FINAL: Minnesota 48 — Baylor 67. Our Monte Carlo simulation projected Minnesota 76.9 - Baylor 80.8 (Baylor at 64.4% win probability). The spread is 4.0 and the total is 147.5.
Minnesota
76.9
Projected Score
VS
O/U 147.5
Baylor
80.8
Projected Score
Win Probability
MinnesotaBaylor
+4.0
Spread (Minnesota)
147.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 70.9% (4,284 games)
Projected Points Range 10th – 90th percentile
Baylor
688193
Minnesota
647790
Projected
Minnesota 76.9 — Baylor 80.8
Actual
Minnesota 48 — Baylor 67
Pick Results
OVER 147.5overWIN+0.91u
Spread Analysis
Minnesota Cover
49.9%
Baylor Cover
50.1%
ATS Edge: +0.2 pts
AI Intelligence Analysis
LEAN +1GREEN ZONE82.7% WR (n=37)
Away favorite Baylor sits in historically profitable zone (82.7% WR for away ML favorites) with +5.4% edge on moneyline (64.6% model vs 59.2% market), but severe recent form (ICE_COLD 22.2% WR over 7d) and calibration drift to unprofitable LOW bucket mandate reduced conviction.
Key Factors
- Zone support: Away ML favorites 82.7% WR (n=37, z=4.11, GREEN zone) provides historical statistical edge
- Moneyline edge: Model 64.6% vs market 59.2% = 5.4% edge (Baylor -170 represents value)
- Tournament dynamics: Neutral court eliminates 3.5pt HCA disadvantage for away team
- Model-market alignment on direction: Both agree Baylor wins, only margin width differs
- Recent form headwind: ICE_COLD tier (22.2% WR 7d, n=9) and LOW bucket unprofitable (50.1% WR)
Risk Factors
- Severe recent form: CBB ICE_COLD tier over 7d (22.2% WR, n=9) creates regime doubt
- ML recent underperformance: 30-day ML picks at 36.8% WR (7-12) well below 65.6% historical grade
- Calibration drift: LOW bucket has turned unprofitable (50.1% WR as of latest), suggesting threshold creep
GREEN ZONEML VALUEAWAY FAVORITE EDGEICE COLD FORMCALIBRATION DRIFTINJURY IMPACT
Edge Analysis
Moneyline
Baylor 64.4%
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Spread
+4.0
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Total
147.5
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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 →