MLB predictive intelligence. 10,000 simulations per game, compared against live market prices, with every edge explained in plain English.
Every pitch, every game day. From data ingestion to an alert, along with the edge, the probability, and the rationale.
Proprietary model runs thousands of game simulations across pitching, lineups, park conditions, and more.
Quantifying what markets expect. Model probabilities stacked against live pricing from major sportsbooks to surface inefficiency.
Every signal starts with a number. Confidence, expected value, edge size. No gut calls, no narratives. Just the math.
Predictions are useless if you don't know why. Every pick comes with the key factors driving the edge, written for humans.
Public data sources flow into the simulation engine. Edges, probabilities, and explanations. For every game, every day.
Every signal comes with the math behind it. Probability, expected value, and the fundamentals in plain English.
Moneylines, run lines, and totals. Every market the simulation covers, scored by expected value.
Predicted final score and win probability for every team, on every game. No black boxes.
Confidence-rated model outputs with expected value against live lines. So you always know where the edge sits.
Plain-English explanations. Not model jargon, not a spreadsheet dump. Actual reasoning behind every recommendation.
Three rules we hold ourselves to. They're the difference between a tipster and a model.
Every pick tracked. Every result logged. Every edge visible. No "trust me" energy, no "I was at the track" stories.
Powered by simulation, not gut feel. The model generates probabilities, not the other way around. No confirmation bias, just output.
Built for expected value over thousands of decisions, not streaks. EV compounds. That's the entire thesis, and it plays out every game.
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