Brennan, Michael vs Greyserman, Max prediction for May 21, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects Greyserman, Max 78 - Brennan, Michael 81. Brennan, Michael is favored with a 57.4% win probability. The spread is -0.18.
Greyserman, Max
+0.56
Strokes Gained / Round
VS
H2H • THE CJ CUP Byron Nelson
Brennan, Michael
+0.22
Strokes Gained / Round
Head-to-Head Win Probability
Greyserman, MaxBrennan, Michael
-115
Best Odds
+7.4%
Edge
1.0u MEDIUM
Sizing
Projected Points Range 10th – 90th percentile
Brennan, Michael
748188
Greyserman, Max
717885
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 — Brennan, Michael
Strokes Gained
+0.22/round
Tour Avg
Course Fit
good
+0.281 SG adj
Expected Finish
81th / 147
Matchup Analysis
Brennan, Michael
+0.22 SG
EF 81th
Skill Gap
-0.18 SG/round
tight edge for Greyserman, Max
Greyserman, Max
+0.56 SG
EF 78th · Above Avg
Edge Breakdown
Our Model
57.4%
Books Say
53.5%
Edge
+7.4%
Brennan, Michael vs Greyserman, Max: Model gives Brennan, Michael 57.4% win probability vs 53.5% implied (+7.4% edge). Skill advantage: -0.18 SG/round. Expected finish: 81.
AI Intelligence Analysis
NEUTRAL +0YELLOW ZONE0.6% WR (n=380)
Model 57.44% vs market 53.49% creates +7.4% edge, but -0.179 skill gap, mid-field EF parity (81.0 both), and negative odds (-115) on modest edge indicate uncertain value.
Key Factors
- Skill gap: -0.179 to Greyserman (Greyserman better)
- Course fit: +0.281 (Brennan advantage)
- SG total: +0.216 (Brennan advantage)
- EF: 81.0 both (parity)
- Edge: +7.4% at -115 Bovada (expensive)
Risk Factors
- Greyserman -0.179 skill advantage contradicts finish matrix
- EF parity (81.0 both) suggests coin-flip
- Negative odds (-115) expensive for modest edge
CONFLICTING SIGNALSEF PARITY
Edge Analysis
Moneyline
Brennan, Michael 57.4%
+7.4 pts
Spread
-0.2
+7.4 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 →