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Predictions for the Masters, 2022

By Dr. Ed Feng Leave a Comment

You want to bet a Masters outright. You check out a site like Data Golf and get their win probability for each golfer. Compare it to the markets and make a bet.

Unfortunately, most of these predictions won’t show any value. For example, Xander Schauffele has a 3.0% chance to win, which doesn’t suggest value at +2400 (4% break even win probability).

To find value, you have to go beyond the predictions. Data Golf uses data on each and every shot to make predictions. Perhaps some of these shots have more randomness than others, and this presents an advantage.

To make a comparison to a different sport, consider college basketball. As I discussed in March, three point shooting has a large component of randomness. Teams that have made a high rate of threes should expect regression to the mean.

Brandon Gdula of numberFire found a similar result for putting. To understand his results, consider strokes gained, a metric for how well a golfer performs compared to the tour average. For example, consider a putt within five feet, a shot made 97% of the time. If a golfer sinks this putt, then he gains 0.03 strokes (one minus the tour average of 0.97). Missing this putt results in -0.97 strokes gained.

Brandon found that strokes gained for short putts explains most of the variance for strokes gained on all putts. To be specific, let’s look at the R-squared value. Strokes gained for putts of 15 feet or less explained 80.5% of the strokes gained overall for putting.

This implies a huge random component for long putts. Brandon suggests looking at the 73% of putts from 15 feet or less in getting a more accurate assessment of putting.

To apply this idea to the Masters, consider Xander Schauffele. Through March 18th, Brandon pulled data for players with at least 100 rounds of strokes gained data. Overall, Schauffele was 15th in strokes gained putting.

However, when only using putts from within 15 feet, Schauffele ranks first overall. He is great on putts that are predictive, and he has had some bad luck on longer putts that pulls down his overall putting strokes gained.

This analysis will be far from perfect. In Brandon’s article, he mentioned that he didn’t find putting at any distance to be predictive over half year intervals. There is a ton of randomness in putting.

However, Schauffele is a great all around golfer who finished 3rd in last year’s Masters. The putting data suggests that the numbers might be low on him, and there is value in betting Schauffele to win at +2400.

Here are golf and Masters resources to check out:

  • The putting study by Brandon Gdula
  • Masters predictions by Brandon Gdula
  • Data Golf. They put most of their predictions behind a pay wall but they also have many free resources.

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  • About
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