Nightly MLB predictions — with receipts.
A machine-learning model picks every MLB game — the winner, the score, and the hitters to watch. Every prediction is logged, graded against the real result, and published. Hits and misses alike.
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Recent results
STEP 1
Every pitch, in
Play-by-play and pitch-level data from every MLB game, updated each morning.
STEP 2
Rolling form
Each team's recent play — and tonight's actual lineup — distilled into features.
STEP 3
One model, three calls
A gradient-boosted model predicts each team's runs: that's the winner, the score, and the game total.
STEP 4
Scored in public
Picks post every morning, then get graded against the final score.
Predictions are machine-learning model output, not betting advice.