McCarthy, Denny vs Hisatsune, Ryo prediction for May 5, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects Hisatsune, Ryo 37 - McCarthy, Denny 30. McCarthy, Denny is favored with a 52.0% win probability. The spread is -0.07.
Hisatsune, Ryo
+0.57
Strokes Gained / Round
VS
H2H • Truist Championship
McCarthy, Denny
+0.51
Strokes Gained / Round
Head-to-Head Win Probability
Hisatsune, RyoMcCarthy, Denny
+112
Best Odds
+10.2%
Edge
1.0u HIGH
Sizing
Projected Points Range 10th – 90th percentile
McCarthy, Denny
233037
Hisatsune, Ryo
303744
Tournament Context
Event
Truist Championship
Course
Quail Hollow Club
Field
72 players
Wind
12 mph
Temp
76°F
Conditions
harder (+0.6)
Player Profile — McCarthy, Denny
Strokes Gained
+0.51/round
Above Avg
Course Fit
excellent
+0.869 SG adj
Expected Finish
30th / 72
Matchup Analysis
McCarthy, Denny
+0.51 SG
EF 30th
Skill Gap
-0.07 SG/round
essentially a coin flip
Hisatsune, Ryo
+0.57 SG
EF 37th · Above Avg
Edge Breakdown
Our Model
52.0%
Books Say
47.2%
Edge
+10.2%
McCarthy, Denny vs Hisatsune, Ryo: Model gives McCarthy, Denny 52.0% win probability vs 47.2% implied (+10.2% edge). Expected finish: 30.
AI Intelligence Analysis
STRONG BET +1
McCarthy 51.7% h2h vs 44.4% implied = +16.3% edge; McCarthy's +0.51 SG total + +0.87 course fit (strong for McCarthy) drives edge despite skill near-parity with Hisatsune.
Key Factors
- McCarthy course fit +0.869 SG (strong local advantage)
- McCarthy SG +0.51 total (EF 30.5, mid-pack)
- Skill diff near-zero (-0.074 SG)
- BetOnline +125 (44.4% implied) vs 51.7% model = +16.3% edge
Risk Factors
- McCarthy's overall skill +0.51 SG is mid-tier; edge is pure course fit
- Hisatsune's profile unknown; could be comparable or stronger
- Field volatility in Rounds 2-4 may undermine course-fit edge
Edge Analysis
Moneyline
McCarthy, Denny 52.0%
+10.2 pts
Spread
-0.1
+10.2 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 →