Stacks
Stack shape, not just stack count
V12 scores stack composition explicitly — 4-3, 4-2-1, 3-3-2, secondary stacks, contrarian stacks. Each shape gets a ranker bonus based on slate state and historical pro patterns.
MLB DFS · Stack-aware · large field dataset
MLB DFS Lineup Optimizer with stacks that actually correlate
V12's MLB engine reads stack shape, pitcher-batter correlation, and a 70,000-lineup historical field-aware analysis before it builds your portfolio. Configured sims, behavioral pattern scoring, and FanDuel-ready CSV exports ship in every run.
70K+
field-aware analysis
10K
configured sims
150
max lineups per run
MLB + NBA nativeFanDuel CSV readyStack shape scoringBehavioral rankerReplayable postmortems
Section · 01
Stacks score on shape, not count
Every MLB optimizer tells you it does stacks. V12 explicitly scores stack shape — 4-3 same-team, 4-2-1, 3-3-2, secondary stacks against the opposing pitcher's batting side, contrarian stacks pivoting off chalk teams. Each shape gets a ranker bonus based on the slate state and on patterns that historically produced top-pro lineups. Stack count alone is a blunt instrument; shape is the cut.
Section · 02
Pitcher-batter correlation, baked in
When sim is enabled, the multivariate-normal simulator wires same-team batter positive correlation (~+0.35) and opponent-pitcher → batter negative correlation (~-0.30) directly into the covariance matrix. Percentile bands the ranker reads are post-correlation. That means a 4-stack against a tough pitcher gets the realistic ceiling/floor it deserves — not a math-fiction ceiling that assumes independent draws.
Section · 03
large field dataset the ranker actually uses
V12 carries an archive of over 70,000 historical MLB contest lineups, bucketed by sport, contest size band, and entry fee band. The ranker reads this archive when scoring new lineups, and the sim_optimals function can sample synthetic fields against your portfolio. The archive is V12-built from open scraping — not borrowed, not stitched together from another tool's data layer.
Section · 04
Pro-mimic bonus on lineups that match the winners
Trained on a 1,291-pro-lineup MLB dataset, the behavioral ranker bumps lineups whose stack shape, cap utilization, and salary distribution match historical top-pro lineups. Per-preset historical ROI backtests run against this archive too, so the next time you pick a preset, you can see how it actually performed on the last 14 days of real slates.
Built into the engine
Every run ships with the same pillars: pool, projections, ownership, simulation, ranker, and warnings.
Correlation
Pitcher-batter the way it matters
proprietary simulation with same-team batter +0.35 correlation and opponent pitcher → batter -0.30 correlation. Stack outcomes read realistic, not independent.
Field-aware
Large historical contest archive
Archive bucketed by sport, contest size band, and entry fee band. The ranker scores new lineups against real behavioral patterns — not invented heuristics.
Behavioral pattern
Pro-mimic ranker bonus
Trained on a 1,291-pro-lineup dataset. Bumps lineups that match the shape, cap utilization, and salary band that pros actually run on MLB slates.
Availability
Loud about scratches
Confirmed OUT, NS, scratched-late, and unavailable players are blocked when the slate data verifies them. Missing data fails loud rather than silently passing.
Backtest
Per-preset historical ROI
MLB backtest harness runs new configs against the archive. Configurable date range. Surfaces top-5 preset combinations by ROI, sortable.
Common questions
01
Does V12's MLB DFS optimizer support stacks?
Yes. V12 explicitly scores stack shape — 4-3 same-team, 4-2-1, 3-3-2, secondary stacks — and the ranker can be tuned toward shapes that match historical top-pro MLB lineups. Stack count alone isn't enough; the shape of the stack matters and the ranker treats it that way.
02
Does V12 model pitcher-batter correlation for MLB DFS?
Yes. The proprietary simulation simulator wires same-team batter positive correlation (~+0.35) and opponent-pitcher → batter negative correlation (~-0.30) into the covariance matrix. The percentile bands the ranker reads reflect realistic stack outcomes instead of independent draws.
03
What is V12's MLB field-aware analysis?
V12 carries an archive of over 70,000 historical MLB contest lineups, bucketed by sport, contest size, and entry fee. The ranker uses this archive to score new lineups against patterns that pros historically built. The archive is V12-built, not borrowed from any other DFS tool.
04
Can V12 generate FanDuel MLB lineups?
Yes. The MLB engine targets FanDuel's MLB roster (P/C/1B/2B/3B/SS/OF/OF/OF, $35,000 cap) and the export uses the official FanDuel entry template format. Player IDs and entry IDs are written into the CSV so it uploads directly into the contest.
05
How does V12 handle late MLB scratches?
Confirmed OUT, NS, locked, and unavailable players are blocked at the availability wall when public slate data verifies them. If late scratches appear after generation, the dashboard surfaces them as warnings and the agent can regenerate the affected lineups before lock.