MLS

New York Red Bulls vs Charlotte FC Corner Prediction

Updated

Kickoff:

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OVER 7.5 corners

Model projects 10.0 total corners (line 7.5, edge +2.5). Home team averages 5.0 corners for, away averages 5.0. League baseline: 10.0. Lean: OVER.

Confidence 60%
Fair odds 1.29
Best odds n/a
Value No market yet

Team comparison: corner stats

NEW New York Red Bulls
VS
Charlotte FC CHA
5.0
Corners for, per match
5.0
5.0
Corners against Lower is better
5.0
10.0
Total match corners
10.0
4.5
First half corners
4.5
1.7
Avg goals for
1.4
51%
Over 2.5 goals Percentage
51%
Leader in row Follower

Other markets for this match

OVER 2.5 goals

57% · odds 1.50

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Both teams to score — Yes

56% · odds 1.42

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OVER 8.5 corners

54% · odds 1.47

OVER 9.5 corners

48% · odds 1.78

OVER 10.5 corners

42% · odds 2.28

OVER 3.5 goals

39% · odds 2.26

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OVER 11.5 corners

36% · odds 3.12

Other MLS fixtures

The match at a glance

  • Match: New York Red Bulls vs Charlotte FC
  • Competition: MLS
  • Date and kickoff: Saturday 25 July 2026, 22:30
  • Model pick: Over 7.5 corners at n/a, 60% confidence, 10.0 corners projected
  • New York Red Bulls average: 5.0 corners for, 5.0 against per match
  • Charlotte FC average: 5.0 corners for, 5.0 against per match

Frequently asked questions

What does the model say about corners in New York Red Bulls vs Charlotte FC?
The corneredge.bet model picks over 7.5 corners at 60% confidence. The predicted total across the match is 10.0 corners.
When is New York Red Bulls vs Charlotte FC played?
Kickoff is 18:30 ET on Saturday 25 July 2026. That is 23:30 in the United Kingdom and 00:30 in central Europe.
What are the corner averages for New York Red Bulls and Charlotte FC?
Across the last 15 matches, New York Red Bulls produces 5.0 corners per game. Charlotte FC produces 5.0 corners across the last 5 fixtures. For corners conceded, New York Red Bulls sits at 5.0 per match against 5.0 for Charlotte FC. The two sides are close on corner output.
Page last updated: . Predictions, odds and team stats refresh automatically. Sources: Fixture data and team statistics from API-Football. Odds from the sportsbooks we track. Methodology: see how the model works.
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