Qatar QSL

Al Rayyan vs Lusail Corner Prediction

Updated 1 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

AL Al Rayyan
VS
Lusail LUS
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 1.61

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OVER 2.5 goals

49% · odds 1.32

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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 1.84

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Other Qatar QSL fixtures

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Al-Wakrah vs Qatar
Fri 16:30

Al-Arabi Doha vs Al Shamal SC
Sat 16:30

Al Sadd vs Al Ahli Doha

The match at a glance

  • Match: Al Rayyan vs Lusail
  • Competition: Qatar QSL
  • Date and kickoff: Thursday 20 August 2026, 16:30
  • Model pick: Over 7.5 corners at n/a, 60% confidence, 10.0 corners projected
  • Al Rayyan average: 5.0 corners for, 5.0 against per match
  • Lusail average: 5.0 corners for, 5.0 against per match

Frequently asked questions

What does the model say about corners in Al Rayyan vs Lusail?
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 Al Rayyan vs Lusail?
Kickoff is 12:30 ET on Thursday 20 August 2026. That is 17:30 in the United Kingdom and 18:30 in central Europe.
How do Al Rayyan and Lusail compare on corners?
Across the last 5 matches, Al Rayyan produces 5.0 corners per game. Lusail produces 5.0 corners across the last 5 fixtures. For corners conceded, Al Rayyan sits at 5.0 per match against 5.0 for Lusail. 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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