Chicago Fire vs New York City FC prediction for July 25, 2026: Our Monte Carlo simulation ran 5,000 game iterations and projects New York City FC 1.49 - Chicago Fire 1.45. New York City FC is favored with a 38.6% win probability. Expected total goals: 2.9..
New York City FC
1.49
Projected Goals
VS
2.9 total
Chicago Fire
1.45
Projected Goals
Match Outcome Probabilities
New York City FCDrawChicago Fire
Calibrated accuracy at this confidence: 64.8% (1,163 games)
Projected Goals Range 10th – 90th percentile
Chicago Fire
0.71.42.2
New York City FC
0.71.52.3
Expected Goals (xG)
New York City FC1.49
Chicago Fire1.45
18.8Shots15.7
6.8On Target5.6
6.0Corners5.6
Goal Probabilities
Over 0.5
96.1%
Over 1.5
77.4%
Over 2.5
54.0%
Over 3.5
41.8%
Under 2.5
46.0%
BTTS
58.5%
Most Likely Scores
1-1
12.4%
2-1
8.6%
1-2
8.4%
1-0
7.0%
0-1
6.8%
Match Context
MLSMedium
New York City FC
2.75
Draw
3.79
Chicago Fire
2.47
AI Intelligence Analysis
NEUTRAL
Essentially a coin flip: xG nearly identical (NYCFC 1.49 vs Chicago 1.45), model probabilities close (38.62% vs 37.16%), and market shows slight NYCFC home preference. Home ML slight edge (+2.26%) but historical support is weak YELLOW (a supportive track record); away ML RED (a supportive track record).
Key Factors
- xG parity: NYCFC 1.49 vs Chicago 1.45 = only 0.04 xG gap (essential coin flip on offense)
- Model sees home edge: NYCFC 38.62% vs Chicago 37.16% = only 1.46 percentage-point home edge
- Market undervalues home: NYCFC 36.36% implied vs model 38.62% = +2.26% edge to home ML
- Home ML weak historical support historical a supportive track record insufficient
- Draw probability 24.21% is substantial; makes 3-way ML risky
Risk Factors
- Away ML historically weak — cannot recommend Chicago away
- Home ML YELLOW but weak (a supportive track record) — cannot overcome 24% draw rate
- This is a true statistical coin flip (0.04 xG difference); edge too small to justify bet
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 →