Im, Sungjae vs Finau, Tony prediction for May 5, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects Finau, Tony 61 - Im, Sungjae 32. Im, Sungjae is favored with a 75.0% win probability. The spread is 0.09.
Finau, Tony
-0.04
Strokes Gained / Round
VS
H2H • Truist Championship
Im, Sungjae
+0.04
Strokes Gained / Round
Head-to-Head Win Probability
Finau, TonyIm, Sungjae
-145
Best Odds
+26.8%
Edge
2.0u HIGH
Sizing
Projected Points Range 10th – 90th percentile
Im, Sungjae
253239
Finau, Tony
546168
Tournament Context
Event
Truist Championship
Course
Quail Hollow Club
Field
72 players
Wind
11 mph
Temp
76°F
Conditions
harder (+0.5)
Player Profile — Im, Sungjae
Strokes Gained
+0.04/round
Tour Avg
Course Fit
excellent
+1.129 SG adj
Expected Finish
32th / 72
Matchup Analysis
Im, Sungjae
+0.04 SG
EF 32th
Skill Gap
+0.09 SG/round
essentially a coin flip
Finau, Tony
-0.04 SG
EF 61th · Below Avg
Edge Breakdown
Our Model
75.0%
Books Say
59.2%
Edge
+26.8%
Im, Sungjae vs Finau, Tony: Model gives Im, Sungjae 75.0% win probability vs 59.2% implied (+26.8% edge). Expected finish: 32.
AI Intelligence Analysis
STRONG BET +1
Im 75.1% finish probability vs 59.0% implied = +27.2% edge; Im's +1.13 course fit + slightly stronger SG profile (0.045 total) beats Finau in bent-grass/approach environment.
Key Factors
- Im course fit +1.13 SG vs Finau's data unavailable; Im has EF 32.8 (solid mid-pack)
- Skill diff 0.09 SG slightly favors Im (within margin)
- Pinnacle -144 (59% implied) vs 75.1% model = elite-tier H2H edge
- Expected finish differential (Im 32.8 vs Finau ~35+) favors Im in h2h variance
Risk Factors
- Very close skill levels (0.045 SG for Im, near-zero for Finau) — true h2h may be tighter
- Course fit is main edge; if Finau is strong putter/approach player, edge shrinks
- Finau plays well in windy conditions (not Im's strength) — Round 2 (20.9 mph) is risk
Edge Analysis
Moneyline
Im, Sungjae 75.0%
+26.8 pts
Spread
+0.1
+26.8 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 →