Division 2

Opava vs MFK Karvina Corner Prediction

Updated

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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

OPA Opava
VS
MFK Karvina MFK
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
1.4
Avg goals for
1.4
51%
Over 2.5 goals Percentage
51%
Leader in row Follower

Other markets for this match

OVER 8.5 corners

54% · odds 1.47

Both teams to score — Yes

49% · odds 1.68

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OVER 2.5 goals

49% · odds 1.82

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OVER 9.5 corners

48% · odds 1.78

OVER 10.5 corners

42% · odds 2.28

OVER 11.5 corners

36% · odds 3.12

OVER 3.5 goals

31% · odds 3.02

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Other Division 2 fixtures

The match at a glance

  • Match: Opava vs MFK Karvina
  • Competition: Division 2
  • Date and kickoff: Monday 27 July 2026, 16:00
  • Model pick: Over 7.5 corners at n/a, 60% confidence, 10.0 corners projected
  • Opava average: 5.0 corners for, 5.0 against per match
  • MFK Karvina average: 5.0 corners for, 5.0 against per match

Frequently asked questions

What is the corner prediction for Opava vs MFK Karvina?
The corneredge.bet model picks over 7.5 corners at 60% confidence. The predicted total across the match is 10.0 corners.
What is the kickoff time for Opava vs MFK Karvina?
Kickoff is 12:00 ET on Monday 27 July 2026. That is 17:00 in the United Kingdom and 18:00 in central Europe.
How do Opava and MFK Karvina compare on corners?
Across the last 5 matches, Opava produces 5.0 corners per game. MFK Karvina produces 5.0 corners across the last 5 fixtures. For corners conceded, Opava sits at 5.0 per match against 5.0 for MFK Karvina. 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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