I’ve been playing golf DFS for about 7 years. In the beginning, like most, I was trying to perfectly predict what would happen on the course. “This golfer is going to shoot well on this course on this specific day because this particular model or data point is telling me so.” Only to check the scores the following day to see my golfer carded a 3 over 75, at 25% ownership, sinking all of my showdown rosters for that slate.
It took some time, but I finally realized that predicting golf is incredibly difficult. As an avid golfer myself, I understand on a basic level how variable golf can be from day to day. One day I’m striping it, thinking I’ll never hit a bad shot again. The next, I’m standing over the ball wondering if I’ll be able to keep it in play. In many ways, I think we as DFS players can relate to the unpredictable nature of golf. In both games, you must always be striving for improvement amidst the constant up and downs
PGA Showdown Strategy (Range Of Outcomes)
While pro golfers may not have as drastic swings from day to day as I do, there is a natural range of outcomes that every golfer has when they tee it up. It wasn’t until I understood this fact, and began incorporating it into my research, that I started seeing some nice success in PGA Showdown.
My first PGA showdown win from round 3 of the 2022 BMW Championship.
Golf, as I touched on above, presents a unique challenge in DFS due to its inherent unpredictability. Despite the advancements in projection models, accurately forecasting golfer performance remains a daunting task. To illustrate this, I created a simple monte carlo simulation within excel. This simulation is designed to demonstrate the inherent randomness that exists for every professional golfer from round to round, regardless of skill level.
For the sake of this demonstration, I gave this golfer an average round score of 70, and a standard deviation of 3. These figures are about what you could expect from an average PGA TOUR professional. I ran the simulations for 100 total rounds, which is approximately the number of rounds a pro golfer will play over the course of a full PGA Tour season. It isn’t a perfect example given the sample size issues, and the additional nuances to each golfer that need to be taken into account. However, the demonstration will help paint the picture.
As you can see, roughly 36% of rounds fell within 2 strokes of the average score of 70. Projection models will heavily favor this outcome, as it is the scenario that is most likely to occur. However, that still leaves 64% of rounds that will fall outside of this range. Let’s take an even more in depth look at the individual simulation runs to see just how much scores can differ from round to round, and still be considered within the reasonable range of outcomes.
Above, we are viewing the first four rounds out of the 100 total round simulation sample I built. In this example, our golfer fired an opening round 66, good for 6 under par. At most courses, that would likely put them in the top 10 after round 1.
Here in lies the crux of PGA Showdown game theory, which is particularly evident as tournaments progress. While opening round ownership projections offer some semblance of predictability given their pre-tournament nature, subsequent rounds feature a shift in dynamics. A golfer may, like in our example above, shoot an unexpected low score and therefore garner additional ownership in round two.
PGA Showdown Game Theory – PGA DFS ‘Desire For Certainty’
There is a cognitive bias rooted in our innate desire for certainty, that often leads to inflated ownership on players coming off of a well-played round. For many, seeing something happen once leads to more certainty of it happening again in the future. However, seasoned DFS players understand the transient nature of golf performance, and set aside the temptation to overvalue data points from a single round. Sticking mostly to our pre-tournament evaluations on players is key to staying ahead of the curve, and on the sharp side of ownership in showdown style formats.
This is not to say that you should be auto fading any player who scored well in prior rounds. However, you need to be aware of what those successful rounds will do to their popularity amongst the field. Being able to make a decision on if that player’s baseline skillset warrants the impending ownership bump that will likely occur is a key decision point.
This very same thinking can be used in the inverse. In my approach to showdown slates, I start my research by identifying the golfers that are going overlooked by the field based on the one or two round sample size of lackluster play. I always start with Stokastic’s PGA showdown ownership projections, which provide a nice overview of the upcoming slate.
If I liked a golfer before the tournament, and he’s projecting for single digit ownership based off a couple of poor rounds, I will always take a shot on variance catching up. To illustrate, let’s take a look at this three round sample from the same simulation as above.
In this example, this golfer would have likely just snuck through the cut after the first two rounds. Given he’s an average player, coming off of two poor rounds, he’s unlikely to garner much attention for round three showdown. This would be a situation that would pique my interest assuming I liked the underlying metrics on this golfer before the tournament began. A spiked round is still well within this player’s range of outcomes, as evidenced by the third round 65 in the simulation. At single digit ownership, this is the type of play that wins you all the money.
Keep in mind, as with most profitable DFS tournament rosters, you’ll want to be balancing the “best” plays with some of these more under the radar plays. You don’t want to be constantly chasing these lower probability outcomes across your entire roster. Sprinkling them in conjunction with some of the more ‘solid’ plays on the slate is a nice recipe for success in DFS showdown.
I believe PGA Showdown presents one of the biggest edges available within the current DFS ecosystem. The often times predictable, and sub-optimal, behavior from our competition provides the opportunity to swing variance in our favor. You’ll never be able to accurately predict which golfers will go low on a given day, but by constantly putting yourself on the correct side of the probabilities, eventually the perfect lineup will come together.
Stokastic’s PGA Sims tool does a lot of that work for you. With each golfer being put through rigorous hole-by-hole simulations thousands of times, you’ll be able to uncover spots the field is overlooking. See both full lineup and individual player level advanced statistics like Simulated ROI%, Win %, and Projected Ownership Sum. Powered by Stokastic’s hole by hole simulation technology, it’s the best DFS Golf simulation tool on the market.
Good luck this season on your PGA Showdown contests, and I hope to see you all at the top of the leaderboards this PGA season.
