Gdula's Golf Simulations: U.S. Open
Volatility is the name of the game in golf, and picking winners isn't easy. With fields of 150-plus golfers sometimes being separated by how a putt or two falls each week, predicting golf can be absurdly tough.
We'll never be able to capture everything that goes into a golfer's expectations for a week, but we can try to account for that by simulating out the weekend and seeing what happens.
The Process
Over the years, I have made plenty of tweaks to my original golf model, which uses a combination of the OWGR's field strength numbers and datagolf's field strength numbers to adjust each golfer's score relative to the field (on the PGA Tour, the European Tour, and the Korn Ferry Tour).
The ultimate goal is to place a score from the Waste Management Open, the BMW International Open, and the Knoxville Open on level playing fields. This adjusted strokes metric lets me see how golfers are performing across all tours. From there, a golfer's adjusted stroke data is combined with their round-to-round variance to see how the field is likely to perform when playing out the event thousands of times.
In addition to that long-term adjusted form, I factor in course-level adjustments for course fit.
I run a second model that uses more granular strokes gained data, which allows me to very easily adjust for course fit. The results are averaged out.
I let the data do the talking and don't make many tweaks -- if any. Golfers with a small sample get regressed to a low-end PGA Tour player to round out their samples. Data points are weighted more heavily toward recent performance.
Here are the most likely winners for the U.S. Open, according to the models.
| Golfer | Simulated Win% |
Simulated Top-10% |
Simulated Made Cut% |
FanDuel Sportsbook Win Odds |
|---|---|---|---|---|
| Jon Rahm | 6.3% | 36.7% | 82.6% | +950 |
| Xander Schauffele | 5.4% | 33.3% | 81.1% | +1800 |
| Dustin Johnson | 5.1% | 31.0% | 79.8% | +1500 |
| Bryson DeChambeau | 4.2% | 29.8% | 78.8% | +1600 |
| Justin Thomas | 3.9% | 26.7% | 77.8% | +2300 |
| Tony Finau | 3.5% | 26.7% | 77.1% | +2400 |
| Jordan Spieth | 3.3% | 24.6% | 75.3% | +2100 |
| Patrick Cantlay | 3.2% | 25.4% | 76.0% | +2400 |
| Viktor Hovland | 2.8% | 23.5% | 74.9% | +2400 |
| Rory McIlroy | 2.8% | 23.4% | 74.6% | +1800 |
| Patrick Reed | 2.7% | 22.1% | 74.4% | +2800 |
| Brooks Koepka | 2.5% | 20.6% | 72.7% | +1800 |
| Webb Simpson | 2.5% | 20.3% | 73.0% | +5500 |
| Daniel Berger | 2.4% | 20.0% | 72.6% | +4400 |
| Collin Morikawa | 2.3% | 20.9% | 72.5% | +1900 |
| Tyrrell Hatton | 2.2% | 18.7% | 71.2% | +4200 |
| Will Zalatoris | 1.8% | 17.8% | 70.4% | +4100 |
| Scottie Scheffler | 1.8% | 19.4% | 71.4% | +4100 |
| Jason Kokrak | 1.6% | 15.1% | 67.0% | +7000 |
| Louis Oosthuizen | 1.6% | 16.6% | 69.1% | +5000 |
| Paul Casey | 1.6% | 16.3% | 68.3% | +4700 |
| Joaquin Niemann | 1.5% | 15.5% | 67.9% | +7000 |
| Hideki Matsuyama | 1.4% | 15.5% | 67.3% | +3400 |
| Cameron Smith | 1.4% | 16.0% | 68.3% | +6000 |
| Matthew Fitzpatrick | 1.4% | 16.3% | 69.2% | +6500 |
| Abraham Ancer | 1.3% | 14.6% | 66.8% | +7000 |
| Corey Conners | 1.2% | 13.4% | 65.9% | +7500 |
| Harris English | 1.1% | 12.4% | 64.1% | +9500 |
| Charley Hoffman | 1.1% | 13.3% | 64.9% | +8000 |
| Sam Burns | 0.9% | 11.6% | 62.6% | +11000 |
| Shane Lowry | 0.8% | 11.2% | 62.3% | +3700 |
| Brian Harman | 0.8% | 11.2% | 63.3% | +13000 |
| Sergio Garcia | 0.8% | 10.1% | 60.8% | +11000 |
| Justin Rose | 0.8% | 9.7% | 59.5% | +4700 |
| Si Woo Kim | 0.7% | 9.7% | 60.0% | +17000 |
| Russell Henley | 0.7% | 7.6% | 56.1% | +29000 |
| Tommy Fleetwood | 0.7% | 8.5% | 57.8% | +7500 |
| Adam Scott | 0.7% | 9.1% | 58.8% | +9500 |
| Ryan Palmer | 0.7% | 9.0% | 58.9% | +15000 |
| Christiaan Bezuidenhout | 0.6% | 8.0% | 57.0% | +16000 |
| Carlos Ortiz | 0.6% | 8.5% | 58.4% | +15000 |
| Gary Woodland | 0.6% | 7.8% | 56.5% | +9000 |
| Max Homa | 0.6% | 8.9% | 58.8% | +11000 |
| Matt Wallace | 0.6% | 7.6% | 55.9% | +15000 |
| Billy Horschel | 0.6% | 7.5% | 56.4% | +16000 |
| Lanto Griffin | 0.6% | 7.7% | 57.8% | +21000 |
| Sungjae Im | 0.5% | 8.0% | 57.8% | +8000 |
| Stewart Cink | 0.5% | 8.8% | 57.9% | +18000 |
| Matt Jones | 0.5% | 8.0% | 57.7% | +23000 |
| Bubba Watson | 0.5% | 7.7% | 56.8% | +15000 |
| Kevin Streelman | 0.5% | 8.6% | 58.2% | +18000 |
| Marc Leishman | 0.5% | 6.4% | 53.6% | +8500 |
| Phil Mickelson | 0.5% | 5.8% | 53.2% | +5500 |
The favorite by the betting odds, Jon Rahm (+950 at Golf odds) is technically the favorite in my model, but only just -- and not enough to want to bet him.
The betting value comes in positively on Xander Schauffele (+1800) and even on Justin Thomas (+2300), which is surprising. Schauffele has Torrey Pines ties and is feeling confident with his wristlock putting grip. We're really starting to get a strong number on Thomas, though, and that's appealing. Don't forget that Bryson DeChambeau could be had at +2800 the week of the U.S. Open last summer.
Other golfers who outperformed their betting odds in the simulations include Tyrrell Hatton (+4200), Daniel Berger (+4400), Webb Simpson (+5500 -- a former U.S. Open winner), Jason Kokrak (+7000), and Joaquin Niemann (+7000).
Tony Finau (+2400), Patrick Reed (+2800), and Louis Oosthuizen (+5000) are slight negative values but still in my consideration set.
The model is never high enough on Brooks Koepka (+1800) because he really does step up his game in majors, which is hard to quantify, and I don't aim to alter the stats to fit any narratives. However, I'm leaning toward betting Brooks at the top.
I'm settling in on Koepka, Schauffele, and Oosthuizen for now.
