CF Montreal vs Nashville SC prediction for July 23, 2026: Our Monte Carlo simulation ran 5,000 game iterations and projects Nashville SC 1.94 - CF Montreal 1.05. Nashville SC is favored with a 57.4% win probability. Expected total goals: 3.0..
Nashville SC
1.94
Projected Goals
VS
3.0 total
CF Montreal
1.05
Projected Goals
Match Outcome Probabilities
Nashville SCDrawCF Montreal
Calibrated accuracy at this confidence: 62.8% (1,163 games)
Projected Goals Range 10th – 90th percentile
CF Montreal
0.31.11.8
Nashville SC
1.21.92.7
Expected Goals (xG)
Nashville SC1.94
CF Montreal1.05
19.0Shots16.3
6.9On Target5.8
6.0Corners5.7
Goal Probabilities
Over 0.5
96.6%
Over 1.5
78.2%
Over 2.5
55.5%
Over 3.5
42.7%
Under 2.5
44.5%
BTTS
60.5%
Most Likely Scores
1-1
11.2%
2-1
10.1%
2-0
9.6%
1-0
9.0%
3-1
6.5%
Match Context
MLSMedium
Nashville SC
1.52
Draw
4.63
CF Montreal
6.14
AI Intelligence Analysis
NEUTRAL -1
Market overvalues Nashville home by 8.36% (57.44% model vs 65.8% market), but historically weak home ML + high draw probability (23.11%) eliminate any actionable advantage despite xG dominance
Key Factors
- Strong xG mismatch: Nashville 1.94 xGF vs Montreal 1.05 xGF (+0.89 advantage — largest on slate)
- Market overvaluation: Nashville model 57.44% win prob but market 65.8% implied (8.36% gap favoring away)
- High draw probability: Model 23.11% draw frequency — if correct, reduces home win probability from 57.44% to ~44% of total outcomes
- Home ML in RED: SOCCER | ml | home | any | any | any at a supportive track record
- Odds compression: -220 Nashville already reflects market confidence; limited value even if model correct
Risk Factors
- Draw frequency contradiction: H2H shows 0% draws but model shows 23.11% — unresolved data integrity issue
- historically weak trap: Home ML has 43.3% historical WR despite xG edge; statistical evidence against home bets
- Potential sharp action: Market pushing Nashville to -220 may indicate public overload; sharp money could be lurking elsewhere
Edge Analysis
How this prediction was generated: This page shows output from the Olympus Bets Soccer Monte Carlo engine. Each game is simulated 5,000 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 →