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 Zurich Classic, according to the models.
| Team | Simulated Win% | Simulated Top-10% | Simulated Made Cut% | FanDuel Sportsbook Win Odds |
|---|---|---|---|---|
| Schauffele/Cantlay | 12.2% | 53.8% | 81.0% | +700 |
| Rahm/Palmer | 10.3% | 50.2% | 79.9% | +700 |
| Watson/Scheffler | 4.8% | 33.5% | 68.7% | +1400 |
| Morikawa/Wolff | 4.2% | 30.2% | 67.4% | +1400 |
| Finau/Champ | 3.9% | 29.5% | 67.8% | +1400 |
| Homa/Gooch | 3.7% | 28.4% | 65.3% | +3100 |
| Horschel/Burns | 3.5% | 28.3% | 64.7% | +2000 |
| Kirk/Todd | 3.5% | 29.5% | 65.9% | +2000 |
| Willett/Hatton | 3.0% | 26.2% | 63.6% | +2700 |
| Smith/Leishman | 2.8% | 26.0% | 63.3% | +900 |
| Hovland/Ventura | 2.7% | 26.3% | 63.9% | +3400 |
| Oosthuizen/Schwartzel | 2.6% | 23.2% | 59.9% | +3300 |
| Frittelli/Streelman | 2.6% | 23.1% | 61.5% | +3400 |
| Dahmen/Griffin | 2.2% | 21.5% | 59.7% | +4100 |
| Bradley/Steele | 2.1% | 21.1% | 60.2% | +2900 |
| Grace/Varner III | 1.9% | 20.1% | 57.6% | +2900 |
| Kokrak/Perez | 1.8% | 22.5% | 61.2% | +6500 |
| Clark/Rooyen | 1.5% | 17.5% | 55.1% | +5500 |
| Im/Hun An | 1.4% | 18.0% | 56.9% | +4100 |
| Noren/Norlander | 1.4% | 17.8% | 54.4% | +6500 |
| Glover/Reavie | 1.4% | 17.1% | 54.8% | +4500 |
| Ghim/Suh | 1.4% | 17.9% | 56.7% | +4500 |
| Pieters/Lewis | 1.2% | 14.2% | 52.0% | +5500 |
| Garnett/Stallings | 1.1% | 14.0% | 51.5% | +15000 |
| Laird/Taylor | 1.0% | 13.3% | 50.1% | +8000 |
| NeSmith/Seiffert | 1.0% | 14.9% | 51.8% | +10000 |
| Brown/Kisner | 1.0% | 12.8% | 50.6% | +5000 |
| Castro/Tringale | 0.9% | 13.6% | 51.9% | +5500 |
| Straka/Teater | 0.9% | 12.6% | 49.8% | +12000 |
| Sloan/Baddeley | 0.9% | 10.8% | 46.4% | +15000 |
| Redman/Ryder | 0.9% | 12.7% | 49.2% | +10000 |
| Thompson/Gordon | 0.9% | 13.0% | 50.1% | +6500 |
| Knox/Stuard | 0.9% | 11.8% | 47.9% | +6500 |
| Rose/Stenson | 0.8% | 12.4% | 48.9% | +3100 |
| Piercy/Bhatia | 0.8% | 12.4% | 49.7% | +10000 |
| Werenski/Uihlein | 0.7% | 11.2% | 46.9% | +9000 |
| Duncan/Schenk | 0.7% | 11.6% | 47.9% | +12000 |
| Hadley/Martin | 0.7% | 11.4% | 48.3% | +12000 |
| McNealy/Bramlett | 0.7% | 11.6% | 48.0% | +8000 |
| McDowell/Wallace | 0.7% | 11.0% | 47.5% | +5500 |
| Hojgaard/Taylor | 0.6% | 9.7% | 45.0% | +12000 |
| Spaun/Jones | 0.6% | 9.9% | 45.0% | +10000 |
| Snedeker/Mitchell | 0.6% | 8.3% | 42.5% | +8000 |
| Hubbard/Cappelen | 0.5% | 7.8% | 41.4% | +21000 |
| Landry/Cook | 0.5% | 8.9% | 44.3% | +15000 |
| Merritt/Streb | 0.5% | 8.9% | 43.8% | +15000 |
| Hoffman/Watney | 0.5% | 6.3% | 38.8% | +6000 |
| Zhang/Pan | 0.5% | 8.0% | 42.4% | +15000 |
There are two co-favorites this week with Jon Rahm and Ryan Palmer -- the defending champions -- and Xander Schauffele and Patrick Cantlay both at +700 on FanDuel Sportsbook. Both teams rate well in my win simulations:
Both teams are pretty comparable with their statistical profiles and driving archetypes, but Xander and Cantlay rate out better there. They're a fair bet at +700.
The model is not particularly keen on the other golfers listed near the top of the board until we get to Max Homa and Talor Gooch at +3100. Both golfers are quite similar overall and off the tee, which should allow them to play their games together without massive alterations.
That said, I do like the Bubba Watson and Scottie Scheffler overlap at +1400.
Teams with longer odds that look promising based on the model and/or the team fit include Jason Kokrak and Pat Perez (+6500), Doc Redman and Sam Ryder (+10000), and Matthew NeSmith and Chase Seiffert (+10000), and Brice Garnett and Scott Stallings (+15000).
I have honed in on Schauffele/Cantlay, Watson/Scheffler, Homa/Gooch, Kokrak/Perez, NeSmith/Seiffert, and Redman/Ryder.