Coody, Pierceson vs Thompson, Davis prediction for May 21, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects Thompson, Davis 76 - Coody, Pierceson 69. Coody, Pierceson is favored with a 55.5% win probability. The spread is -0.04.
Thompson, Davis
+0.43
Strokes Gained / Round
VS
H2H • THE CJ CUP Byron Nelson
Coody, Pierceson
+0.55
Strokes Gained / Round
Head-to-Head Win Probability
Thompson, DavisCoody, Pierceson
-103
Best Odds
+9.4%
Edge
1.0u MEDIUM
Sizing
Projected Points Range 10th – 90th percentile
Coody, Pierceson
626976
Thompson, Davis
697683
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 — Coody, Pierceson
Strokes Gained
+0.55/round
Above Avg
Course Fit
excellent
+0.332 SG adj
Expected Finish
69th / 147
Matchup Analysis
Coody, Pierceson
+0.55 SG
EF 69th
Skill Gap
-0.04 SG/round
essentially a coin flip
Thompson, Davis
+0.43 SG
EF 76th · Tour Avg
Edge Breakdown
Our Model
55.5%
Books Say
50.7%
Edge
+9.4%
Coody, Pierceson vs Thompson, Davis: Model gives Coody, Pierceson 55.5% win probability vs 50.7% implied (+9.4% edge). Expected finish: 69.
AI Intelligence Analysis
LEAN +0YELLOW ZONE0.5% WR (n=380)
Coody's +0.55 SG and +0.332 course fit vs Thompson's +0.588 SG create conflicting signals; +8.3% edge (54.97% vs 50.74%) too modest with negative odds (-103) to justify strong play.
Key Factors
- SG total Coody: +0.55 (advantage)
- SG total Thompson: +0.588 (stronger advantage)
- Course fit: +0.332 (Coody advantage)
- EF: 69.1 vs 71.1 (both similar)
- Edge: +8.3% at -103 Betcris (modest, negative odds)
Risk Factors
- Thompson's +0.588 SG is stronger than Coody's +0.55
- EF parity suggests coin-flip
- Negative odds (-103) unfavorable for modest edge
CONFLICTING SIGNALSMODEST EDGE
Edge Analysis
Moneyline
Coody, Pierceson 55.5%
+9.4 pts
Spread
-0.0
+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 →