Foundation Models for Sports Intelligence

Next-Generation Probabilistic Sports Forecasting

Deep foundation models built for sports—delivering calibrated probability distributions for player performance, matchup outcomes, and live daily slates.

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MLB Daily Slate • Sample Player Projections
CALIBRATED PROBABILITIES
Player Matchup 1+ Hit Probability 2+ Total Bases
Bobby Witt Jr. KC vs. CLE
78.4%
51.2%
Luis Arraez SD vs. ARI
76.9%
38.4%
Vladimir Guerrero Jr. TOR vs. BOS
74.2%
47.8%
Shohei Ohtani LAD vs. SF
72.8%
55.6%

Built for Precision & Calibration

Moving beyond point estimates and hand-crafted heuristics with modern deep learning.

01 · Full Distributions

Beyond Simple Averages

Instead of single-number projections, SportsFM outputs calibrated probability distributions across every outcome—capturing upside, tail risk, and matchup sensitivity.

02 · Live Context

Real-Time Slate Updates

Forecasts automatically adjust as starting lineups, rotations, and game conditions are confirmed ahead of first pitch.

03 · Rigorous Backtesting

Out-of-Sample Verified

Evaluated on strict out-of-sample calibration and log-loss benchmarks against industry consensus baselines.

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