) | Golf Analytics

  2. Pingback: Predicting Professional Performance of Collegiate Golfers (Part III) | Golf Analytics

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