Woodland, Gary vs Finau, Tony prediction for May 27, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects Finau, Tony 39 - Woodland, Gary 55. Woodland, Gary is favored with a 58.3% win probability. The spread is 0.46.
Finau, Tony
+0.24
Strokes Gained / Round
VS
H2H • Charles Schwab Challenge
Woodland, Gary
+0.70
Strokes Gained / Round
Head-to-Head Win Probability
Finau, TonyWoodland, Gary
-105
Best Odds
+16.7%
Edge
1.5u ELITE
Sizing
Projected Points Range 10th – 90th percentile
Woodland, Gary
485562
Finau, Tony
323946
Tournament Context
Event
Charles Schwab Challenge
Course
Colonial CC
Field
132 players
Wind
10 mph
Temp
86°F
Conditions
harder (+0.4)
Player Profile — Woodland, Gary
Strokes Gained
+0.70/round
Above Avg
Course Fit
excellent
+0.518 SG adj
Expected Finish
55th / 132
Matchup Analysis
Woodland, Gary
+0.70 SG
EF 55th
Skill Gap
+0.46 SG/round
meaningful edge for Woodland, Gary
Finau, Tony
+0.24 SG
EF 39th · Tour Avg
Edge Breakdown
Our Model
58.3%
Books Say
51.2%
Edge
+16.7%
Woodland, Gary vs Finau, Tony: Model gives Woodland, Gary 58.3% win probability vs 51.2% implied (+13.7% edge). Skill advantage: +0.46 SG/round. Expected finish: 55. AI: strong recent form; course specialist.
AI Intelligence Analysis
LEAN +0
Woodland's course fit (+0.518) is offset by a significant skill advantage to Finau (+0.459 SG differential); narrow 13.3% edge reflects tight match despite fit advantage.
Key Factors
- Model: 58.0% vs 51.2% implied (+13.3% edge)
- Course fit: +0.518 (Woodland advantage)
- Skill differential: +0.459 to Finau (large, against Woodland)
- Expected finish: Woodland 55 vs Finau 68
Risk Factors
- Finau's massive skill advantage (+0.459 SG) overwhelms Woodland's fit edge
- Finau is higher-quality player despite negative fit
- Narrow 13.3% edge is vulnerable to variance
CONTRARIAN FIT
Edge Analysis
Moneyline
Woodland, Gary 58.3%
+16.7 pts
Spread
+0.5
+16.7 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 →