Updated: Monday, Dec 15 01:23:43 AM EST
Chicago State Cougars vs Loyola Chicago Ramblers (Final)
84 - 75, (Margin: +9, Total: 159)
Gentile Arena
Second-Half conditional estimates based on a margin of +7.0 points and 63.0 total points (models are continuously adjusted up to Halftime)
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E[AWAY] E[HOME] E[SP] 68% CI E[TOTAL] 68% CI 2H-A 2H-H 2H-SP 2H-TTL AWAY WIN% HOME WIN% (ODDS HOME)
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72.4 61.7 10.7 (0.7, +20.8) 134.1 (121.9, 146.3) 0.0 0.0 +10.7 134.1 86.7% 13.3% +653
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Live conditional estimates per 5 Minutes (+/- 1 deviation) (models are continuously adjusted)
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TYPE 5M 10M 15M 20M 25M 30M 35M 40M
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E[SP] - - - - - - - +7.4
P[W] - - - - - - - 0.0%
ODDS - - - - - - - +99999
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Ornstein-Uhlenbeck Process with BIC Model Selection**
TYPE L95% E[X] U95%
E[F|1H] -10.2 6.2 22.6
E[F|NOW] -2.3 8.0 18.2
Deep Learning: Quantile GRU v6.0 (Neural Network with Calibrated Uncertainty)
TYPE L95% L68% E[X] U68% U95%
E[F|1H] 5.3 6.2 7.1 7.9 9.5
E[F|NOW] 5.9 6.9 7.8 8.7 10.5
Enhanced Ornstein-Uhlenbeck Process (BIC-optimized AR order, continuous-time Kalman filtering)
MODEL NOTES:
** O-U Process validated on 61,166 games (MAE: 8.50 pts, well-calibrated 68%/95% confidence intervals)
** GRU v6.0 validated on Fall 2025 (MAE: 10.99 pts, 5.2% better than previous LSTM)
CHART LEGEND:
1) Blue line: O-U Improved model trained on first-half data, locked at halftime (68% and 95% CI shown)
2) Green line: O-U Improved model continuously retrained as new plays arrive (68% CI shown)
3) Both lines use the same statistical model; divergence shows how live events update predictions
4) Model automatically selects AR(1) or AR(2) using BIC for optimal fit to irregular scoring events
Updated: Monday, Dec 15 01:23:43 AM EST
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