Below you can see Stokastic's NFL Boom/Bust Probability Tool for this week's DraftKings and FanDuel slate. This data gives the user an idea how likely a player is to meet their ceiling and floor, relative to their median projections. You're seeing a PREVIEW of our industry-leading NFL DFS data for today's DraftKings slate. The preview does not contain all the data for today's slate. Join for the full list of our NFL DFS booms and busts!
Stokastic's Week 14 NFL DFS Boom-Bust Tool Preview
| Name | Team | Salary | Position | Projection | Std Dev | Ceiling | Floor | Bust% | Boom% | Slate | Own% | Optimal% | Leverage |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Jake Browning | CIN | 5,100 | QB | 13.5 | 5.9 | 17.5 | 9.5 | 48.8 | 0.8 | Monday | |||
| Joe Mixon | CIN | 6,200 | RB | 12.5 | 5.7 | 16.4 | 8.6 | 52.7 | 1.6 | Monday | |||
| Chase Brown | CIN | 4,000 | RB | 0.2 | 0.7 | 0.7 | -0.3 | 100.0 | 0.0 | Monday | |||
| Trayveon Williams | CIN | 4,000 | RB | 1.6 | 2.0 | 3.0 | 0.3 | 99.9 | 0.0 | Monday | |||
| Ja'Marr Chase | CIN | 8,100 | WR | 13.4 | 7.3 | 18.3 | 8.5 | 71.1 | 1.0 | Monday | |||
| Tee Higgins | CIN | 6,300 | WR | 8.8 | 5.8 | 12.7 | 4.9 | 77.5 | 0.1 | Monday | |||
| Tyler Boyd | CIN | 4,200 | WR | 7.1 | 5.2 | 10.6 | 3.6 | 57.3 | 0.4 | Monday | |||
| Trenton Irwin | CIN | 3,000 | WR | 1.8 | 2.4 | 3.4 | 0.1 | 92.1 | 0.0 | Monday | |||
| Andrei Iosivas | CIN | 3,000 | WR | 0.9 | 1.6 | 2.0 | -0.2 | 99.6 | 0.0 | Monday | |||
| Tanner Hudson | CIN | 2,700 | TE | 5.1 | 4.3 | 8.0 | 2.2 | 44.1 | 0.8 | Monday | |||
| Irv Smith Jr. | CIN | 2,500 | TE | 2.2 | 2.5 | 3.9 | 0.5 | 76.2 | 0.0 | Monday | |||
| Drew Sample | CIN | 2,500 | TE | 1.8 | 2.5 | 3.5 | 0.2 | 81.3 | 0.0 | Monday | |||
| Mitchell Wilcox | CIN | 2,500 | TE | 0.2 | 0.8 | 0.8 | -0.3 | 100.0 | 0.0 | Monday | |||
| Evan McPherson | CIN | 6,900 | K | 5.6 | 4.6 | 8.7 | 2.5 | 97.5 | 0.0 | Monday | |||
| Bengals | CIN | 2,600 | DST | 5.5 | 4.8 | 8.7 | 2.3 | 39.7 | 3.5 | Monday | |||
| Jordan Love | GB | 5,800 | QB | 16.5 | 7.0 | 21.2 | 11.7 | 44.0 | 2.7 | Primetime | |||
| AJ Dillon | GB | 5,400 | RB | 11.1 | 5.5 | 14.8 | 7.4 | 48.9 | 1.5 | Primetime | |||
| James Robinson | GB | 0 | RB | 0.9 | 1.6 | 2.0 | -0.2 | -2,146,826,273.0 | 0.0 | Primetime | |||
| Patrick Taylor | GB | 4,000 | RB | 6.3 | 4.0 | 9.0 | 3.6 | 63.1 | 0.0 | Primetime | |||
| Christian Watson | GB | 4,600 | WR | 10.6 | 6.7 | 15.1 | 6.2 | 40.5 | 4.4 | Primetime | |||
| Romeo Doubs | GB | 4,800 | WR | 8.9 | 5.9 | 12.9 | 4.9 | 54.1 | 1.1 | Primetime | |||
| Jayden Reed | GB | 4,400 | WR | 10.2 | 6.6 | 14.6 | 5.7 | 40.4 | 4.3 | Primetime | |||
| Dontayvion Wicks | GB | 3,000 | WR | 5.4 | 4.6 | 8.5 | 2.3 | 48.5 | 0.3 | Primetime | |||
| Malik Heath | GB | 3,000 | WR | 1.4 | 2.2 | 3.0 | -0.1 | 95.3 | 0.0 | Primetime | |||
| Tucker Kraft | GB | 3,000 | TE | 6.7 | 5.2 | 10.2 | 3.2 | 38.7 | 3.4 | Primetime | |||
| Ben Sims | GB | 2,500 | TE | 1.3 | 2.1 | 2.7 | -0.1 | 90.6 | 0.0 | Primetime | |||
| Anders Carlson | GB | 0 | K | 6.1 | 4.5 | 9.2 | 3.1 | -2,146,826,273.0 | 0.0 | Primetime | |||
| Packers | GB | 2,500 | DST | 5.9 | 5.3 | 9.5 | 2.4 | 35.9 | 6.3 | Primetime | |||
| Trevor Lawrence | JAX | 6,600 | QB | 18.5 | 7.3 | 23.5 | 13.6 | 46.2 | 3.0 | Monday | |||
| Travis Etienne Jr. | JAX | 7,000 | RB | 16.8 | 7.2 | 21.6 | 11.9 | 39.2 | 8.0 | Monday | |||
| Tank Bigsby | JAX | 4,000 | RB | 2.0 | 2.4 | 3.6 | 0.3 | 98.9 | 0.0 | Monday | |||
| D'Ernest Johnson | JAX | 4,300 | RB | 5.5 | 3.8 | 8.1 | 3.0 | 77.1 | 0.0 | Monday | |||
| Calvin Ridley | JAX | 6,400 | WR | 13.9 | 7.8 | 19.2 | 8.7 | 47.1 | 5.6 | Monday | |||
| Christian Kirk | JAX | 5,800 | WR | 12.5 | 7.5 | 17.5 | 7.4 | 47.1 | 4.9 | Monday | |||
| Zay Jones | JAX | 3,700 | WR | 7.5 | 5.6 | 11.3 | 3.7 | 45.7 | 1.4 | Monday | |||
| Parker Washington | JAX | 3,000 | WR | 0.3 | 1.1 | 1.1 | -0.4 | 100.0 | 0.0 | Monday | |||
| Tim Jones | JAX | 3,000 | WR | 0.8 | 1.6 | 1.9 | -0.3 | 99.7 | 0.0 | Monday | |||
| Evan Engram | JAX | 4,500 | TE | 12.1 | 7.3 | 17.0 | 7.2 | 32.6 | 14.4 | Monday | |||
| Luke Farrell | JAX | 2,500 | TE | 1.9 | 2.6 | 3.7 | 0.2 | 78.9 | 0.0 | Monday | |||
| Josh Pederson | JAX | 2,500 | TE | 0.7 | 1.7 | 1.8 | -0.4 | 97.5 | 0.0 | Monday | |||
| Brandon McManus | JAX | 7,500 | K | 8.5 | 5.0 | 11.9 | 5.1 | 93.1 | 0.0 | Monday | |||
| Jaguars | JAX | 3,400 | DST | 9.4 | 5.3 | 12.9 | 5.9 | 26.9 | 9.9 | Monday | |||
| Patrick Mahomes | KC | 7,800 | QB | 20.8 | 8.0 | 26.2 | 15.4 | 53.1 | 3.0 | Primetime | |||
| Isiah Pacheco | KC | 6,500 | RB | 16.6 | 6.9 | 21.3 | 11.9 | 33.2 | 9.8 | Primetime | |||
| Clyde Edwards-Helaire | KC | 4,200 | RB | 3.7 | 3.2 | 5.8 | 1.6 | 91.6 | 0.0 | Primetime | |||
| Kadarius Toney | KC | 3,200 | WR | 3.7 | 3.6 | 6.1 | 1.3 | 70.7 | 0.0 | Primetime | |||
| Rashee Rice | KC | 5,600 | WR | 11.2 | 7.0 | 16.0 | 6.5 | 51.1 | 2.9 | Primetime | |||
| Skyy Moore | KC | 3,000 | WR | 4.4 | 4.1 | 7.2 | 1.7 | 57.7 | 0.0 | Primetime | |||
| Marquez Valdes-Scantling | KC | 3,100 | WR | 3.3 | 3.6 | 5.7 | 0.8 | 72.4 | 0.0 | Primetime | |||
| Richie James Jr. | KC | 3,000 | WR | 1.4 | 2.4 | 3.0 | -0.2 | 94.3 | 0.0 | Primetime | |||
| Justin Watson | KC | 3,500 | WR | 6.8 | 5.4 | 10.4 | 3.2 | 47.1 | 1.0 | Primetime | |||
| Montrell Washington | KC | 3,000 | WR | 0.2 | 0.6 | 0.6 | -0.2 | 100.0 | 0.0 | Primetime | |||
| Travis Kelce | KC | 8,000 | TE | 18.9 | 9.4 | 25.2 | 12.6 | 42.7 | 16.0 | Primetime | |||
| Noah Gray | KC | 2,500 | TE | 3.6 | 3.9 | 6.2 | 0.9 | 54.3 | 0.2 | Primetime | |||
| Blake Bell | KC | 2,500 | TE | 0.5 | 1.5 | 1.5 | -0.5 | 99.0 | 0.0 | Primetime | |||
| Harrison Butker | KC | 0 | K | 8.1 | 4.8 | 11.3 | 4.8 | -2,146,826,273.0 | 0.0 | Primetime | |||
| Chiefs | KC | 3,300 | DST | 8.0 | 5.3 | 11.5 | 4.4 | 35.0 | 6.6 | Primetime |
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About Our NFL DFS Boom-Bust Tool for Week 14
In all DFS sports, being able to compare the strength of a player each day versus their popularity is key to success. For each player, we calculate the standard deviation based on a variety of factors and use that to calculate the ceiling (75th-percentile performance) the floor (25th-percentile performance) and the probability that they will bust (not meeting value) or boom (large field GPP winning player). Combining these metrics, you will be able to gain an edge on everyone by identifying under-owned or over-owned players.
The Boom and Bust percentages are determined by the probability that each player will reach a target score determined by position and salary. For instance on DK the average points/$1k for QB's is about 3x while other positions about 2.4x. On top of that on a full slate your team has to overperform by about 100 points, which is divvied up across the 9 roster spots.
Boom% is the probability of achieving positional target score based on chance of being the top 1 QB, top 2 RB, etc. Bust% is the probability of failing to achieve positional value – 2 fpts. Ceiling is the 75th percentile performance and the Floor is the 25th percentile performance. Finally, Optimal% is the probability that player will be in perfect lineup that slate.
How To Use Our NFL DFS Boom-Bust Tool
View the video below to see how our NFL DFS booms and busts can be used to build successful lineups.
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