Updated: Monday, Dec 15 01:22:43 AM EST

St. Xavier  (IL) Cougars vs Southeast Missouri State Redhawks (Final)
65 - 88, (Margin: -23, Total: 153)
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Second-Half conditional estimates based on a margin of -24.0 points and 68.0 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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59.7	84.7	-25.1	(-35.1, -15.0)	    144.4	(132.2, 156.6)	 0.0	 0.0	-25.1	144.4	    2.3%	   97.7%	-4190
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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
======================================================================================================================================================
 E[SP]         -	         -	         -	         -	         -	         -	     -30.4	     -30.4
  P[W]         -	         -	         -	         -	         -	         -	    100.0%	    100.0%
  ODDS         -	         -	         -	         -	         -	         -	    -99999	         -
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Ornstein-Uhlenbeck Process with BIC Model Selection**
TYPE		L95%	E[X]	U95%
E[F|1H]  	-39.8	-22.5	-5.1
E[F|NOW]	-42.0	-29.5	-17.0

Deep Learning: Quantile GRU v6.0 (Neural Network with Calibrated Uncertainty)
TYPE		L95%	L68%	E[X]		U68%	U95%
E[F|1H]  	-28.8	-25.3	-24.0		-22.5	-20.1
E[F|NOW]	-35.5	-31.2	-29.6		-27.7	-24.9

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 01:22:43 AM EST
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