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Training data from 2002 Backtested 2018–2025 72.9% moneyline accuracy
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Years of Training Data
0
Moneyline Accuracy (64% overall)
$19.6K
Return Since 2018 (+16% avg ROI)
0
ML Models

Built for bracket intelligence

Learn more →
Ensemble

5-Model Ensemble

Predictions generated by XGBoost, Random Forest, PyTorch neural network, KenPom analytic model, and a meta-learner stacking their outputs. Each model trained on 200+ features per matchup.

Simulate

Monte Carlo Bracket Sim

10,000 Monte Carlo simulations per bracket chart every plausible path to the championship. Champion probabilities, upset likelihoods, and round-by-round advancement odds.

Data

24 Years of NCAA Data

Trained on KenPom efficiency ratings, strength of schedule, tempo, and luck metrics from every season since 2002. Backtested on 380 tournament games from 2018–2025.

Backtest results

Full methodology →
Moneyline
72.9%
Win rate · 380 bets
+19.68% ROI · $7,478
Spread
62.1%
Win rate · 380 bets
+18.56% ROI · $7,760
Over / Under
57.9%
Win rate · 380 bets
+10.53% ROI · $4,400
Favorites 328 bets
73.8%
Correct242
Incorrect86
Return+$5,083
ROI+15.50%
242 W86 L
Underdogs 52 bets
67.3%
Correct35
Incorrect17
Return+$2,395
ROI+46.06%
35 W17 L
Favorites 213 bets
59.6%
Correct127
Incorrect86
Return+$3,240
ROI+13.83%
127 W86 L
Underdogs 167 bets
65.3%
Correct109
Incorrect58
Return+$4,520
ROI+24.61%
109 W58 L
Over 222 bets
51.8%
Correct115
Incorrect107
Return-$270
ROI-1.11%
115 W107 L
Under 158 bets
66.5%
Correct105
Incorrect53
Return+$4,670
ROI+26.87%
105 W53 L

"Trained on 24 years of NCAA data. Backtested on every tournament game since 2018. Ready for March 2026."

BallGPT — Training data from 2002 · Backtest results from 2018–2025 · 380 games verified