MLB Analytics & LiveSignals

The Problem With "Data-Driven": Every service claims to be data-driven. Most of them mean a spreadsheet or some AI shit. i built something different: a live pricing model that tracks the specific spots where a sportsbook's own algorithm hasn't caught up yet. Sportsbooks don't handicap every line by hand, they can't. Too many games, too many markets, moving too fast. So they lean on algorithms that update odds based on preset rules and assumptions. Those systems are good, but they're not perfect. They react to conditions; they don't think. That gap between what the algorithm assumes and what's actually happening on the field is where we work.

‍MLB: Where It Started: Our first live model is built around MLB run totals, specifically the innings where bullpen decisions swing a game the most. We track pitcher fatigue, closer availability, and bullpen depth in real time. This is the kind of situational detail a generic pricing model doesn't fully account for when it moves a total mid-game. What I do differently is that our model weighs recent workload and quality metrics for every arm a team has available, adjusts for how a bullpen typically performs under different leverage situations, and recalculates as the game state changes, not just once before first pitch. When our model and the live line disagree by enough, that's a signal.

[Track record block — link/embed to the Track Record page]

‍Where It's Headed: MLB is live today. NHL and NBA models are in development, built on the same core idea of finding the situational spots where sportsbook algorithms are structurally weak, not just "who's going to win." More to come soon!

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