Thompson, Davis vs Hisatsune, Ryo prediction for May 21, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects Hisatsune, Ryo 58 - Thompson, Davis 72. Thompson, Davis is favored with a 54.4% win probability. The spread is -0.02.
Hisatsune, Ryo
+0.66
Strokes Gained / Round
VS
H2H • THE CJ CUP Byron Nelson
Thompson, Davis
+0.59
Strokes Gained / Round
Head-to-Head Win Probability
Hisatsune, RyoThompson, Davis
+110
Best Odds
+14.1%
Edge
1.5u HIGH
Sizing
Projected Points Range 10th – 90th percentile
Thompson, Davis
657279
Hisatsune, Ryo
515865
Tournament Context
Event
THE CJ CUP Byron Nelson
Course
TPC Craig Ranch
Field
147 players
Wind
15 mph
Temp
82°F
Conditions
harder (+0.8)
Player Profile — Thompson, Davis
Strokes Gained
+0.59/round
Above Avg
Course Fit
good
+0.225 SG adj
Expected Finish
72th / 147
Matchup Analysis
Thompson, Davis
+0.59 SG
EF 72th
Skill Gap
-0.02 SG/round
essentially a coin flip
Hisatsune, Ryo
+0.66 SG
EF 58th · Above Avg
Edge Breakdown
Our Model
54.4%
Books Say
47.6%
Edge
+14.1%
Thompson, Davis vs Hisatsune, Ryo: Model gives Thompson, Davis 54.4% win probability vs 47.6% implied (+14.1% edge). Expected finish: 72.
AI Intelligence Analysis
LEAN +0YELLOW ZONE0.5% WR (n=380)
Thompson's +0.588 SG total but -0.019 skill gap creates 54.2% finish prob vs 47.62% market (+13.8% edge); mid-field skill parity makes this a lean-only play.
Key Factors
- SG total: +0.588 (Thompson has overall advantage)
- Skill gap: -0.019 (near-zero; essentially matched)
- Course fit: +0.225 (Thompson minor advantage)
- EF: 71.1 both (tight finish positions)
- Edge: +13.8% but undermined by EF parity
Risk Factors
- EF 71.1 for both suggests coin-flip upside; model edge may be statistical noise
- Skill parity (-0.019) means no clear winner
- Caesars +110 odds suggest public may correctly value as close match
TIGHT MATCHUPEF PARITY
Edge Analysis
Moneyline
Thompson, Davis 54.4%
+14.1 pts
Spread
-0.0
+14.1 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 →