Friendlies World

Vietnam vs Gangwon FC Corner Prediction

Updated

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OVER 7.5 corners

Model projects 9.8 total corners (line 7.5, edge +2.3). Home team averages 4.7 corners for, away averages 5.0. League baseline: 10.0. Lean: OVER.

Confidence 59%
Fair odds 1.32
Best odds n/a
Value n/a

Team comparison: corner stats

VIE Vietnam
VS
Gangwon FC GAN
4.3
Corners for, per match
4.8
5.2
Corners against Lower is better
4.8
9.5
Total match corners
9.5
2.0
First half corners
4.3
1.3
Avg goals for
1.5
42%
Over 2.5 goals Percentage
55%
Leader in row Follower

Alternative corner markets

OVER 8.5 corners

53% · odds 1.52

YES 0 corners

49% · odds 1.82

OVER 2.5 corners

49% · odds 1.74

OVER 9.5 corners

47% · odds 1.87

OVER 10.5 corners

41% · odds 2.43

OVER 11.5 corners

35% · odds 3.35

OVER 3.5 corners

31% · odds 4.32

Other Friendlies fixtures

The match at a glance

  • Match: Vietnam vs Gangwon FC
  • Competition: Friendlies
  • Date and kickoff: Monday 13 July 2026, 08:00
  • Model pick: Over 7.5 corners at n/a, 59% confidence, 9.8 corners projected
  • Vietnam average: 4.3 corners for, 5.2 against per match
  • Gangwon FC average: 4.8 corners for, 4.8 against per match

Frequently asked questions

How many corners does the model expect in Vietnam vs Gangwon FC?
The corneredge.bet model picks over 7.5 corners at 59% confidence. The predicted total across the match is 9.8 corners.
What time does Vietnam vs Gangwon FC kick off?
Kickoff is 04:00 ET on Monday 13 July 2026. That is 09:00 in the United Kingdom and 10:00 in central Europe.
Which team produces more corners, Vietnam or Gangwon FC?
Across the last 7 matches, Vietnam produces 4.3 corners per game. Gangwon FC produces 4.8 corners across the last 5 fixtures. For corners conceded, Vietnam sits at 5.2 per match against 4.8 for Gangwon 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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