Rose, Justin vs Thomas, Justin prediction for May 13, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects Thomas, Justin 77 - Rose, Justin 63. Rose, Justin is favored with a 50.5% win probability. The spread is 0.1.
Thomas, Justin
+0.87
Strokes Gained / Round
VS
H2H • PGA Championship
Rose, Justin
+0.97
Strokes Gained / Round
Head-to-Head Win Probability
Thomas, JustinRose, Justin
+122
Best Odds
+12.2%
Edge
1.0u HIGH
Sizing
Projected Points Range 10th – 90th percentile
Rose, Justin
566370
Thomas, Justin
707784
Tournament Context
Event
PGA Championship
Course
Aronimink Golf Club
Field
156 players
Player Profile — Rose, Justin
Strokes Gained
+0.97/round
Above Avg
Course Fit
excellent
+1.055 SG adj
Expected Finish
63th / 156
Matchup Analysis
Rose, Justin
+0.97 SG
EF 63th
Skill Gap
+0.10 SG/round
tight edge for Rose, Justin
Thomas, Justin
+0.87 SG
EF 77th · Above Avg
Edge Breakdown
Our Model
50.5%
Books Say
45.1%
Edge
+12.2%
Rose, Justin vs Thomas, Justin: Model gives Rose, Justin 50.5% win probability vs 45.0% implied (+12.2% edge). Skill advantage: +0.10 SG/round. Expected finish: 63.
AI Intelligence Analysis
STRONG BET +2GREEN ZONE0.6% WR (n=284)
Rose's strong course fit (+1.998) combined with superior approach play and finish positioning crushes Thomas in Aronimink matchup.
Key Factors
- Course fit differential: +0.935 SG (Rose +1.998 vs Thomas +1.063) = strong advantage
- Finish position edge: Rose EF 38 vs Thomas EF 67.1 = 29-position gap
- Approach play: Rose SG-APP +0.47 vs Thomas +0.39 = relevant at Aronimink
- Edge: +24.5% (58.4% model vs 46.9% implied) = solid value at +113
Risk Factors
- Rose is 46 years old; single-event variance higher for aging players
- Thomas has major championship pedigree; can elevate vs top competition
- H2H correlation risk if both play near expectations
LINE VALUECOURSE FIT SUPPORTEDEXPERIENCE EDGE
Edge Analysis
Moneyline
Rose, Justin 50.5%
+12.2 pts
Spread
+0.1
+12.2 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. Full methodology →