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In my first non-event-driven blog post, I wanted to share insights uncovered in researching which skills drive DFS scoring.
There’s an intrinsic belief that you look for ball-strikers to find players who produce high scores in daily fantasy sports. “Can this guy create the most opportunities and jump up the leaderboard?” A novel thought, this data provides us with a simpler answer to the question of who can outscore their finishing position.
Finding players who outscore their final leaderboard position is key to success, as DFS scoring does not naturally follow the leaderboard – it is another game in itself. This is what we mean when we say a guy “scores well”.
A player with 2 pars will lose 1.5 DraftKings (DK) points to a player with 1 birdie and 1 bogey as the players share a leaderboard spot at even par.
A player with 8 pars and 1 birdie (7 DK points) in an outward 9 will lose 7 DK points to a player with an eagle, 2 birdies, 3 bogies and 3 pars (14 DK points). Both will finish 1 under par.
Then comes the 3-streak bonus points that only come if you can make those birdies.
That is the margin in some DraftKings contests between 1st and 5th, $50,000 and $15,000.
As most strokes-gained stats, DFS breakdowns, and course history analyses look exclusively at raw score or relative strokes-gained that are not 1:1 with DFS scoring, it begs the question: are we evaluating the right metrics when projected DraftKings scoring?
Plus4: A view into what drives DFS scoring
We will look at driving distance, driving accuracy, and the 4 strokes-gained stats to show your 4heads who you should be playing in DFS when struggling to comp the course, limiting a player pool, or stuck in that testy 1v1 situation when building.
Difference in expected fantasy points (Δ exp. FP)
The Y-axis in all of the skill-based plots below will be each player’s average over-performance or under-performance of their finishing leaderboard position in relation to the expected fantasy points of that finish spot.
We take each event since 2021, plot the finishing positions and hole scoring, streaks, and bonus point fantasy points (excludes finishing position points and hole-in-one points), create a line of best fit, and then evaluate who over-performed and who under-performed in DraftKings scoring based on their leaderboard spot.
Do that 250 times over, and it’s a great sample.
Below is the plotting for the 2025 Masters Tournament
Rory… a true maniac with all those eagles and double bogies. Reed’s late eagle pushed him well over that fit-line.
Driving distance
Without a doubt, driving distance is the number 1 attribute that drives higher scoring. For every 5 yards of distance, a player projects to outscore their final leaderboard position by almost a full point.
This is why you play bombers in PGA DFS. Distance leads to better eagle opportunities, which drives a ton of scoring differential.
Driving accuracy
On the contrary, guys who lean on driving accuracy significantly underscore their leaderboard position.
This is not solely due to old guys being both more accurate and conversative. Playing from the middle of the fairway is a benefit, but it limits that variance we actually seek out in DFS.
SG: Off-the-tee
Off-the-tee skill is, of the 4 SG categories, the largest contributor to DFS scoring boosts. Given the upward trend (but not as upward as distance), we can see that driving distance is a much higher factor in OTT play than accuracy.
SG: Approach
This is where conventional wisdom gets tested.
It seems to be common belief that approach skill leads to the birdie opportunities that drive DFS scoring – while true, the factor here is substantially less than distance and almost negligible.
SG: Around-the-green
If you miss greens, you can’t score. It’s that simple.
The guys missing greens and making par are not valuable in DFS when bombers with exciting scorecards are the same price.
SG: Putting
While our most variant strokes-gained stat in a given round, overall putting skill is actually a large component of DFS scoring advantage – almost to the same degree as approach.
Those who can roll it hot can capitalize on those birdie chances and get on a roll of circles.
Analysis of top 50 players
For those who want to see the top 50 players in the world (per datagolf.com), this plots each of the players. Notes:
- Bryson and Rory score the shit out of the golf ball, but not far behind are these variant guys like JT, Cam Smith, Viktor, and the Spanish wonderkid David Puig.
- JT and Cam specifically can get very hot with the putter and, despite top 10 short games, produce some very fun scorecards and higher DK scores.
- At the bottom are guys like Denny, Aaron Rai, Ryo Hisatsune, and Tommy Fleetwood. What do these have in common? Shorter players who rely on driving accuracy and short game. If you are playing these guys, know that they need a high finish to create that floor of DK points.
Plus4: Conclusion
Simply, you should be playing bombers when you get the chance. Guys that spray it and create shorter looks at birdies and eagles create the scoring differential you need over 72 holes of a DFS tournament.
You may be thinking, naturally better players will outscore their finishing leaderboard position—making birdies and eagles is in itself evidence of higher skill. But importantly, these figures all hold true even when we filter our pool to those players who have negative true total strokes gained… i.e. the bad or middling TOUR professionals fighting for cards.
This gives credence to playing the young, strappy bombers that come from school or the lower tours—these guys may be more variant in their leaderboard finishes than the Ben Martins and Greyson Siggs of Earth, but when they hit a good finish, their DK scoring will be even better.
We can use these tools with confidence when building our player pools and, specifically, when evaluating the guys below $7,000 in DraftKings that we need to score well in a given week. Those low-end players are not likely to finish top 10, or even top 20, on the leaderboard, but… when they finish tied for 24th on the leaderboard… they finish 15th in what we really care about, the DraftKings board!
A note on vibe-coding in ChatGPT
ChatGPT was heavily used in the creation of the regression modeling, but not in the writing of this report.
It’s incredible what you can do with this technology in a coding and development space. I have experience in Python, I have a ton of experience using the DataGolf APIs, and I’m great in Power BI – this project would have taken 20 to 30 hours of manpower to complete 3 years ago, researching libraries, testing, debugging, and delivering. With ChatGPT, it was done in 3 hours with 300 lines of code.
Vibe-coding is “an AI-dependent programming practice where a programmer describes a problem in a few sentences as a prompt to a large language model (LLM) tuned for coding.” If you don’t know already, it’s ripping through IT departments and product management at large. If you can make it work for you, you can create almost any small-scale application or analytic you can fathom.
As always, GL GL GL in whatever you are doing.
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