Matt Fitzpatick has been on a tear. He has five top 10 finishes in his last six tournaments, and this includes a win at the US Open.
Data Golf ranks Fitzpatrick 5th in the world. It seems like a no brainer that he should be favored over Jordan Spieth, the 20th ranked golfer. In their match up section, Data Golf gives a 57.8% chance that Fitzpatrick beats Spieth.
However, there are limitations to predictive golf analytics.
On an episode of The Football Analytics Show, Matt Courchene, the analytics guru behind Data Golf, explained how his model has problems with golfers like Spieth. The model uses years of data, and it doesn’t react too much to a stretch of good performance.
This analysis is based on research over all golfers. However, Spieth might be an exception. He rocked the golf world with two wins and a 2nd place at majors in 2015. He won another major in 2017.
Spieth’s past performance suggests a high ceiling. Data Golf should have a different reaction to a stretch of good play from Spieth than an average golfer. Right now, it doesn’t.
On my podcast, Matt admitted that his model is probably sluggish to react to Spieth compared to the markets. This season, Spieth has five top 10 finishes and a win at the RBC Heritage.
Two other reasons also favor Spieth over Fitzpatrick:
- Spieth excels at The Open. For example, he won this major in 2017 and finished 2nd last season.
- Circa has better win odds for Spieth (+1800) than Fitzpatrick (+2100).
This suggests value on Spieth +100 in a match up over Fitzpatrick at DraftKings.
In no way do I mean to denigrate the work on Data Golf. In fact, their work has significant market influence.
Some sports books go to the extent of copying Data Golf’s match up probabilities. This is lazier than finding a wife in a catalog from Eastern Europe.
It’s also another reason why you might like Spieth in a match up over Fitzpatrick.
Check out Matt Courchene’s appearance on The Football Analytics Show podcast at any of these places:
- The Power Rank
- YouTube, with links to various segments
- Apple Podcasts
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