Inter Miami CF vs CF Montreal prediction for July 25, 2026: Our Monte Carlo simulation ran 5,000 game iterations and projects CF Montreal 1.37 - Inter Miami CF 1.4. Inter Miami CF is favored with a 39.4% win probability. Expected total goals: 2.8..
CF Montreal
1.37
Projected Goals
VS
2.8 total
Inter Miami CF
1.4
Projected Goals
Match Outcome Probabilities
CF MontrealDrawInter Miami CF
Calibrated accuracy at this confidence: 65.6% (1,163 games)
Projected Goals Range 10th – 90th percentile
Inter Miami CF
0.61.42.2
CF Montreal
0.61.42.1
Expected Goals (xG)
CF Montreal1.37
Inter Miami CF1.40
19.6Shots15.9
7.1On Target5.6
6.2Corners5.6
Goal Probabilities
Over 0.5
97.0%
Over 1.5
78.0%
Over 2.5
47.6%
Over 3.5
45.5%
Under 2.5
52.4%
BTTS
60.0%
Most Likely Scores
1-1
13.0%
1-2
8.5%
2-1
8.3%
0-1
7.8%
1-0
7.6%
Match Context
MLSMedium
CF Montreal
2.90
Draw
4.06
Inter Miami CF
2.26
AI Intelligence Analysis
NEUTRAL
Near-complete parity: xG near-identical (Montreal 1.37 vs Miami 1.40), model probabilities nearly even (38.03% vs 39.41%), and market shows Miami as favorite. Away ML is historically weak — cannot recommend despite +4.84% probability edge.
Key Factors
- xG parity: Montreal 1.37 vs Miami 1.40 = nearly identical (1-in-9 team edge). This is a true toss-up on offense
- Model sees Miami edge: 39.41% away win vs Montreal 38.03% home = Miami +1.38 percentage point edge
- Market favors Miami more: -144 odds imply 44.25% vs model 39.41% = market ahead by 4.84% on away ML
- Away ML historically weak: Historical a supportive track record — category fundamentally unprofitable
- Totals severely undervalued: Model 2.78 vs market 3.5 = -0.72 edge (model giving massive UNDER edge, but Under is F grade)
Risk Factors
- Away ML blocked by historically weak — cannot be recommended regardless of edge size
- Model-market gap of 4.84% on away ML suggests either model underestimating or market overestimating Miami
- Draw probability 22.56% is moderate but makes ML risky in 3-way market
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 →