GOLF

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

What do thousands of simulations tell us about betting value for this week's PGA Tour event, 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
Sportsbook
Win
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.