Kjelsås vs Øygarden: prediction and stats
2. Division - Group 2Group 2 - 17Kick-off on August 28, 2021 at 01:00 PM (UTC)Grefsen Stadion, Oslo
Match postponed, new date to be confirmed
What is the recent form of both teams?
Over their last 15 matches in all competitions, Kjelsås have 5 wins, 3 draws and 7 defeats; Øygarden have 8, 3 and 4.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 23, 2021 | Rosenborg II(away) | 3-1 | 2. Division - Group 2 |
| Aug 18, 2021 | Arendal(home) | 2-2 | 2. Division - Group 2 |
| Aug 14, 2021 | Øygarden(home) | 2-2 | 2. Division - Group 2 |
| Aug 1, 2021 | Grorud(home) | 0-1 | NM Cupen |
| Jul 28, 2021 | Levanger(home) | 0-1 | 2. Division - Group 2 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| 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 |
| Aug 4, 2021 | Vard(home) | 3-1 | 2. Division - Group 2 |
| Aug 1, 2021 | Fyllingsdalen(away) | 2-1 | NM Cupen |
What does the head-to-head say?
In the last meeting: 0 Kjelsås wins, 1 draw, 0 Øygarden wins.
| Date | Score | Competition |
|---|---|---|
| Aug 14, 2021 | Kjelsås 2-2 Øygarden | 2. Division - Group 2 |
How many goals should we expect?
Kjelsås score 1.3 and concede 1.7 goals per match over their last 15; Øygarden score 1.9 and concede 1.5.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Kjelsås | 1.3 | 1.7 | 3 | 8/15 | 9/15 |
| Øygarden | 1.9 | 1.5 | 5 | 8/15 | 8/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 2 | Kjelsås | 23 | 16 | 2 | 5 | 53 | 32 | 50 |
A question about Kjelsås vs Øygarden?
Ask Footlab AI: lineups, absences, player form, stats, how the match could unfold.
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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