FINAL: Colorado 86 — Oklahoma 90. Our Monte Carlo simulation projected Colorado 76.7 - Oklahoma 83.6 (Oklahoma at 68.2% win probability). The spread is 9.0 and the total is 163.5.
Colorado
76.7
Projected Score
VS
O/U 163.5
Oklahoma
83.6
Projected Score
Win Probability
ColoradoOklahoma
+9.0
Spread (Colorado)
163.5
Total Line
10,000
Simulations
OklahomaColorado L4
Calibrated accuracy at this confidence: 71.8% (4,284 games)
Projected Points Range 10th – 90th percentile
Oklahoma
718496
Colorado
647790
Projected
Colorado 76.7 — Oklahoma 83.6
Actual
Colorado 86 — Oklahoma 90
Pick Results
Colorado +9.0spreadWIN+0.45u
Spread Analysis
Colorado Cover
60.8%
Oklahoma Cover
39.2%
ATS Edge: +3.4 pts
AI Intelligence Analysis
NEUTRAL -1GREEN ZONE82.7% WR (n=37)
Market pricing Oklahoma at 80.6% (overconfident) vs model 69.5% is inverted edge case (model disagrees by being MORE skeptical). This violates hardcoded rule: high disagreement = model likely wrong. Recent CBB ICE_COLD status (22.2% WR 7d) + unprofitable LOW bucket make confident conviction impossible.
Key Factors
- Inverted edge case: Market more confident (80.6%) than model (69.5%), -11.1% prob edge against model
- Hardcoded rule violation: High model-market disagreement signals model is wrong, not finding value
- Spread edge direction correct: Model +3.1pts toward Oklahoma, but probability edge is inverted
- Recent form: CBB ICE_COLD tier (22.2% WR 7d) creates regime doubt on all picks
Risk Factors
- High edge warning: Model-market 11.1% disagreement (market overconfident) historically results in 29.4% WR when model tries to fade confidence
- Calibration instability: LOW bucket unprofitable (50.1%), suggesting model's confidence calibration is drifting
- Regime collapse: 7d performance at 22.2% WR is catastrophic, predicting continued volatility
HIGH EDGE WARNINGMODEL MARKET CONFLICTICE COLD FORMINVERTED EDGECALIBRATION DRIFTMARKET OVERCONFIDENCE
Edge Analysis
Moneyline
Oklahoma 68.2%
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Spread
+9.0
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Total
163.5
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How this prediction was generated: This page shows output from the Olympus Bets College Basketball Monte Carlo engine. Each game is simulated 10,000 times using real-time team data, injury reports, and current odds. Probabilities are calibrated using Bayesian methods and sized via the Kelly Criterion. Full methodology →