Kjelsås vs Flekkerøy: prediction and stats
2. Division - Group 2Group 2 - 26Kick-off on October 30, 2021 at 12:00 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 4 wins, 7 draws and 4 defeats; Flekkerøy have 3, 6 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 25, 2021 | Odd II(away) | 1-1 | 2. Division - Group 2 |
| Oct 21, 2021 | Flekkerøy(away) | 2-2 | 2. Division - Group 2 |
| Oct 16, 2021 | Vard(home) | 3-1 | 2. Division - Group 2 |
| Oct 9, 2021 | Øygarden(away) | 2-3 | 2. Division - Group 2 |
| Oct 3, 2021 | Sotra(home) | 3-1 | 2. Division - Group 2 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 25, 2021 | Rosenborg II(home) | 2-1 | 2. Division - Group 2 |
| Oct 21, 2021 | Kjelsås(home) | 2-2 | 2. Division - Group 2 |
| Oct 17, 2021 | Levanger(away) | 0-1 | 2. Division - Group 2 |
| Oct 9, 2021 | Vard(away) | 1-5 | 2. Division - Group 2 |
| Oct 3, 2021 | Øygarden(home) | 0-0 | 2. Division - Group 2 |
What does the head-to-head say?
In the last meeting: 0 Kjelsås wins, 1 draw, 0 Flekkerøy wins.
| Date | Score | Competition |
|---|---|---|
| Oct 21, 2021 | Flekkerøy 2-2 Kjelsås | 2. Division - Group 2 |
How many goals should we expect?
Kjelsås score 1.9 and concede 1.5 goals per match over their last 15; Flekkerøy score 1.1 and concede 1.9.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Kjelsås | 1.9 | 1.5 | 1 | 12/15 | 10/15 |
| Flekkerøy | 1.1 | 1.9 | 3 | 10/15 | 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 Flekkerøy?
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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