DATA-DRIVEN SPORTS INSIGHTS

Better Models. Smarter Picks.

Built by an actuary, BBMI’s transparent, probability-driven models find edges before the market moves. Every pick is locked before the game, graded in public, and kept on the record.

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Data-driven models

Thousands of simulations power our probabilistic projections.

Verified performance

Every pick is graded in public. Nothing is hidden.

Market awareness

We compare our numbers to the market to find real edges.

Research first

Continuous testing and validation keep our models sharp.

MethodologyHow the MLB model works

A per-plate-appearance Monte Carlo simulator. Every game is replayed hundreds of times, one plate appearance at a time, with each batter facing the pitcher actually on the mound and the result advancing runners the way real batted balls do.

What it reads

Handedness splits for every hitter and pitcher on both rosters
Confirmed lineups and starters, plus each pitcher’s workload distribution
Park factors per event type, weather, and the Wrigley wind model
Active rosters and bullpen roles, sampled by usage rate
Every input frozen at its pre-game state, never restated later

What it produces

A full distribution of runs for each side, not a single projected score
Full-game total, first-five-innings total, margin, win probability, and an expected value against the posted moneyline
Season-long playoff, pennant and title odds from a separate season simulation

What we publish

Full-game totals and run line
First-five-innings spreads
First-five and full-game moneyline, each graded and each carrying a win probability and an expected value
Rankings come from a different, older engine and are labeled as such

Not claimed

Totals is one-sided by design: the under side did not hold up in testing and is not shipped. Full-game totals and both moneylines are labeled in calibration, with their records public while the sample builds.

See the MLB record →