Skeid vs jerv: result 0-0 and analysis
1. DivisionRegular Season - 3Kick-off on April 14, 2019 at 01:00 PM (UTC)Nordre Åsen kunstgress, Oslo
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What was the result of Skeid vs jerv?
Skeid and jerv drew 0-0 on April 14, 2019.
Official lineup for Skeid vs jerv
The starting elevens fielded at kick-off.
Skeid
- 9D. Tavakoli
- 10M. Can
- 11J. Buduson
- 6M. Mahnin
- 7H. Yousef
- 22H. Tønsberg Andresen
- 3Stian Kommandantvold Pettersen
- 5T. Skogsrud
- 17A. Aleesami
- 18F. Berglie
- 30I. Lysgård
jerv
- 9L. Ferreira
- 27Chuma Emeka Uche Anene
- 6M. Wichmann
- 8Thomas Zernichow
- 11Daniel Aase
- 2T. Wichne
- 4E. Knudsen
- 7S. Larsen
- 19K. Tønnessen
- 25M. Ogungbaro
- 20Ø. Øvretveit
What is the recent form of both teams?
Over their last 2 matches in all competitions, Skeid have 1 win, 1 draw and 0 defeats; jerv 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 |
|---|---|---|---|
| Apr 7, 2019 | Notodden(away) | 1-1 | 1. Division |
| Mar 31, 2019 | Ham-Kam(home) | 1-0 | 1. Division |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 7, 2019 | Strommen(home) | 1-1 | 1. Division |
| Nov 11, 2018 | Tromsdalen Uil(home) | 0-1 | 1. Division |
| Nov 4, 2018 | Ull/Kisa(away) | 1-4 | 1. Division |
| Oct 28, 2018 | Kongsvinger(home) | 1-2 | 1. Division |
| Oct 21, 2018 | Mjondalen(away) | 1-1 | 1. Division |
How many goals should we expect?
Skeid score 1.0 and concede 0.5 goals per match over their last 2; jerv score 0.9 and concede 1.4.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Skeid | 1.0 | 0.5 | 1 | 1/2 | 0/2 |
| jerv | 0.9 | 1.4 | 4 | 8/15 | 5/15 |
Over the last 2 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 16 | Skeid | 30 | 2 | 9 | 19 | 35 | 66 | 15 |
A question about Skeid vs jerv?
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