If you’re like me, you may have wondered about why the baseball book, Moneyball, profiled a baseball team that did not win the World Series in any of the seasons that took place in the book. Originally written by Michael Lewis, Moneyball chronicles the Oakland Athletics during the time period from roughly 2000-2003, when the Yankees, Diamondbacks, Angels, and Florida Marlins all took home World Series victories. I’m as big a proponent as any about the pioneering ways of the small-market A’s in those seasons, and the use of advanced analytics in baseball, but I’ve always found it interesting the book and movie were such wild successes when the teams never actually won it all. The Diamondbacks, Angels, and Marlins all could have fit a similar profile as the A’s during those seasons – smaller payroll organizations, built around pitching and defense who got hot at the right time and won baseball’s playoff tournament. But the A’s were chosen for the book because of the unique ways they were evaluating players and doing so on this shoestring budget, to make the playoffs all four seasons and outduel the larger market teams.
So, why should you care about Moneyball and DFS? Because just like it’s really hard to win a World Series, it’s really hard to win a DFS tournament with thousands and thousands of entries. You need a process, you need to be different, and you also need a heck of a lot of luck. And yet, even without winning a World Series title, it’s not as if other MLB teams could not recognize the innovative ways the A’s were approaching baseball management, and adapt them to sustain success in the future. In the immediate years that followed, almost every team boosted their analytics department with headcount after headcount to follow suit on an A’s team that had sustained winning during the regular season even without any trophies coming home.
I hope you can see the parallels here. Just because you may not be seeing the results you want to see in one-game or one-week sample sizes, it does not mean your approach needs to be overhauled. Assessing your process is a critical factor in DFS success. But be careful not to overthink it. Luck is a real element of success in this world. Name your field and we’ll cite how and where luck plays a part. NFL DFS success is not all about luck. No way. But on any given slate, there’s a variance (luck) factor present, and we have to accept it and determine whether we had faults in our process or sometimes just not enough luck.
The Tampa Bay Rays eventually caught on to the Oakland Athletics outside-the-box thinking. They adopted the high on-base percentage hitters, and the high spin-rate pitchers, and saw much more success than the A’s in the years that followed: losing in two World Series finals in 2008 and 2020. They’ve also pioneered new strategies such as using an opening pitcher, one of their best relievers, in the first inning after much of the data showed the first inning as one of the highest-scoring innings in a given MLB game. As we head into Week 13 of the NFL season, try to be the Tampa Bay Rays. Don’t ditch the “hasn’t worked” and “never will” processes you’ve already established. Instead, build upon these foundations and try slight new changes in your DFS approach.
For me, while I’ve constantly been honing in on game overstacks, I’m going to approach Week 13 with less correlation in my lineups, to build for higher upside. It’s going to require me to get a lot more mini-stacks and floating plays right (more guessing, which I hate), but with how common stacking is across the field, it may be crazy enough to work. So what happened in Week 12 and how did we miss it?
What a world we live in, when a running back who was cut from the Jacksonville Jaguars goes up against the #2 DVOA defense against the run and puts up 47 DK points. The first learning here is one size does not fit all. Sometimes, we can take DVOA metrics and throw them out the window. Sometimes, we can play according to these metrics. There isn’t one correct approach, but on Sunday there was just one Leonard Fourtuddys. There was really only one way you could have gotten onto Fournette. Your story would have been the Bucs scoring points, and it coming on the ground, leveraging the higher-owned Bucs pass-catchers (Godwin, Gronk, Evans) along with QB Tom Brady. The probability of this scenario playing out this way was absolutely higher than Lenny’s sub-5% ownership in most tournaments, so there’s your justification for playing Fournette (similar to Jonathan Taylor, two weeks ago) in large-field GPPs.
The real lesson here, however, is to continue to avoid analysis paralysis. We don’t need to go four, five, six layers deep to ‘uncover’ why a player is a great play. There literally was not an advanced statistic around last week dictating why Lenny Fournette should be on your rosters in this game. We didn’t have to look into elusive rating, and gash rate, and yards after contact for us to get comfortable landing on Uncle Lenny. Instead, we could have said it’s possible the Bucs score on the ground, he provides leverage off Gronk and Godwin, and the current narrative around him is Brady isn’t trusting him (see video circulating last week of Brady telling Fournette the coverage as he fakes a handoff) and Ronald Jones may get work (hah). That’s all we need to land here. Keep this in mind for Week 13.
All three of these guys went nuclear on Sunday. Mixon benefitted from a reeling defense in the Pittsburgh Steelers, who just came off allowing a career game to Austin Ekeler, and a dominant performance from D’Andre Swift. Mixon scored early, then the game script just fell into his lap and he was able to take the Bengals on his back and carry them to a W.
Patterson’s low ownership was likely due to his questionable playing status heading into Sunday. It seems every week on Sunday morning, I fail to react to late-breaking news on a player who I should more seriously consider (I made up for this later Sunday with AJ Dillon, alas it was not enough). The Falcons are devoid of any real offensive threats, so if/when he was ruled in with a matchup versus the lowly Jaguars, at his $6500 price tag, he should have been more in play.
Finally, Elijah Mitchell. We’ve seen his tremendous yards per carry, and how he has shown he’s clearly the 49ers best running back this season. The knock on him was A) he doesn’t catch passes so he’s game script dependent (he did, however, have a five target game just two weeks prior), and B) he had two injuries nagging him into Sunday (finger and ribs). We heard all weekend about the Vikings being down all four defensive starters from the first game of the season for this game so Mitchell being in there, plus the lack of talent on the defensive line for MIN, and adding in Kittle and Juszczyk leading the way as blockers, made Mitchell’s setup logically sound. Side note: I’m kicking myself for the Kittle call this past weekend. He was in a perfect leverage spot with the ownership surrounding others around him, but I should have recognized the run-heavy game script with the injuries to the Vikings defensive line, and the propensity the 49ers have shown to ignore Kittle in the passing game when he can be just as impactful as a blocking TE.
“Waddle is a low aDOT WR.”
“His upside is limited based on the role Miami uses him in.”
“His QB stinks, Miami is going nowhere.”
These were all statements made in the DFS industry regarding Jaylen Waddle this week. And then he had the last laugh with his 9/137/1 performance on Sunday. Nine targets, 65 yards. Ten targets, 63 yards. 13 targets, 70 yards. These are real Waddle box scores from earlier this season. So, while Carolina coach Matt Rhule deserves credit here for allowing Stephon Gilmore to also spend time on Mike Gesicki this week, Waddle took the narratives around him and changed them in an instant with this performance. He was buoyed by a long 57-yard catch, of course, but his recent target counts of 9, 6, 10, 11, and 13 showed his floor was there at only $5,900 on DK, and his role as the featured WR, albeit in one of the slower games on the slate, should have been recognized.