I started playing DFS on DraftStreet in 2013. For the next six years, I primarily played cash games because I was in love with the slow, methodical grind, along with the safety that comes from playing a format where you only have to beat one other person or roughly half the field if you’re in 50/50s or double-ups.
Nowadays, I’ve decided to pull the ripcord on the safety net so that I could seek out more upside.
The hardest part of switching to GPP only? Getting comfortable with losing … a lot more often. However, with proper game selection and bankroll management, all you need is one or two nice scores to be in the black when the season ends.
And when you’re mainly targeting small-field GPPs, your lineups don’t need to be as perfect compared to when you’re entering these larger fields. Personally, I consider a small field as a tournament with 500 or fewer people, but some DFS players may have a broader definition.
And typically, I am playing in tournaments with 300 or fewer people.
Anyway, each week I’ll be using our extensive suite of analytical fantasy tools and the FantasyLabs Player Models to discuss my overall strategy for how I’m attacking these smaller fields.
Additionally, our Lineup Builder is the perfect tool to use when hand-building your lineups.
General Strategy
My overall strategy for these formats is quite simple. I try to find the best spots to correlate and utilize the Leverage Scores in our Player Models to find pivots off of players who are projected for higher rostership.
A lot of the time, when looking for games to target, you land on high-total games because that’s where we’d expect the most points to be scored. Naturally, high-total games come with higher projected ownership on certain players. However, it’s still possible to have unique builds when targeting these games, and we can still insert other one-off plays to differentiate our lineups.
You don’t need a whole lineup of contrarian plays to win a small-field tournament, though it helps to pivot in the right spots. I also tend to rely on the Ceiling Projections instead of Median Projections when I am making my lineup decisions.
Also, keep in mind the projected ownership levels in the models are geared toward large-field GPPs, so there is some guesswork on estimating ownership projections for smaller fields.
Note: I play these small-field tournaments on DraftKings, so that’s what this analysis will focus on.
Game(s) I’m Targeting
Philadelphia Eagles (26) at. Detroit Lions (22.5)
Jalen Hurts catches a lot of grief for not being a good real-life quarterback from some people, but he fills up the stat sheet for DFS, and that’s all we care about. Hurts has hit salary-based expectations every game this season and is averaging a +4.24 Plus/Minus on DraftKings, giving him a 100% Consistency Rating in our models.
One of the great features of being a FantasyLabs Pro member is that you can apply different weights to our NFL projections from some of our partners (may require separate purchases) to create an aggregate set to your specifications (you can also upload your own):
When I make my preferred inputs, Hurts is second in my Ceiling Projections. This seems like a good spot for Hurts against a Detroit defense that ranks 27th in pass DVOA. Dallas Goedert is my preferred stack option as he played 93% of the snaps with Zach Ertz gone, and Goedert’s 6.4 routes per target led the team in Week 7.
Despite the high ownership projection, I’m still going to use D’Andre Swift as the bring-back option. His 17.1 touches per game ranks sixth in the league, and he leads the entire league in high-value touches (RotoViz). Additionally, Swift is tied with TJ Hockenson for a team-high 20.5% target share. Swift brings the perfect combination of floor and ceiling.
As I mentioned earlier, we don’t need to be contrarian everywhere — but if you wanted to add some contrarian element to this stack — you could run a two-TE team with Hockenson since he and Swift are the focal points of this offense. We currently have Hockenson projected for around 6% rostership, but I think it could be less in smaller fields.
At the time of writing, this is the main stack I am focused on for Week 8 since I am just rolling out a single entry. Come back Sunday for any updates.
One-Off Plays
Usually, these one-off plays are where I am looking to differentiate my roster from everyone else, especially if the stacks I am targeting project to be highly rostered.
My reasoning behind these plays is rather minimalistic — I look at projected ownership and Ceiling Projections. Those two things combined are where we get our Leverage Scores and Ratings.
Our brand new Minimal Tournament Model that’s in our Pro Models is perfect for these plays. It’s a model I created that focuses on three things: Ceiling Projections, Pro Trends, and ownership projections. Keep in mind the plays in this model will fluctuate based on changes in ceiling and ownership projections.
With a lot of people focused on Josh Allen, I don’t mind Zack Moss a cheap pay-down option to leverage off Allen. There is obviously risk in this play since the Bills have one of the lowest rushing rates in the league, but as 17.5-point favorites, I’ll take a shot here with Moss’s 76% Leverage Rating.
Najee Harris is $400 more expensive than Swift and is projecting for about half the rostership. And since you’re not sacrificing much in projections, Harris has one of the best Leverage Scores. Harris currently ranks fifth in the Minimal Tournament Model.
After a few weeks failing as chalk, people are back off Derrick Henry, who is second in the Minimal Tournament Model. Henry is one of the few players who has true slate-breaking potential. His 29.9 touches per game ranks first in the league by over six touches. Tyreek Hill and Henry are two of my favorite players to target when they’re not expected to garner a bunch of rostership.
Michael Pittman doesn’t stand out in Leverage Ratings or Scores, but he’s one of my favorite plays in this range. He fits into any roster build and has a top-15 Ceiling Projection, but he’s priced outside the top 20. Pittman leads the Colts with a 23.5% target share and 36% air yards share.
Cooper Kupp is turning into a big decision point each week. He started the season at $5,500 in Week 1, but now he rocketed to $9,000. He has four games over 30 DraftKings points this year and five over 25. If I can fit him in, I’ll be doing so. He still has a positive Leverage Score in our models.
With Chris Godwin projected for high rostership, two receivers priced around him that are ranking well in the Minimal Tournament Model are Dionte Johnson ($6,700) and Keenan Allen ($6,500). Johnson leads the Steelers with a 29% target share and 38% air yards share, and he saw 13 targets with Juju Smith-Schuster on the shelf.
Allen is a tougher one to decipher because he hasn’t shown much of a ceiling this year. However, he’s still seeing 25% of the Chargers’ target share, and his ownership projections are decreasing every week, making him one of the more intriguing buy-low options.
If we’re running the above Hurts stack with Goedert, we don’t have much use for a one-off TE play, but these are the top five tight ends standing out in the Minimal Tournament Model:
Other One-Off Plays Based on Leverage Scores/Ratings
- Alvin Kamara
- Jonathan Taylor
- Deebo Samuel
- Mike Evans
- Marvin Jones
- Emmanuel Sanders
Sunday Morning Update
I don’t always have an update on Sundays, but sometimes my thoughts change after I write this. Check back Sunday to see if anything has changed.
Not a whole lot has changed for me, even with the Calvin Ridley news. You could use Russell Gage if you needed the salary, but Kyle Pitts is a little harder to get to on DraftKings depending on your build. We were already on Swift, and Jamaal Williams is now out. This brightens Swift’s outlook, but it will raise his rostership.
Hockenson’s rostership could be even lower now.
Players I’ve added to my pool: Kenneth Gainwell, Emmanuel Sanders, Jared Cook.
If you’re struggling to get a feel for the slate, we also have some optimizer templates in our Lineup Optimizer that you can use to see where the raw projections are leaning for stacks:
