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The best DFS stacks & blowup targets for wild-card weekend

Cincinnati Bengals wide receiver Tee Higgins (85) comes down with a touchdown reception ahead of coverage from Baltimore Ravens safety Ar'Darius Washington (29) in the fourth quarter of the NFL Week 16 game between the Cincinnati Bengals and the Baltimore Ravens at Paul Brown Stadium in downtown Cincinnati on Sunday, Dec. 26, 2021. The Bengals improved to 9-6 on the season with a 41-21 win over the Ravens. Baltimore Ravens At Cincinnati Bengals Week 16

Small slate DFS requires a completely different approach than the traditional regular season main slate with around 10 different game options. The DFS sites broke up the wild card round into featured slates and also provided a three-day structure with all six games.

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The various DFS models in this article will have applications and plays for any of the sites that span the weekend contests. On shorter slates, don’t be afraid to press on the game stack, with the expectation that identifying the right game provides value when it far outshines the others. 


One of the best ways to find value opportunities on a given slate is to start with the salary-adjusted expectation for all players. We have a worthwhile dataset of player salaries and their resulting fantasy performances for DraftKings since it has been around for over six years. By figuring out the expectation based on each player’s salary and position, we can compare their salary-expected fantasy performance to PFF’s fantasy projections. Doing this highlights the best value plays based on salary.

Player Position Team DK Salary Salary Expectation Proj. Fantasy Pts Proj. Above Salary Expectation
Leonard Fournette HB TB 5900 12.96 17.91 4.95
Tyler Johnson WR TB 4000 6.96 11.55 4.59
Cooper Kupp WR LA 9000 22.69 26.92 4.23
Jakobi Meyers WR NE 4500 8.53 12.74 4.21
Antoine Wesley WR ARZ 3300 4.75 8.47 3.72
Odell Beckham Jr. WR LA 5100 10.42 14.07 3.65
Tee Higgins WR CIN 6300 14.20 17.77 3.57
C.J. Uzomah TE CIN 3200 5.11 8.63 3.52
Tyler Boyd WR CIN 5000 10.10 13.14 3.04
Emmanuel Sanders WR BUF 4000 6.96 9.92 2.96
Brandon Aiyuk WR SF 5400 11.36 13.96 2.60
Hunter Henry TE NE 3700 6.68 9.21 2.53
Ja'Marr Chase WR CIN 7400 17.66 20.14 2.48
Cole Beasley WR BUF 4300 7.90 10.24 2.34
DeVonta Smith WR PHI 5500 11.68 14.02 2.34


Utilizing specific variables, we can build a model tuned to predict performances where a pass-catcher goes over a certain site-specific scoring threshold. For DraftKings, this is set at 25 fantasy points.

This model provides the percentage chance each receiver will meet or exceed our fantasy-point threshold for the site given their historical opportunity. The model won’t be right on every player, but it is useful in identifying the blow-up performances we want to unearth in our DFS lineups.

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