Updated: Monday, Dec 15 01:22:05 AM EST
High Point Panthers vs App State Mountaineers (Final/OT)
78 - 86, (Margin: -8, Total: 164)
Tarlton Complex
Second-Half conditional estimates based on a margin of -1.0 points and 67.0 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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71.9 70.4 1.5 (-8.5, +11.5) 142.3 (130.2, 154.5) 0.0 0.0 +1.5 142.3 60.5% 39.5% +153
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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] - - - - - - - -
P[W] - - - - - - - -
ODDS - - - - - - - -
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Deep Learning: Quantile GRU v6.0 (Neural Network with Calibrated Uncertainty)
TYPE L95% L68% E[X] U68% U95%
E[F|1H] -2.0 -1.6 -1.4 -1.2 -0.9
E[F|NOW] -9.1 -7.7 -7.1 -6.4 -5.2
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 01:22:05 AM EST
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