PGA Tour Golf

Potgieter, Aldrich vs Hojgaard, Rasmus Prediction

July 21, 2026

10,000 Monte Carlo simulations

Potgieter, Aldrich vs Hojgaard, Rasmus prediction for July 21, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects Hojgaard, Rasmus 98 - Potgieter, Aldrich 93. Potgieter, Aldrich is favored with a 61.7% win probability. The spread is -0.01.

Hojgaard, Rasmus
+0.14
Strokes Gained / Round
VS H2H • 3M Open
Potgieter, Aldrich
+0.15
Strokes Gained / Round
Head-to-Head Win Probability
38.3%
61.7%
Hojgaard, RasmusPotgieter, Aldrich
-120
Best Odds
FINALHojgaard, Rasmus (T41) def Potgieter, Aldrich (T141)

Projected Points Range 10th – 90th percentile

Potgieter, Aldrich
8693100
Hojgaard, Rasmus
9198105

Tournament Context

Event
3M Open
Course
TPC Twin Cities
Field
144 players
Wind
12 mph
Temp
81°F
Conditions
harder (+0.6)

AI Intelligence Analysis

STRONG BET +1
Potgieter's strong course fit (+0.15 better than Hojgaard) and relative tournament form edge (62.1% model vs 54.5% market) represents genuine value; slight skill parity (-0.012) not a factor.

Key Factors

  • Model edge: +13.9% probability (62.1% vs 54.5%) — second-largest edge on slate
  • Course fit: Potgieter -0.15 vs Hojgaard worse implied fit = Potgieter benefit at Twin Cities
  • Skill parity: -0.012 SG/round difference is noise; execution and consistency matter more
  • Odds -120 (caesars): implies 54.55%, our model 62.14% = +759 bps edge
  • Expected finish: Potgieter 92.8 (lower is better) suggests deeper field player with course advantage

Risk Factors

  • Hojgaard is younger (potentially higher ceiling); form variance could swing this
  • Potgieter's -0.15 course fit is negative but slightly — not a course fit mismatch, just neutral
  • Both players in 90+ expected finish range suggests mid-field matchup with higher variance
Sharp MoneyWith ModelSolid mid-field edge; market has not fully priced Potgieter's course advantage

Edge Analysis

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Edge Analysis
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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. Probabilities are calibrated using Bayesian methods and sized via the Kelly Criterion. Full methodology →

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