Øygarden vs Levanger: prediction and stats
2. Division - Group 2Group 2 - 18Kick-off on September 5, 2021 at 03:00 PM (UTC)Ågotnes Stadion, Ågotnes
Match postponed, new date to be confirmed
What is the recent form of both teams?
Over their last 15 matches in all competitions, Øygarden have 8 wins, 4 draws and 3 defeats; Levanger have 8, 2 and 5.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 5, 2021 | Skeid(home) | 0-0 | 2. Division - Group 2 |
| Aug 28, 2021 | Egersund(home) | 0-0 | 2. Division - Group 2 |
| Aug 21, 2021 | Fram(away) | 1-1 | 2. Division - Group 2 |
| Aug 18, 2021 | Nardo(home) | 2-0 | 2. Division - Group 2 |
| Aug 14, 2021 | Kjelsås(away) | 2-2 | 2. Division - Group 2 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 5, 2021 | Arendal(home) | 3-1 | 2. Division - Group 2 |
| Sep 1, 2021 | Fram(away) | 0-0 | 2. Division - Group 2 |
| Aug 27, 2021 | Rosenborg II(home) | 5-1 | 2. Division - Group 2 |
| Aug 22, 2021 | Egersund(away) | 1-0 | 2. Division - Group 2 |
| Aug 18, 2021 | Fram(home) | 2-4 | 2. Division - Group 2 |
What does the head-to-head say?
In the last meeting: 0 Øygarden wins, 0 draws, 1 Levanger win.
| Date | Score | Competition |
|---|---|---|
| Jul 11, 2021 | Levanger 8-0 Øygarden | 2. Division - Group 2 |
How many goals should we expect?
Øygarden score 1.7 and concede 1.2 goals per match over their last 15; Levanger score 2.4 and concede 1.4.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Øygarden | 1.7 | 1.2 | 7 | 6/15 | 7/15 |
| Levanger | 2.4 | 1.4 | 6 | 8/15 | 10/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 3 | Levanger | 23 | 15 | 1 | 7 | 53 | 27 | 46 |
A question about Øygarden vs Levanger?
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How does Footlab AI compute this prediction?
The model combines both teams' Elo ratings (anchored by competition pool), their recent form weighted by opponent strength, home advantage and a Poisson matrix for scorelines. When bookmakers publish odds for the match, their consensus is built into the calculation: that is what proved most accurate on past matches. Its accuracy is measured continuously on the predictions actually published. Methodology and measured accuracy