Charlotte FC vs New York Red Bulls prediction for July 25, 2026: Our Monte Carlo simulation ran 5,000 game iterations and projects New York Red Bulls 1.63 - Charlotte FC 1.36. New York Red Bulls is favored with a 44.5% win probability. Expected total goals: 3.0..
New York Red Bulls
1.63
Projected Goals
VS
3.0 total
Charlotte FC
1.36
Projected Goals
Match Outcome Probabilities
New York Red BullsDrawCharlotte FC
Calibrated accuracy at this confidence: 63.1% (1,163 games)
Projected Goals Range 10th – 90th percentile
Charlotte FC
0.61.42.1
New York Red Bulls
0.91.62.4
Expected Goals (xG)
New York Red Bulls1.63
Charlotte FC1.36
19.3Shots16.0
7.0On Target5.7
6.1Corners5.7
Goal Probabilities
Over 0.5
97.4%
Over 1.5
77.8%
Over 2.5
55.3%
Over 3.5
42.7%
Under 2.5
44.7%
BTTS
59.8%
Most Likely Scores
1-1
12.1%
2-1
9.2%
1-2
7.7%
1-0
7.4%
2-0
6.7%
Match Context
MLSMedium
New York Red Bulls
2.23
Draw
3.95
Charlotte FC
3.00
AI Intelligence Analysis
NEUTRAL -1
Market correctly priced or slightly ahead: home ML 44.46% model vs 44.84% market is negative edge (-0.38%), and home ML historically mixed only a supportive track record historically.
Key Factors
- xG gap minimal: NYRB 1.63 vs Charlotte 1.36 = 0.27 xG advantage (modest quality gap)
- Home ML negative edge: Model 44.46% vs market 44.84% = -0.38% (market ahead)
- historical support underperformance: SOCCER | ml | home historically mixed only a supportive track record, below breakeven
- Draw risk elevated: Model draw_prob 23.16% + recent MLS draw rate 25% = ~24% of outcomes are losses on 3-way ML
- Totals overpriced: Model expects 2.99 goals, line 3.25 = underestimating goals by 0.26
Risk Factors
- Home ML historically weak overall (SOCCER | ml | any | any | any | any = RED, a supportive track record) — category disabled
- 23.16% draw probability with 25% MLS draw rate = 1-in-4 games result in loss for ML
- Market odds -123 imply 55.2% true probability needed to break even after vig — model only gives 44.46%
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 →