Conference League

FC Universitatea Cluj vs Brann Corner Prediction

Updated

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OVER 7.5 corners

Model projects 10.1 total corners (line 7.5, edge +2.6). Home team averages 5.4 corners for, away averages 7.0. League baseline: 10.0. Lean: OVER.

Confidence 56%
Fair odds 1.27
Best odds n/a
Value No market yet

Team comparison: corner stats

FC FC Universitatea Cluj
VS
Brann BRA
5.0
Corners for, per match
7.0
4.3
Corners against Lower is better
4.0
9.3
Total match corners
11.0
4.3
First half corners
4.5
1.6
Avg goals for
2.0
47%
Over 2.5 goals Percentage
51%
Leader in row Follower

Other markets for this match

OVER 8.5 corners

50% · odds 1.44

OVER 2.5 goals

49% · odds 2.04

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Both teams to score — Yes

49% · odds 1.80

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OVER 9.5 corners

44% · odds 1.73

OVER 10.5 corners

38% · odds 2.20

OVER 11.5 corners

32% · odds 2.98

OVER 3.5 goals

31% · odds 3.54

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Other Conference League fixtures

The match at a glance

  • Match: FC Universitatea Cluj vs Brann
  • Competition: Conference League
  • Date and kickoff: Thursday 23 July 2026, 17:00
  • Model pick: Over 7.5 corners at n/a, 56% confidence, 10.1 corners projected
  • FC Universitatea Cluj average: 5.0 corners for, 4.3 against per match
  • Brann average: 7.0 corners for, 4.0 against per match

Frequently asked questions

What does the model say about corners in FC Universitatea Cluj vs Brann?
The corneredge.bet model picks over 7.5 corners at 56% confidence. The predicted total across the match is 10.1 corners.
What time does FC Universitatea Cluj vs Brann kick off?
Kickoff is 13:00 ET on Thursday 23 July 2026. That is 18:00 in the United Kingdom and 19:00 in central Europe.
What are the corner averages for FC Universitatea Cluj and Brann?
Across the last 30 matches, FC Universitatea Cluj produces 5.0 corners per game. Brann produces 7.0 corners across the last 1 fixtures. For corners conceded, FC Universitatea Cluj sits at 4.3 per match against 4.0 for Brann. The corner battle tilts toward Brann.
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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