PGA Tour Golf

Bhatia, Akshay vs Fowler, Rickie Prediction

June 18, 2026

10,000 Monte Carlo simulations

Bhatia, Akshay vs Fowler, Rickie prediction for June 18, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects Fowler, Rickie 42 - Bhatia, Akshay 98. Bhatia, Akshay is favored with a 59.8% win probability. The spread is 0.11.

Fowler, Rickie
+0.78
Strokes Gained / Round
VS H2H • U.S. Open
Bhatia, Akshay
+0.95
Strokes Gained / Round
Head-to-Head Win Probability
40.2%
59.8%
Fowler, RickieBhatia, Akshay
-105
Best Odds
+16.7%
Edge
1.5u ELITE
Sizing
FINALFowler, Rickie (T31) def Bhatia, Akshay (T53)

Projected Points Range 10th – 90th percentile

Bhatia, Akshay
9198105
Fowler, Rickie
354249

Tournament Context

Event
U.S. Open
Course
Shinnecock Hills Golf Club
Field
156 players

Player Profile — Bhatia, Akshay

Strokes Gained
+0.95/round
Above Avg
Course Fit
poor
-0.236 SG adj
Expected Finish
98th / 156

Matchup Analysis

Bhatia, Akshay
+0.95 SG
EF 98th
Skill Gap
+0.11 SG/round
tight edge for Bhatia, Akshay
Fowler, Rickie
+0.78 SG
EF 42th · Above Avg

Edge Breakdown

Our Model
59.8%
Books Say
51.2%
Edge
+16.7%

Bhatia, Akshay vs Fowler, Rickie: Model gives Bhatia, Akshay 59.8% win probability vs 51.2% implied (+16.7% edge). Skill advantage: +0.11 SG/round. Expected finish: 98.

Edge Analysis

Moneyline
Bhatia, Akshay 59.8%
+16.7 pts
Spread
+0.1
+16.7 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 →

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