Burns, Sam vs Reed, Patrick prediction for May 13, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects Reed, Patrick 98 - Burns, Sam 83. Burns, Sam is favored with a 62.0% win probability. The spread is 0.32.
Reed, Patrick
+0.97
Strokes Gained / Round
VS
H2H • PGA Championship
Burns, Sam
+1.30
Strokes Gained / Round
Head-to-Head Win Probability
Reed, PatrickBurns, Sam
-125
Best Odds
+11.5%
Edge
1.5u HIGH
Sizing
Projected Points Range 10th – 90th percentile
Burns, Sam
768390
Reed, Patrick
9198105
Tournament Context
Event
PGA Championship
Course
Aronimink Golf Club
Field
156 players
Player Profile — Burns, Sam
Strokes Gained
+1.30/round
Tour Elite
Course Fit
neutral
+0.097 SG adj
Expected Finish
83th / 156
Matchup Analysis
Burns, Sam
+1.30 SG
EF 83th
Skill Gap
+0.32 SG/round
tight edge for Burns, Sam
Reed, Patrick
+0.97 SG
EF 98th · Above Avg
Edge Breakdown
Our Model
62.0%
Books Say
55.6%
Edge
+11.5%
Burns, Sam vs Reed, Patrick: Model gives Burns, Sam 62.0% win probability vs 55.6% implied (+11.5% edge). Skill advantage: +0.32 SG/round. Expected finish: 83.
AI Intelligence Analysis
STRONG BET +1GREEN ZONE0.6% WR (n=284)
Burns's skill advantage (+0.318 SG/round) overcomes Reed's rough course fit; Burns's superior approach play drives edge.
Key Factors
- Skill gap: +0.318 SG/round (Burns +1.297 vs Reed +0.969)
- Course fit differential: +0.604 SG (Burns +0.097 vs Reed -0.507) = Reed is POORLY fit
- Finish position: Burns EF 83.8 vs Reed EF 111.2 = 27-position gap (massive)
- Edge: +19.8% (66.5% model vs 55.6% implied) = solid at -125
Risk Factors
- Reed has major championship experience and can elevate
- Single-event tournament variance can favor underdog
- If course setup heavily penalizes longer hitters, Reed's short-game touch might help
LINE VALUECOURSE FIT SUPPORTEDFINISH POSITION GAP
Edge Analysis
Moneyline
Burns, Sam 62.0%
+11.5 pts
Spread
+0.3
+11.5 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 →