Every CourtEdge model measures lineups the same way: by win equity — the Monte Carlo probability a lineup finishes 1st in the GPP — plus expected ROI. We draw one fantasy score for every golfer from a boom/bust distribution built off projection · ceiling · floor, score a realistic field drawn by ownership, and rank across 10,000 simulated tournaments. Leverage is the whole game: when your low-owned bink-maker fires, the chalk field gets left behind.
Initializing engine…
Win equity leaderboard
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Lineup
Win equity
Fair odds
Top 1%
Top 10%
Cash
Exp ROI
Avg finish
Proj mean
Salary
Build / paste your own lineup
Salary: $0 / $50,000 · 0/6
Classic = 6 golfers under $50,000. Showdown = 1 Captain (1.5× points & salary) + 5 FLEX. Pasted lineups are simmed against the same field with the controls above.
Model: per-golfer scores are drawn from a two-piece (split) normal anchored on projection with separate ceiling/floor spread — golf's heavy right-skew (boom rounds) and blow-up downside, plus a shared per-slate scoring-environment term so the field is internally consistent. The opponent field is generated by sampling the pool by projected ownership under the salary cap; win equity is the order-statistic probability of being the single highest score across the chosen field size. GPP mode fattens the ceiling tail and scores a top-heavy payout curve; Cash mode tightens to the floor and scores a double-up. Projections / ownership from the CourtEdge Travelers R4 main-slate model. Payout curves are representative, not a specific contest. Engine:/js/win-equity-engine.js (seedable Monte Carlo, runnable via --selftest).