Ham-Kam vs jerv: result 2-0 and analysis
1. DivisionRegular Season - 11Kick-off on June 3, 2018 at 04:00 PM (UTC)Briskeby Arena, Hamar
Full time
What was the result of Ham-Kam vs jerv?
Ham-Kam won 2-0 on June 3, 2018.
Goalscorers
- 13′A. DønnumHam-Kam
- 51′K. OnsrudHam-Kam
Official lineup for Ham-Kam vs jerv
The starting elevens fielded at kick-off.
Ham-Kam
- 9Ivar Sollie Rønning
- 7Petter Vaagan Moen
- 8M. Solbakken
- 15A. Dønnum
- 17S. Nordli
- 22K. Onsrud
- 3O. Ómarsson
- 4J. Egeris
- 5L. Brotangen
- 10Truls Jevne Hagen
- 12Ł. Jarosiński
jerv
- 10Aram Khalili
- 17M. Andersen
- 6M. Wichmann
- 7Ulrik Reinaldo Berglann
- 8Thomas Zernichow
- 23Andreas Hagen
- 2Glenn Brevik Andersen
- 3B. Wembangomo
- 4E. Knudsen
- 19K. Tønnessen
- 20Ø. Øvretveit
What is the recent form of both teams?
Over their last 10 matches in all competitions, Ham-Kam have 3 wins, 4 draws and 3 defeats; jerv have 5, 4 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 27, 2018 | Aalesund(away) | 2-1 | 1. Division |
| May 21, 2018 | Floro(home) | 3-0 | 1. Division |
| May 16, 2018 | Kongsvinger(away) | 1-2 | 1. Division |
| May 13, 2018 | Nest-Sotra(home) | 1-1 | 1. Division |
| May 5, 2018 | Strommen(home) | 3-2 | 1. Division |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 27, 2018 | Viking(home) | 3-2 | 1. Division |
| May 21, 2018 | Levanger(away) | 3-2 | 1. Division |
| May 16, 2018 | Notodden(home) | 1-0 | 1. Division |
| May 13, 2018 | Strommen(away) | 3-2 | 1. Division |
| May 6, 2018 | Asane(home) | 1-1 | 1. Division |
How many goals should we expect?
Ham-Kam score 1.6 and concede 1.5 goals per match over their last 10; jerv score 1.3 and concede 1.9.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Ham-Kam | 1.6 | 1.5 | 2 | 8/10 | 6/10 |
| jerv | 1.3 | 1.9 | 3 | 9/15 | 7/15 |
Over the last 10 matches in all competitions.
A question about Ham-Kam vs jerv?
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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