Burns, Sam vs Cantlay, Patrick prediction for May 5, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects Cantlay, Patrick 34 - Burns, Sam 25. Burns, Sam is favored with a 58.4% win probability. The spread is -0.07.
Cantlay, Patrick
+1.44
Strokes Gained / Round
VS
H2H • Truist Championship
Burns, Sam
+1.38
Strokes Gained / Round
Head-to-Head Win Probability
Cantlay, PatrickBurns, Sam
-103
Best Odds
+15.0%
Edge
1.5u ELITE
Sizing
Projected Points Range 10th – 90th percentile
Burns, Sam
182532
Cantlay, Patrick
273441
Tournament Context
Event
Truist Championship
Course
Quail Hollow Club
Field
72 players
Wind
11 mph
Temp
76°F
Conditions
harder (+0.5)
Player Profile — Burns, Sam
Strokes Gained
+1.38/round
Tour Elite
Course Fit
excellent
+0.333 SG adj
Expected Finish
25th / 72
Matchup Analysis
Burns, Sam
+1.38 SG
EF 25th
Skill Gap
-0.07 SG/round
essentially a coin flip
Cantlay, Patrick
+1.44 SG
EF 34th · Tour Elite
Edge Breakdown
Our Model
58.4%
Books Say
50.7%
Edge
+15.0%
Burns, Sam vs Cantlay, Patrick: Model gives Burns, Sam 58.4% win probability vs 50.7% implied (+15.0% edge). Expected finish: 25.
AI Intelligence Analysis
STRONG BET +1
Burns 57.8% h2h vs 51.2% implied = +12.9% edge; Burns' +1.38 SG total + modest +0.33 course fit + near-parity skill (-0.073 SG) = balanced matchup edge.
Key Factors
- Burns SG +1.38 (strong mid-tier)
- Cantlay strong player but negative course fit (-0.439 SG as shown in field data)
- Skill diff near-zero (-0.073 SG, negligible)
- BetMGM -105 (51.2% implied) vs 57.8% model = +12.9% edge
Risk Factors
- Cantlay's negative course fit (-0.439 SG) is main advantage for Burns; must be accurate
- Skill gap negligible; entire edge depends on venue adjustment
- Cantlay is elite player with veteran experience; variance risk
Edge Analysis
Moneyline
Burns, Sam 58.4%
+15.0 pts
Spread
-0.1
+15.0 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. Full methodology →