Kim, Si Woo vs Fowler, Rickie prediction for May 13, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects Fowler, Rickie 80 - Kim, Si Woo 80. Kim, Si Woo is favored with a 55.7% win probability. The spread is -0.05.
Fowler, Rickie
+1.38
Strokes Gained / Round
VS
H2H • PGA Championship
Kim, Si Woo
+1.32
Strokes Gained / Round
Head-to-Head Win Probability
Fowler, RickieKim, Si Woo
+100
Best Odds
+11.4%
Edge
1.0u HIGH
Sizing
Projected Points Range 10th – 90th percentile
Kim, Si Woo
738087
Fowler, Rickie
738087
Tournament Context
Event
PGA Championship
Course
Aronimink Golf Club
Field
156 players
Player Profile — Kim, Si Woo
Strokes Gained
+1.32/round
Tour Elite
Course Fit
good
+0.176 SG adj
Expected Finish
80th / 156
Matchup Analysis
Kim, Si Woo
+1.32 SG
EF 80th
Skill Gap
-0.05 SG/round
essentially a coin flip
Fowler, Rickie
+1.38 SG
EF 80th · Tour Elite
Edge Breakdown
Our Model
55.7%
Books Say
50.0%
Edge
+11.4%
Kim, Si Woo vs Fowler, Rickie: Model gives Kim, Si Woo 55.7% win probability vs 50.0% implied (+11.4% edge). Expected finish: 80.
AI Intelligence Analysis
NEUTRAL +0RED ZONE0.5% WR (n=100)
Kim's SG data (-0.051 skill disadvantage) contradicts model's 55.5% win probability; edge is data artifact, not real.
Key Factors
- Skill disadvantage: Kim -0.057 SG/round (Kim +1.323 vs Fowler +1.38)
- Finish position: Kim EF 79.9 vs Fowler EF 80.6 (parity)
- Edge is in WRONG DIRECTION; Fowler should be favored
- Model giving edge to worse player = RED FLAG
Risk Factors
- Edge contradicted by fundamental skill and finish data
- Model likely overfitting on H2H matrix noise
- Market odds (50-50) correct; model wrong
MODEL ERRORSKILL DISADVANTAGESUSPICIOUS EDGESKIP
Edge Analysis
Moneyline
Kim, Si Woo 55.7%
+11.4 pts
Spread
-0.1
+11.4 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 →