NBA Postseason Best Bets (5/14)
Alex Christenson
In PGA DFS, the landscape is a bit different from its NFL counterpart. Unlike the gridiron battles where individual player performances can significantly impact each other, golf is a solitary pursuit. What one player does cannot help, nor prevent, another from doing the same on the PGA ownership review for the WM Open.
In PGA DFS, the landscape is a bit different from its NFL counterpart. Unlike the gridiron battles where individual player performances can significantly impact each other, golf is a solitary pursuit. What one player does cannot help, nor prevent, another from doing the same on the course. In other words, the correlation that plays an enormous role in other DFS sports like NFL and MLB is almost entirely absent from PGA. This fundamental difference magnifies the importance of game theory – it’s arguably all we have. Well, if game theory is all we have, then we’d better be using the best ownership projections.
Now three weeks into this article, it sure looks like we do! We’ve magnified this advantage by introducing our new GPP scores, which have resulted in back-to-back weeks of tremendous success. As you’ll see, Cam Young serves as a great example of both our ownership creating an edge, and how the GPP scores make intuitive sense.
Key Differences from the Industry
How much does ownership really matter? This is a question often discussed in our industry, so allow me to take a stab at answering it. I believe ownership matters only a little bit, until it matters a ton. More specifically, small differences in ownership from one source to another is close to meaningless (like 12% vs. 13%). Large differences, however, are enormously important, in large part because they affect the decisions we actually make on who to play or fade.
It therefore makes sense to look at the instances where our ownership projection deviated most from the industry average and compare those projections to the actual ownerships observed in contests.
All actual ownership percentages for this section will come from the large $12 Single-Entry contest. This tournament is large enough to represent the entire field of DFS players, yet the single-entry aspect makes it more about the psychology of clicking on each individual player as opposed to what an optimizer spits out.
Our three largest differences were:
Cameron Young
Industry: 12.3%
FTN: 5.4%
Actual: 4.6%
Beau Hossler
Industry: 11.8%
FTN: 17.7%
Actual: 19.8%
Si Woo Kim
Industry: 12.4%
FTN: 16.9%
Actual: 16.7%
It’s great to see that once again, we nailed the ownerships on the guys we were most different from the industry on. Cameron Young was a true difference maker in the sense that not only were we right about him being so contrarian, but he also finished 8th in the event. The GPP scores are extremely sensitive to ownership, so his was great since we accurately projected him to be so contrarian.
Accuracy Analysis
We can compare overall accuracy by looking at r-squared and RMSE. For those unfamiliar with these metrics, you can focus on just r-squared. If we were exactly right about every single player’s ownership, to the exact decimal place, our r-squared would be 100%. The closer to 100%, the better. The lower the RMSE, the better.
Many of you probably already know the drill by now — the advantage is largest in the contests with the most hand-building, like the small $200 SE. We can talk about ownership advantages all day long, but it only matters if we can use that to produce real results. For the second straight week, I was able to do just that, with this SE lineup:
Scottie Scheffler and Adam Scott had the two highest GPP scores. I chose to stack the late Thursday wave or else I also would have had Sahith Theegala, whose GPP score was third overall.
I believe that ownership matters more in PGA than any other sport because the player outcomes are more volatile than in any other. Winning GPPs in PGA DFS is as much about taking advantage of the weeks where chalk fails as it is about hitting on all of your plays. The GPP Scores do an excellent job of showing you which of the chalky plays have the best chance of failing. Scottie Scheffler only had a 9% chance of missing the cut in our simulations, but a near 45% chance of finishing top five. Hence, his GPP score was through the roof while Justin Thomas’ was the worst on the slate (I know that will ruffle some feathers). We had Thomas more likely to miss the cut than finish top 5. He did neither, which is why the decision to play him or fade him turned out to be not-so-important… which is the other side of the low GPP score coin. He was also a good fade because he was unlikely to hurt you if you faded him, so it was worth taking a chance both on somebody else and on the possibility that he could sink 40% of others’ lineups.
