If you’ve played daily fantasy football for any extended length of time, you’ve learned by now there isn’t a single magic button you can push to guarantee sustained success. Instead, you have to work hard to get better -- at a lot of things -- to become a profitable player over the long term.
The “things” I’ve personally had to work hardest at to improve as a DFS player involve game theory. Bankroll management, intelligent game selection, and projecting outcomes in terms of probability don’t come easy to me because they require discipline and restraint (neither of which are any fun).
If you’re looking for advice on how to become a better game theorist, I’m sorry to report you’ve clicked on the wrong link. Consciously working to improve those skills made a huge difference in my results last season, but at this point I’m admittedly still more of a buyer than a seller when it comes to guidance on the science of logical decision making in human beings.
Fortunately (for you, my bankroll, and the good folks paying me to write this article), there is another component to winning DFS strategy. The best players are able to blend their knowledge of game theory with sharp instincts and good old fashioned statistical research -- a pair of traits that are more interwoven than you might think. When you know which stats are most important to analyze -- and how to get your hands on them quickly and easily -- it’s funny how your “instincts” suddenly appear quite sharp.
So how does one get their hands on the most relevant stats quickly and easily?
The answer is by using the stat tools included with a Footballguys subscription. But before you blast me for being an unapologetic shill, you don’t have to take my word for it. I’m going to show you it’s true, then you can try it for yourself and decide whether or not I’m a snake oil salesman.
Before I get to the part where I show off my favorite Footballguys stat tool -- the Data Dominator -- allow me to frame its usefulness for DFS purposes:
It was Week 10 last season, and as usual I was searching for running back value on DraftKings. To this point in the season, Jonathan Stewart had been mostly injured or ineffective, but he came out of the Panthers Week 5 bye looking healthy. Stewart had strung together four straight games with 20+ carries and had been on the field for 72% of Carolina’s offensive snaps over that span.
Quick side note -- this would be a good time to point out opportunity stats rule the day for running backs (and all other offensive positions besides quarterback) in DFS. 4for4 senior DFS editor, Chris Raybon, published some fantastic work ahead of last season that showed snaps and total touches were essentially just as highly correlated to running back fantasy scoring as total touchdowns and rushing yards. And back in March, Pro Football Focus’ Scott Barrett tweeted 2015 correlation data for running back fantasy scoring that showed opportunity was every bit as important last season as it had been in 2014:
Pulled every RB game from 2015 for an article I'm working on. Here's how some different stats correlate with FP. pic.twitter.com/3iO9TlnkKX— Scott Barrett (@DudeFantasyBro) March 10, 2016
Footballguys makes it easy to determine a player’s snap count each week by viewing the summaries on each NFL team’s page. Total touches over any time period are easily calculated using Historical Stats, which even include filters for Fanduel and DraftKings scoring formats. But as great as those tools are, they’re not the stars of today’s show. Back to how the Data Dominator pointed me in Stewart’s direction back in Week 10…
While Stewart was dominating the work in Carolina’s backfield and performing as a back-end RB1 for fantasy, DraftKings pricing algorithm hadn’t taken notice. Stewart’s $3,900 Week 6 salary had only risen to $4,300 despite the fact he had reached at least a 3x salary multiplier in three of the last four games. He was cheap (RB25), getting more carries over the last four weeks than any running back besides Adrian Peterson (hat tip once again to Historical Stats), and destined to be low-owned since he was coming off a 7.8 point dud in Week 9. All signs pointed towards Stewart being a solid contrarian play in a matchup with Tennessee’s very-bad rush defense. The only reason to hesitate was the prevailing narrative that Stewart’s touchdown upside was capped due to Cam Newton vulturing his goal line carries.
Watch how the Data Dominator allowed me to cut against that narrative and enjoy a solid 15.1 point game from Stewart (3.5x salary multiplier) at 2% ownership in the Week 10 Millionaire Maker:
Did 91 rushing yards and a touchdown from Stewart single-handedly win me a GPP in Week 10? Sadly, the answer is no. But getting a 3.5x return on salary from a cheap, scarcely-owned RB2 could certainly have been one piece of the optimal roster construction that week. For the sake of full disclosure, Stewart’s touchdown came from 16 yards out, while Cam Newton did in fact score on a two yard run in the fourth quarter of the Panthers Week 10 win over the Titans. But Stewart received two carries from inside the five yard line during the game, which tells me the Data Dominator was right to get me thinking in a different direction than 98% of the field with regards to Stewart's scoring potential.
The Data Dominator is such a powerful tool I’m afraid this simple example hardly does it justice. I could spill a bunch more digital ink listing use cases to show how the Dominator can help improve your DFS research, but the best way would be for you to get your hands on it and try it out for yourself. If you're reading this then you're an Insider Pro subscriber and the Data Dominator is all yours. Go ahead, give it a shot, and please reach out to me on Twitter. I’d love to hear more ideas on how we can use this tool to gain an edge in DFS research.