SAS vs OKC prediction for May 18, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects OKC 109.3 - SAS 102.5. OKC is favored with a 69.4% win probability. The spread is -6.5 and the total is 219.5.
OKC
109.3
Projected Score
VS
O/U 219.5
SAS
102.5
Projected Score
Win Probability
OKCSAS
-6.5
Spread (OKC)
219.5
Total Line
10,000
Simulations
SAS W4OKC W5
Calibrated accuracy at this confidence: 77.5% (1,251 games)
Projected Points Range 10th – 90th percentile
SAS
93102112
OKC
99109119
Projected
OKC 109.3 — SAS 102.5
Actual
OKC 115 — SAS 122
Pick Results
Keldon Johnson OVER 8.5 pointsnba_player_pointsWIN+1.36u
Julian Champagnie OVER 8.5 pointsnba_player_pointsWIN+1.30u
Dylan Harper UNDER 19.5 pranba_player_points_rebounds_assistsLOSS-1.50u
Starting Lineups
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
OKC1 OUT
Shai Gilgeous-Alexander31.1PPG4.3RPG6.6APG
Chet Holmgren17.1PPG8.9RPG1.7APG
Jalen Williams17.1PPG4.6RPG5.5APG
Luguentz Dort8.3PPG3.6RPG1.2APG
Cason Wallace8.6PPG3.1RPG2.6APG
AI Intelligence Analysis
NEUTRAL -1YELLOW ZONE80.4% WR (n=14)
Model failed to account for De'Aaron Fox's All-NBA tier injury (documented in injury report but listed as starter), overstating OKC's win probability by ~5-6 points; game already resolved (SAS won 122-115 2OT), making this a post-hoc analysis of model failure, not a betting opportunity.
Key Factors
- De'Aaron Fox (All-NBA, 19pts projected) was OUT per ESPN 2026-05-19 report but still listed in model's SAS starting 5 — ~6.5pt impact not incorporated
- OKC net rating +11.8 vs SAS +8.5 (3.29pt quality gap) suggested OKC dominance, but Fox absence eliminated that advantage
- Victor Wembanyama overwhelmed OKC defense: 41pts, 24rebs, 2OT performance — model may have undervalued elite defensive ceiling in playoff environment
- Dylan Harper's 7 steals (playoff record) indicates SAS defense played at historically elite level despite Fox absence
- Simulation predicted OKC +6.8 margin; actual result SAS +7.0 (14.8pt swing) — among largest prediction errors in recent tracked data
Risk Factors
- Data integrity failure: injury data not properly synchronized with simulation lineup inputs — Fox injury was documented but not reflected in starter projection
- Model likely overweights regular season net ratings in playoff contexts where coaching adjustments and intensity shifts create outsized outcomes
- No market odds data available to assess line value (fetched post-game)
DATA INTEGRITYRESOLVED GAMEINJURY IMPACTMODEL FAILUREALL STAR OUT
Edge Analysis
Moneyline
OKC 69.4%
+0.2 pts
Spread
-6.5
+0.2 pts
Total
219.5
-7.7 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 →