MIN vs SAS prediction for May 6, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects SAS 107.8 - MIN 107.9. MIN is favored with a 50.0% win probability. The spread is -9.5 and the total is 218.5.
SAS
107.8
Projected Score
VS
O/U 218.5
MIN
107.9
Projected Score
Win Probability
SASMIN
-9.5
Spread (SAS)
218.5
Total Line
10,000
Simulations
MIN L5SAS W4
Calibrated accuracy at this confidence: 60.2% (1,191 games)
Projected Points Range 10th – 90th percentile
MIN
98108118
SAS
98108118
Projected
SAS 107.8 — MIN 107.9
Actual
SAS 133 — MIN 95
Pick Results
Julian Champagnie OVER 7.5 pointsnba_player_pointsWIN+0.88u
Dylan Harper UNDER 14.5 pointsnba_player_pointsWIN+0.58u
Mike Conley UNDER 4.5 pointsnba_player_pointsWIN+1.43u
Model Projection
MLELITE+320
MIN ML
+26.1%
Edge
50.0%
Win/Cover Prob
1.0u
Units
100
Quality
Model gives MIN 50% win prob
Against the Spread
MIN ATS
-9.6 pts edge | 76% cover
ELITE
Over/Under
None 218.5
-2.9 pts edge | 56% under
PASS
Starting Lineups
MIN1 OUT
Anthony Edwards28.8PPG5.0RPG3.7APG
Julius Randle21.1PPG6.7RPG5.0APG
Jaden McDaniels14.8PPG4.2RPG2.7APG
Rudy Gobert10.9PPG11.5RPG1.7APG
Ayo Dosunmu14.8PPG3.4RPG3.6APG
SAS1 OUT
De'Aaron Fox18.6PPG3.8RPG6.2APG
Devin Vassell13.9PPG4.0RPG2.5APG
Stephon Castle16.7PPG5.3RPG7.4APG
Victor Wembanyama25.0PPG11.5RPG3.1APG
Julian Champagnie11.1PPG5.8RPG1.5APG
AI Intelligence Analysis
NEUTRAL -2YELLOW ZONE17.9% WR (n=8)
Simulation contains DATA_INTEGRITY error (De'Aaron Fox listed as SAS starter when he plays for SAC), not resimulated despite Anthony Edwards GTD (knee) uncertainty, and extreme spread edge (-9.6pts) contradicts team quality gap (SAS net_rtg +8.2 vs MIN +3.4 = ~4.8pt diff), signaling stale or corrupted model data unsuitable for high-stakes betting.
Key Factors
- Data error: De'Aaron Fox (SAC player) listed in SAS lineup — simulation data corrupted
- MIN Anthony Edwards GTD status unknown, simulation not resimulated (resim=FALSE)
- SAS team quality: net_rtg +8.2 (62-20 record, 75.6 win %), MIN quality: net_rtg +3.4 (49-33, 59.8 win %)
- Spread edge -9.6pts (model -3.3 vs market -9.5) suggests extreme disagreement, but unreliable given data errors
- Line movement: 3pts toward MIN (opening -7.5 to current -10.5), sharp money on MIN per 'toward_home' direction
Risk Factors
- Lineup data integrity failure — simulation outputs cannot be trusted with wrong players in starters
- Resimulation failure for high-impact player (Edwards GTD) means latest injury data not incorporated
- Extreme spread disagreement could indicate model is severely broken or outdated rather than capturing hidden value
DATA INTEGRITYRESIM FRESH MISSINGHIGH EDGE WARNINGLINEUP ERROR
Edge Analysis
Moneyline
MIN 50.0%
-9.6 pts
Spread
-9.5
-9.6 pts
Total
218.5
-2.9 pts
How this prediction was generated: This page shows output from the Olympus Bets NBA 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 →