Rai, Aaron vs Scott, Adam prediction for June 16, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects Scott, Adam 37 - Rai, Aaron 82. Rai, Aaron is favored with a 56.8% win probability. The spread is -0.31.
Scott, Adam
+1.12
Strokes Gained / Round
VS
H2H • U.S. Open
Rai, Aaron
+0.96
Strokes Gained / Round
Head-to-Head Win Probability
Scott, AdamRai, Aaron
-111
Best Odds
+8.0%
Edge
1.0u MEDIUM
Sizing
Projected Points Range 10th – 90th percentile
Rai, Aaron
758289
Scott, Adam
303744
Tournament Context
Event
U.S. Open
Course
Shinnecock Hills Golf Club
Field
156 players
Player Profile — Rai, Aaron
Strokes Gained
+0.96/round
Above Avg
Course Fit
excellent
+0.307 SG adj
Expected Finish
82th / 156
Matchup Analysis
Rai, Aaron
+0.96 SG
EF 82th
Skill Gap
-0.31 SG/round
tight edge for Scott, Adam
Scott, Adam
+1.12 SG
EF 37th · Tour Elite
Edge Breakdown
Our Model
56.8%
Books Say
52.6%
Edge
+8.0%
Rai, Aaron vs Scott, Adam: Model gives Rai, Aaron 56.8% win probability vs 52.6% implied (+8.0% edge). Skill advantage: -0.31 SG/round. Expected finish: 82.
AI Intelligence Analysis
NEUTRAL -1
Edge is PURE course-fit play (+0.307 Rai vs -0.018 Scott) with NEGATIVE skill gap (-0.306 SG/round to Rai); market correctly pricing this as near coin-flip (53.5% vs 56.9% model).
Key Factors
- Course fit differential: Rai +0.307 vs Scott -0.018 (0.325-point Shinnecock advantage)
- Skill differential: -0.306 SG/round (Rai WORSE on fundamentals)
- Expected finish essentially equal: Rai 82.5 vs Scott 82.0 (0.5-stroke gap)
- 6.3% edge is marginal and venue-dependent; no fundamental advantage
Risk Factors
- Rai has negative skill advantage; Scott is fundamentally stronger player
- Expected finish gap only 0.5 strokes—data suggests matchup is essentially even
- Course-fit-only edges high variance in single events; major championships amplify volatility
COURSE FIT ONLY EDGENEGATIVE SKILL GAPEXPECTED FINISH CONFLICTMARGINAL PROBABILITY
Edge Analysis
Moneyline
Rai, Aaron 56.8%
+8.0 pts
Spread
-0.3
+8.0 pts
How this prediction was generated: This page shows output from the Olympus Bets PGA Tour Golf 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. Probabilities are calibrated using Bayesian methods and sized via the Kelly Criterion. Full methodology →