Reverse-engineer a winning lineup.
Break down one winning lineup end to end — the score, the payout, where ownership leaned, how the salary was spread, the stack shape, and the duplication risk.
We take one real winner
A lineup that actually cashed near the top of a contest, with its real roster and result.
We grade the construction
Salary spread, projection, floor/ceiling, ownership sum and geo-mean, and stack shape.
You see the dup risk
An empirical estimate of exact duplicates in the field, with confidence flags on thin data.
Duplication risk, made calculable — no simulator required
We estimate how many exact-lineup duplicates a build draws in a real DraftKings field, backed by historical contest data with transparent calibration-confidence badges. It's the part of winning construction nobody else makes legible.
Grade a lineup inside dfsOS →What the lineup review breaks down
Salary spread
How the winning build allocated salary across the roster.
Projection & range
Projected points with floor, ceiling, and volatility for the build.
Ownership & stack
Ownership sum and geometric mean, plus the stack shape that won.
Expected dups
Empirical duplicate-risk estimate with calibration-confidence badges.
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