CAF Champions League World

GOR Mahia vs Pyramids FC Corner Prediction

Updated

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OVER 7.5 corners

Model projects 8.4 total corners (line 7.5, edge +0.9). Home team averages 4.9 corners for, away averages 5.0. League baseline: 10.0. Lean: OVER.

Confidence 45%
Fair odds 1.64
Best odds n/a
Value No market yet

Team comparison: corner stats

GOR GOR Mahia
VS
Pyramids FC PYR
4.6
Corners for, per match
5.0
4.6
Corners against Lower is better
2.0
9.2
Total match corners
7.0
4.1
First half corners
4.7
1.3
Avg goals for
1.7
45%
Over 2.5 goals Percentage
50%
Leader in row Follower

Other markets for this match

Both teams to score — Yes

46% · odds 1.94

OVER 2.5 goals

41% · odds 1.96

Both teams to score — No

40% · odds 1.98

OVER 8.5 corners

39% · odds 2.06

OVER 9.5 corners

33% · odds 2.74

OVER 10.5 corners

27% · odds 3.87

OVER 3.5 goals

23% · odds 5.28

OVER 11.5 corners

21% · odds 5.74

Other CAF Champions League fixtures

The match at a glance

  • Match: GOR Mahia vs Pyramids FC
  • Competition: CAF Champions League
  • Date and kickoff: Sunday 6 September 2026, 12:00
  • Model pick: Over 7.5 corners at n/a, 45% confidence, 8.4 corners projected
  • GOR Mahia average: 4.6 corners for, 4.6 against per match
  • Pyramids FC average: 5.0 corners for, 2.0 against per match

Frequently asked questions

What is the corner prediction for GOR Mahia vs Pyramids FC?
The corneredge.bet model picks over 7.5 corners at 45% confidence. The predicted total across the match is 8.4 corners.
What is the kickoff time for GOR Mahia vs Pyramids FC?
Kickoff is 08:00 ET on Sunday 6 September 2026. That is 13:00 in the United Kingdom and 14:00 in central Europe.
How do GOR Mahia and Pyramids FC compare on corners?
Across the last 5 matches, GOR Mahia produces 4.6 corners per game. Pyramids FC produces 5.0 corners across the last 1 fixtures. For corners conceded, GOR Mahia sits at 4.6 per match against 2.0 for Pyramids 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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