Price every player prop before the market does.

Live DFS lines plus a de-vigged sportsbook reference; every projection grades nightly against final box scores.

• 9-batter lineup through a base-out state machine vs starter → bullpen
• Empirical-Bayes matchup rates × platoon splits × park/weather × umpire zones
• Statcast contact/whiff/arsenal tilts; posted lineups; steals simulated in-game

Live lines from four DFS books, priced on player rates measured from recent box scores; graded nightly. Injury statuses default to healthy until a licensed feed is connected, and affected projections are flagged.

• Usage → shot/FT/turnover → rebound battle → assist/steal/block attribution
• Per-sim minutes and availability rolls; probabilities are DNP-conditional (DFS voids DNP legs)
• Combos and fantasy correlate by construction (same simulated possessions)

The engine is built and has passed two audits. Live player rates and DFS lines connect when the season opens in late October.

• Load management as a first-class availability channel (rest posture × schedule spots)
• On-ball usage redistribution when stars sit (∝ minutes × on-ball share, conservation proven)
• Garbage time simulated: blowout sims split into competitive + bench-heavy floors

The engine is built and audited. Play-by-play data and DFS lines connect with the September season.

• Environment (drives/plays/points/weather) → per-drive script-adjusted pass rate
• Role-based allocation: targets = routes × TPRR, carries = rush share, TDs = end-zone equity
• Conservation by construction: QB passing yards ≡ Σ receiver yards per sim (structural stack correlations)

The engine is built and audited. College data feeds and a check of DFS line coverage land with the late-August season.

• Starter pulls and garbage time are simulated (per-staff pull margins; backups absorb usage)
• Per-team tempo identities (55–85 plays/game); mismatch-scale environments
• Roster volatility engine: transfer/freshman/committee inputs → demotion-heavy grading

The engine is built and audited, and simulates college structure directly: five fouls, the bonus free-throw ramp, end-game fouling, two-foul benching, and transfer-heavy rosters. Live stats and lines connect with the November season, and every grade is capped at B+ until the backtest earns more.

• Minutes come first: availability, foul trouble (five-foul disqualification), two-foul first-half benching by coach tendency, blowout compression, and tournament rotation tightening are realized per simulation — every probability is DNP-conditional
• The bonus / one-and-one FT structure is simulated within each half (foul accumulation ramps team FT trips; front-end misses are live rebounds) — the closed-form FTA claim is audited against the sim
• End-game fouling is a first-class channel: close-but-not-tied finishes extend the game with intentional-foul cycles (leading team shoots two, trailing team forces threes) — FTA and 3PA distributions carry the real late-game fat tail

Live DFS lines priced on serve and return rates measured from each player's recent matches, split by surface. No sportsbook posts tennis player props, so edges read model versus line, and every grade is capped at B+ until the backtest earns more.

• Deuce games, tiebreaks (1-2-2 rotation, tb10 deciders), sets, Bo3/Bo5
• Barnett–Clarke serve/return blend over tour × surface anchors
• Per-player rates measured from recent matches (surface-split, recency), EB-shrunk toward the anchors

The engine is built, harness-verified, and adversarially audited, with PGA cut events and LIV 54-hole shotgun events as separate formats. DFS golf lines are confirmed available; the missing piece is a licensed strokes-gained data feed, not the calendar.

• Course environment comes first: per-hole difficulty sets the outcome environment, realized exactly by the sim
• PGA and LIV as different structures: 36-hole cut truncation vs 54-hole no-cut shotgun
• The player's own simulated rounds decide his cut — cut risk correlates with every prop

Real DFS lines priced against measured fighter statistics. Full cards build on fight days, and every published prop grades against final fight statistics the morning after. No sportsbook posts these markets in usable multi-book form, so edges read model versus line, and every grade is capped at B+ until the backtest earns more.

• Fight structure comes first: a per-tick finish hazard yields closed-form fight time, round-reach, and decision claims the sim realizes exactly
• 3-round and 5-round fights as different structures; rounds start standing (ground spells end at the bell)
• Early finishes settle volume props — finish risk is priced into the distribution, never voided away

Real DFS lines priced against measured team and player inputs: posted lineups with a confirmed-or-projected status, per-player match statistics, and substitution timing from recent matches. An unposted lineup caps every grade for that match. No sportsbook posts soccer player props in usable multi-book form, so edges read model versus line, and every grade is capped at B+ until the backtest earns more.

• Minutes come first: starts, sub-off timing, and sub-on windows are realized per simulation — every probability is appearance-conditional (DFS voids never-entered legs)
• Possession is zero-sum and splits the prop world: one environment drives your passing volume AND the opponent's defensive actions and keeper saves in the same sims
• Share slots conserve team volume exactly: substitutions pass the opportunity slot while conversion rates stay the player's own

Real DFS lines priced against measured pro match data: league pace, team styles, rosters, and role shares, using only games played before each series. Projections are made before champion select, so distributions widen to carry that uncertainty. No sportsbook posts these markets, so edges read model versus line, and every grade is capped at B+ until the backtest earns more.

• Game duration comes first: a per-minute end-hazard drives every claim — expected map length, P(reach 30/35), team kills — and the sim realizes each exactly
• Early ends settle volume props (a 22-minute stomp cashes unders); remake/forfeit/cancellation are the void events, never simulated in-map
• Line scope is part of the market: Map 1 / Maps 1-2 / Maps 1-3 / series lines sum over the maps actually played — P(map 3 happens) is a structural channel like the golf cut

Real DFS lines priced against measured match data: per-player kill and headshot shares, team strength, and map pools from recent finished maps. Before the map veto, projections mix the likely map pool and say so; a stand-in or unconfirmed roster caps the grade. No sportsbook posts these markets, so edges read model versus line, and every grade is capped at B+ until the backtest earns more.

• Rounds come first: a CS2 map is a race to 13 — every volume stat scales with rounds played, and the rounds distribution is exact score-race mathematics the simulation realizes directly
• Early ends settle volume props (a 13-3 stomp cashes unders); forfeit/cancellation are the void events, never simulated in-map
• The inversion: close maps run long and lift both teams' kills — opposing players' overs are positively related through rounds (surfaced on every relevant prop, the honest slip-stacking number)