Conference League

SP La Fiorita vs UNA Strassen Corner Prediction

Updated 2 days to 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

SP SP La Fiorita
VS
UNA Strassen UNA
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 1.87

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OVER 2.5 goals

49% · odds 1.98

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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 3.38

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Other Conference League fixtures

The match at a glance

  • Match: SP La Fiorita vs UNA Strassen
  • Competition: Conference League
  • Date and kickoff: Tuesday 14 July 2026, 19:00
  • Model pick: Over 7.5 corners at n/a, 60% confidence, 10.0 corners projected
  • SP La Fiorita average: 5.0 corners for, 5.0 against per match
  • UNA Strassen average: 5.0 corners for, 5.0 against per match

Frequently asked questions

How many corners does the model expect in SP La Fiorita vs UNA Strassen?
The corneredge.bet model picks over 7.5 corners at 60% confidence. The predicted total across the match is 10.0 corners.
When is SP La Fiorita vs UNA Strassen played?
Kickoff is 15:00 ET on Tuesday 14 July 2026. That is 20:00 in the United Kingdom and 21:00 in central Europe.
Which team produces more corners, SP La Fiorita or UNA Strassen?
Across the last 5 matches, SP La Fiorita produces 5.0 corners per game. UNA Strassen produces 5.0 corners across the last 5 fixtures. For corners conceded, SP La Fiorita sits at 5.0 per match against 5.0 for UNA Strassen. 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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