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 Corales Puntacana Resort & Club Championship, according to the models.
| Golfer | Simulated Win% | Simulated Top-10% | Simulated Made Cut% | FanDuel Sportsbook Win Odds |
|---|---|---|---|---|
| Charley Hoffman | 5.9% | 35.0% | 84.2% | +1800 |
| Taylor Pendrith | 4.0% | 24.9% | 77.1% | +4000 |
| Charles Howell III | 3.7% | 26.3% | 80.0% | +4800 |
| Emiliano Grillo | 3.1% | 22.3% | 76.8% | +1800 |
| Thomas Detry | 2.8% | 19.8% | 74.5% | +2600 |
| Thomas Pieters | 2.8% | 18.4% | 72.9% | +1800 |
| Sepp Straka | 2.7% | 23.6% | 78.5% | +4000 |
| Luke List | 2.5% | 20.4% | 76.0% | +3100 |
| Jhonattan Vegas | 2.5% | 19.6% | 75.0% | +2600 |
| Lee Hodges | 2.4% | 16.1% | 65.2% | +3200 |
| Roger Sloan | 2.3% | 19.8% | 74.5% | +4500 |
| William Gordon | 2.0% | 18.3% | 73.3% | +4500 |
| Pat Perez | 1.8% | 18.3% | 73.4% | +7000 |
| Brandon Wu | 1.8% | 12.8% | 57.9% | +2600 |
| Tom Lewis | 1.7% | 15.7% | 70.9% | +4500 |
| Patrick Rodgers | 1.7% | 17.0% | 72.7% | +3400 |
| Joel Dahmen | 1.7% | 17.1% | 72.3% | +4800 |
| Stephan Jaeger | 1.7% | 14.7% | 68.3% | +4800 |
| Kristoffer Ventura | 1.6% | 16.9% | 72.0% | +7000 |
| Brandon Hagy | 1.6% | 15.2% | 69.9% | +2900 |
| Lucas Herbert | 1.5% | 12.1% | 62.3% | +5500 |
| Justin Suh | 1.5% | 15.3% | 70.2% | +3100 |
| Brice Garnett | 1.4% | 14.7% | 70.0% | +4000 |
| Tyler Duncan | 1.4% | 15.6% | 69.8% | +10000 |
| Danny Willett | 1.4% | 13.0% | 67.8% | +3400 |
| Chase Seiffert | 1.3% | 13.5% | 68.4% | +4800 |
| Chesson Hadley | 1.3% | 13.5% | 69.1% | +10000 |
| Greyson Sigg | 1.3% | 9.6% | 55.0% | +4800 |
| Sam Ryder | 1.3% | 12.6% | 67.6% | +3400 |
| Adam Schenk | 1.2% | 14.0% | 68.7% | +4800 |
| Troy Merritt | 1.1% | 12.3% | 66.5% | +10000 |
| Fabrizio Zanotti | 1.0% | 12.2% | 66.4% | +6000 |
| Peter Uihlein | 1.0% | 8.0% | 50.1% | +5500 |
| Nate Lashley | 1.0% | 10.3% | 65.0% | +3400 |
| Camilo Villegas | 1.0% | 11.2% | 63.4% | +4800 |
| Brian Stuard | 0.9% | 11.5% | 65.3% | +10000 |
| Hank Lebioda | 0.9% | 11.7% | 66.2% | +10000 |
| Bronson Burgoon | 0.8% | 9.2% | 62.2% | +4800 |
| Padraig Harrington | 0.8% | 6.5% | 50.7% | +5000 |
| Joseph Bramlett | 0.8% | 8.8% | 62.2% | +8000 |
| Vincent Whaley | 0.7% | 9.2% | 62.9% | +10000 |
| Ryan Brehm | 0.7% | 6.6% | 52.0% | +10000 |
| Rafa Cabrera Bello | 0.7% | 8.1% | 60.6% | +4800 |
| Zhang Xinjun | 0.6% | 8.3% | 59.9% | +6000 |
| Aaron Baddeley | 0.6% | 7.0% | 58.2% | +5000 |
| Ben Martin | 0.6% | 6.0% | 50.5% | +10000 |
| Vaughn Taylor | 0.6% | 7.6% | 59.1% | +8000 |
| Tyler McCumber | 0.5% | 6.7% | 58.5% | +5500 |
| Bill Haas | 0.5% | 8.7% | 61.4% | +13000 |
| Rob Oppenheim | 0.5% | 8.3% | 59.5% | +6500 |
| Josh Teater | 0.5% | 5.5% | 50.2% | +10000 |
| Paul Barjon | 0.5% | 6.5% | 55.2% | +15000 |
| Robby Shelton IV | 0.5% | 8.1% | 60.3% | +10000 |
| Alex Smalley | 0.5% | 5.5% | 53.9% | +10000 |
| J.B. Holmes | 0.5% | 5.2% | 47.8% | +5500 |
| Tim Wilkinson | 0.5% | 7.2% | 56.8% | +7000 |
| Beau Hossler | 0.5% | 6.2% | 56.1% | +10000 |
| Satoshi Kodaira | 0.5% | 6.8% | 57.1% | +10000 |
If you were underwhelmed with last week's field, well, buckle up.
Charley Hoffman does deserve to be a co-favorite at +1800, per the simulations, and there's actually value on him at this number. He's pretty easily the best long-term player in the field when adjusted for field strength.
Charles Howell shortened from +4800 to +2800, and it's deserved. My data rates him as the second-best golfer in the field long-term, and there's still value on him at +2800
The model is showing heavier value in mid-range play Taylor Pendrith (+4000), who is the best statistical fit for Corales, per datagolf,
Some other golfers who outperformed their posted odds on FanDuel Sportsbook include Sepp Straka (+4000), Roger Sloan (+4500), Pat Perez (+7000), Kristoffer Ventura (+7000), Tyler Duncan (+10000), and Chesson Hadley (+10000).
I already bet Pendrith for an outright and will update this closer to Thursday with my other bets.