Institutional-grade pitcher and player projection systems built on Bayesian modeling, real-time data pipelines, and machine learning — designed to give you a consistent edge.
Each model is purpose-built for its league — accounting for park factors, lineup construction, umpire tendencies, and real-time Vegas movement.
Per-batter strikeout probability engine with Bayesian H2H blending, platoon splits, pitch mix analysis, and full fantasy scoring.
Korean Baseball Organization strikeout projections adapted for KBO park factors, translation adjustments, and league-specific tendencies.
Nippon Professional Baseball strikeout projections with full NPB-to-MLB translation factors and league-adjusted Bayesian priors.
Most projection tools treat every at-bat the same. We don't. Every projection accounts for the specific pitcher-batter matchup on that day.
K probability is computed individually for each batter in the lineup — accounting for handedness, chase rate, zone contact, and historical H2H data.
Head-to-head matchup data is blended with population priors using PA-weighted Bayesian inference — no more small sample size noise.
Live K lines, outs lines, and prop odds from DraftKings, FanDuel, BetMGM, and Caesars — pulled automatically and baked into every projection.
Park factors, umpire K tendencies, weather, wind direction, day/night splits, and rest days are all factored into the final projection.
We use xFIP and SIERA instead of ERA as the ERA base — more predictive, less noise from defense and sequencing luck.
Pitcher archetype vs lineup vulnerability analysis — automatically flags when a chase-dependent pitcher faces a lineup full of chasers.
A multi-stage pipeline that starts with pitcher arsenal data and ends with a per-start K distribution and fantasy scoring breakdown.
Each pitch type's whiff rate, chase rate, and zone contact rate is pulled from Baseball Savant and weighted by usage frequency.
Each lineup spot gets a K probability based on their chase%, zone contact%, and historical performance vs this pitcher's arsenal.
H2H data is merged with league-average priors. The more PA in the matchup, the more the actual data overrides the prior.
10,000 simulated starts produce a full K distribution — projectedK, confidence interval, over/under probability vs Vegas line.
One of the most critical — and most overlooked — factors in a pitcher K prop is understanding how a pitcher gets strikeouts, and whether tonight's lineup actually enables that approach. Our Lineup Intel system classifies every pitcher by archetype and scores the opposing lineup accordingly.
A chase-dependent pitcher who relies on batters swinging at pitches outside the zone is only dangerous against lineups that actually chase. Put him against a disciplined lineup and his K rate collapses — regardless of what the Vegas line says. Conversely, a zone dominator who generates whiffs on pitches in the zone remains effective even against patient lineups. Knowing the difference before you bet is everything.
The bottom line: Before finalizing any K prop bet, check the pitcher archetype, count how many batters in the lineup match the pitcher's vulnerability profile, and let that inform your confidence level. Our model does this automatically — and shows you the full breakdown for every starter.