Gdula's Golf Simulations and Betting Picks: The RSM Classic

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 adjust for course fit easily. 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 RSM Classic, according to the models, as well as their FanDuel Sportsbook win odds.

Golfer FanDuel
Salary Win% Top-
10% Made
Cut% FanDuel
Odds Louis Oosthuizen$11,7005.7%29.2%74.8%+2500 Cameron Smith$11,8004.6%26.5%72.7%+1700 Scottie Scheffler$12,0004.6%26.8%73.0%+1400 Corey Conners$11,5004.3%26.1%72.4%+2700 Webb Simpson$11,9004.0%24.2%71.5%+1400 Harris English$11,4002.2%17.8%66.0%+3000 Alex Noren$10,8002.1%15.1%62.7%+3600 Russell Henley$11,3002.1%17.7%65.6%+2700 Talor Gooch$11,0002.0%16.0%63.8%+3800 Joaquin Niemann$11,1001.8%15.4%63.5%+3100 Adam Scott$10,9001.7%13.8%61.9%+3600 Brendon Todd$10,4001.6%13.0%60.0%+6000 Chris Kirk$9,8001.5%13.1%60.1%+6500 Taylor Moore$8,7001.5%12.6%60.1%+12000 Brian Harman$9,8001.5%12.7%59.8%+6500 Keegan Bradley$10,5001.5%12.9%60.6%+6500 Kevin Streelman$9,7001.5%12.0%59.1%+9000 Max Homa$10,3001.4%12.1%58.7%+7000 Seamus Power$9,9001.3%12.5%59.7%+5500 Joel Dahmen$10,1001.3%11.5%57.6%+6500 Alex Smalley$9,1001.2%10.6%56.6%+10000 Jhonattan Vegas$10,2001.1%10.6%57.3%+7500 Justin Rose$10,6001.1%11.2%57.3%+5000 Lanto Griffin$9,2001.1%9.0%54.8%+9000 Chad Ramey$8,6001.0%10.4%57.2%+12000 Mackenzie Hughes$10,0000.9%10.3%57.2%+6500 Branden Grace$9,0000.9%8.8%53.3%+7500 Charles Howell III$9,7000.9%10.3%55.4%+7500 Emiliano Grillo$9,0000.9%9.3%54.9%+12000 Chez Reavie$8,6000.8%8.6%53.4%+12000 Michael Thompson$8,1000.8%8.8%53.8%+14000 Lucas Glover$8,5000.8%8.9%53.8%+12000 Matt Jones$8,4000.8%8.4%53.5%+14000 Adam Hadwin$8,9000.8%8.6%53.6%+14000 Troy Merritt$8,9000.8%9.4%54.7%+9000 Mito Pereira$9,9000.8%9.2%54.7%+6500 Doug Ghim$8,6000.8%8.8%54.0%+14000 Stewart Cink$8,1000.8%7.7%51.9%+14000 Stephan Jaeger$8,0000.8%8.2%52.8%+17000 Patton Kizzire$8,5000.8%8.0%52.4%+14000 Cameron Davis$8,3000.7%7.6%50.8%+14000 Tom Hoge$8,4000.7%8.5%53.4%+12000 Kyle Stanley$8,2000.7%7.6%52.0%+14000 Luke List$9,3000.7%9.5%55.3%+7500 Matt Kuchar$9,6000.7%8.1%52.8%+7500 Brendan Steele$8,7000.7%8.0%52.3%+12000 Matthias Schwab$9,0000.7%8.0%53.1%+12000 Robert Streb$9,4000.7%7.4%50.7%+7500 Sebastian Munoz$8,9000.7%7.1%50.6%+12000 Aaron Rai$9,1000.7%8.0%52.8%+10000 Jason Day$9,4000.7%7.7%52.0%+9000 Hank Lebioda$7,9000.6%6.7%50.6%+10000 Patrick Rodgers$9,5000.6%7.0%50.8%+7500 Brian Stuard$8,3000.6%7.1%50.5%+12000 Denny McCarthy$8,6000.6%7.4%51.4%+9000 Russell Knox$8,1000.6%7.3%51.0%+14000 Harry Higgs$8,2000.6%7.1%50.4%+14000 Danny Lee$9,6000.6%6.7%50.0%+6500 Matt Wallace$9,5000.6%6.2%48.7%+7500 Henrik Norlander$8,8000.6%6.5%48.4%+9000 Adam Long$9,3000.5%7.1%50.3%+9000 Keith Mitchell$8,5000.5%6.5%49.2%+9000 Adam Svensson$7,0000.5%6.0%47.5%+34000 Andrew Putnam$7,8000.5%6.7%50.3%+17000 Zach Johnson$8,4000.5%5.9%48.4%+14000 Brice Garnett$7,8000.5%5.8%48.2%+17000 Kevin Kisner$10,7000.5%7.3%49.7%+3000 Kramer Hickok$7,8000.5%6.3%48.2%+12000 Brandt Snedeker$7,5000.5%5.3%46.2%+23000 Vincent Whaley$7,9000.5%6.6%49.4%+17000

There's a ton of value on Louis Oosthuizen (+2500), according to my model, which would view Louis at closer to +1600 if setting the odds. I've already made sure to bet him in case the odds shortened from here.

With a lot of positive expected value on Oosthuizen, the model views a few others at the top as overvalued. That doesn't apply to Corey Conners (+2700), whose simulated win odds imply +2200 territory.

From there, though, we have to skip down a good bit to find positive or even value. We get it with Brendon Todd (+6000), Chris Kirk (+6500), Brian Harman (+6500), Keegan Bradley (+6500), and Max Homa (+7000).

I've already bet Todd, as well. He should benefit from an accuracy-friendly course that features bermuda greens.

I also went with Homa despite not being the most ideal course fit; he's just too good to gloss over at that number.

Taylor Moore (+12000) has great adjusted data and stands out as a long shot option, though I'm more inclined just to stick with a top-10 or top-20 on a golfer with odds quite that long, personally. The same can be said for Kevin Streelman (+9000) and Alex Smalley (+10000). However, I might break that rule for Moore and bet him outright anyway.