A $20 entry into a 150,000-entrant tournament
The engine builds an opposing field of 10,000 lineups from projected ownership, simulates the slate 5,000 times with players correlated inside their own games, and ranks every lineup by expected return against that contest's actual payout curve, choosing on one half of the draws and reporting the other. This run scored 10,000 lineups in 23.5 seconds.
| # | Lineup | Salary | Avg score | ROI (simulated) | Cash % | Ownership | Top 1% |
|---|---|---|---|---|---|---|---|
| 1 | QBJared GoffRBChase BrownRBDe'Von AchaneWRAmon-Ra St. BrownWRGarrett WilsonWRMichael WilsonTESam LaPortaTEDalton SchultzDSTChargers | $50,000 | 130.5 | 635% | 31.6% | 131% | 3.66% |
| 2 | QBTua TagovailoaRBBijan RobinsonRBOmarion HamptonWRDrake LondonWRZay FlowersWRGarrett WilsonWRWan'Dale RobinsonTEHarold Fannin Jr.DSTRaiders | $49,900 | 130.1 | 218% | 29.6% | 164% | 2.78% |
| 3 | QBDaniel JonesRBBijan RobinsonRBChase BrownWRChris OlaveWRAlec PierceWRMichael WilsonWRWan'Dale RobinsonTEDallas GoedertDSTRavens | $49,800 | 135.8 | 564% | 40.9% | 173% | 3.60% |
| 4 | QBCam WardRBChase BrownRBKenny GainwellWRAmon-Ra St. BrownWRChris OlaveWRGarrett WilsonWRWan'Dale RobinsonTETucker KraftDSTEagles | $49,900 | 129.1 | 74% | 30.2% | 155% | 3.28% |
| 5 | QBC.J. StroudRBDe'Von AchaneRBD'Andre SwiftWRJa'Marr ChaseWRNico CollinsWRMichael WilsonWRWan'Dale RobinsonTEDalton SchultzDSTEagles | $49,800 | 125.7 | 457% | 23.0% | 133% | 1.86% |
| 6 | QBJared GoffRBBijan RobinsonRBChase BrownWRNico CollinsWRGarrett WilsonWRWan'Dale RobinsonWRDevaughn VeleTESam LaPortaDSTChargers | $49,800 | 127.1 | 42% | 25.3% | 143% | 2.10% |
| 7 | QBJustin HerbertRBChase BrownRBDerrick HenryWRZay FlowersWRWan'Dale RobinsonWRQuentin JohnstonTETrey McBrideTESam LaPortaDSTRaiders | $49,900 | 131.5 | 72% | 32.9% | 198% | 2.26% |
| 8 | QBJustin HerbertRBBijan RobinsonRBKenny GainwellWRChris OlaveWRGarrett WilsonWRDK MetcalfWRMichael WilsonTESam LaPortaDSTJaguars | $50,000 | 132.2 | 313% | 35.5% | 135% | 4.14% |
Generated 2026-08-19. The ROI column is not sorted, and that is deliberate. Lineups are ordered by the engine's own ranking, made on one half of the draws; the ROI shown is what each earned on the other half. Sorting the board by that column would just promote whichever lineup got luckiest in the half being reported, which is the exact bias the split exists to remove. A tool whose headline number always sorts perfectly is showing you its luck.
What the engine knows about one lineup
NE @ SEA, with the juice removed
A −110/−110 market implies 52.4% + 52.4% = 104.8%. That extra 4.8% is the house's cut, not anybody's opinion. Strip it out and you can see what each book actually thinks, and what you are paying for the privilege.
| Book | Home | Away | Raw implied | Hold | Fair home % |
|---|---|---|---|---|---|
| DraftKings | -110 | -110 | 104.76% | 4.76% | 50.00% |
| FanDuel | -112 | -108 | 104.75% | 4.75% | 50.43% |
On this game FanDuel is the cheapest place to transact, and the books disagree by 0.43 points of fair probability once the vig is stripped. Both facts are invisible on the raw price.
How the simulator actually works
The field is people, not optimizers. A tournament is not won against the best lineups, it is won against the lineups people actually enter. We build the opposing field from projected ownership with a per-lineup appetite for chalk, quarterback stacking and bring-backs, so it contains both the chalk-chasers and the contrarians a real contest has.
Players are correlated inside their game. Scores are drawn jointly through each game's correlation structure, not independently. A quarterback's ceiling and his receiver's ceiling arrive together, because in football they do.
Every player keeps his own range. Outcomes are shaped to that player's own floor and ceiling rather than a generic curve scaled off his median.
Prizes come from your contest's real payout curve. Rank is read from where a lineup finished in the simulated field, then mapped to the block of real places it stands for. Duplication is charged once, when copies genuinely spill past that block.
ROI is measured out of sample. The engine ranks lineups on one half of the draws and reports their return from the other half. Ranking thousands of lineups by a noisy estimate and then quoting the winner's own number always flatters it. That gap is luck, and we throw it away rather than sell it to you.
Which tools this describes. The lineup builder (/dfs/build/) and the top plays on the optimizer (/dfs/optimizer/) both rank this way: lineups are chosen on one half of the draws and their return is reported from the other. Top-1% finish rate is displayed but is not the ranking key. Method in place since 18 August 2026, checked against the production engine (build 9ee914a) on 15 September 2026. The worked example above was frozen on 2026-08-19 with the same method.
Depth is not a luxury. Running the same slate twice with different draws, the engine reproduces 10% of its top 150 at 250 draws, 49% at 5,000 and 67% at 20,000. We publish that because it is the honest limit of what a single lineup's ROI can tell you.
See it on this week's slate
The numbers above are frozen so you can audit them. The live tool runs the same engine against the current week, with your contest's exact size, entry fee and payout shape.
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