The philosophy.
BallBet is a simulation platform, not a picks service. The model outputs probability distributions, edge percentages, and sample sizes — and lets you decide what to bet. The transparency is the trust mechanism.
The sim engine.
Why 25,000 trials.
Features & inputs.
Pitcher inputs.
Batter inputs.
Environmental inputs.
Feature freshness.
The Comp Lab.
When a batter has fewer than 20 prior PAs against a pitcher, raw BvP is statistical noise. The Comp Lab finds statistically similar batters and aggregates their PAs against that pitcher, expanding the sample 5–10× under a transparent similarity score.
The similarity formula.
Weighted Euclidean distance over z-scored features. similarity = 1 / (1 + distance).
The feature vector.
Comp selection rules.
Time decay on historical BvP.
Linear: current season 1.0×, last season 0.7×, two seasons ago 0.4×, anything older 0.2×. Captures arsenal evolution without throwing volume away.
Uniqueness flag.
When the rank-1 comp scores below 0.70, we flag the target as unique and recommend additional caution on the aggregate sample.
Priors, samples & confidence.
Sample size thresholds.
Confidence bands.
Low-confidence flag.
Edge calculation & CLV.
Vig handling.
CLV measurement.
Why “edges” not “picks.”
We surface modeled probability distributions, not betting recommendations. You choose what to bet based on the model output plus your own bankroll and risk tolerance.
Calibration.
Public-facing calibration.
The Calibration Dashboard at /calibration shows our hit rate by edge band over every tracked play. Anyone can audit it. Tools that hide losing streaks are tout services. We're not that.
What miscalibration looks like.
/changelog. If something here is wrong or unclear, email methodology@ballbet.ai and we'll fix it.