MacIntyre, Robert vs Matsuyama, Hideki prediction for May 27, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects Matsuyama, Hideki 34 - MacIntyre, Robert 52. MacIntyre, Robert is favored with a 59.0% win probability. The spread is 0.11.
Matsuyama, Hideki
+1.10
Strokes Gained / Round
VS
H2H • Charles Schwab Challenge
MacIntyre, Robert
+1.24
Strokes Gained / Round
Head-to-Head Win Probability
Matsuyama, HidekiMacIntyre, Robert
-117
Best Odds
+9.4%
Edge
1.0u MEDIUM
Sizing
Projected Points Range 10th – 90th percentile
MacIntyre, Robert
455259
Matsuyama, Hideki
273441
Tournament Context
Event
Charles Schwab Challenge
Course
Colonial CC
Field
132 players
Wind
10 mph
Temp
86°F
Conditions
harder (+0.4)
Player Profile — MacIntyre, Robert
Strokes Gained
+1.24/round
Tour Elite
Course Fit
neutral
+0.119 SG adj
Expected Finish
52th / 132
Matchup Analysis
MacIntyre, Robert
+1.24 SG
EF 52th
Skill Gap
+0.11 SG/round
tight edge for MacIntyre, Robert
Matsuyama, Hideki
+1.10 SG
EF 34th · Tour Elite
Edge Breakdown
Our Model
59.0%
Books Say
53.9%
Edge
+9.4%
MacIntyre, Robert vs Matsuyama, Hideki: Model gives MacIntyre, Robert 59.0% win probability vs 53.9% implied (+9.4% edge). Skill advantage: +0.11 SG/round. Expected finish: 52.
AI Intelligence Analysis
NEUTRAL +0
MacIntyre's elite baseline (1.24 SG) + modest skill advantage (+0.11 SG) + positive fit (+0.119) yield a 9.2% edge that is narrow given the quality of matchup; too compressed.
Key Factors
- Model: 58.9% vs 53.9% implied (+9.2% edge)
- MacIntyre SG: +1.24 (elite)
- Skill advantage: +0.11 (modest)
- Course fit: +0.119 (positive but not dominant)
Risk Factors
- 9.2% edge is narrow despite MacIntyre's quality
- Skill advantage (+0.11) is marginal
- Matsuyama is moderate-quality player
COMPRESSED EDGE
Edge Analysis
Moneyline
MacIntyre, Robert 59.0%
+9.4 pts
Spread
+0.1
+9.4 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 →