Assyriska FF vs Orgryte IS: result 0-1 and analysis
SuperettanRegular Season - 3Kick-off on April 17, 2016 at 02:00 PM (UTC)Södertälje Fotbollsarena, Södertälje
Full time
What was the result of Assyriska FF vs Orgryte IS?
Orgryte IS won 0-1 on April 17, 2016.
Goalscorers
- 29′S. OhlssonOrgryte IS
Official lineup for Assyriska FF vs Orgryte IS
The starting elevens fielded at kick-off.
Assyriska FF
- 10M. Genc
- 19Ken Göran Fagerberg
- 3S. Strand
- 8Daniel Sliper
- 9T. Waker
- 22U. Anyora
- 12F. Holster
- 5D. Durmaz
- 6Linus Malmborg
- 13G. Jarl
- 1Robin Malmkvist
Orgryte IS
- 9George Mourad
- 11William Atashkadeh
- 7J. Lindström
- 8A. Östling
- 14D. Paulson
- 17Björn Anklev
- 5J. Hammar
- 16S. Ohlsson
- 18Hampus Bohman
- 24Fredrik Björck
- 1Robertino Kljajic
What is the recent form of both teams?
Over their last 2 matches in all competitions, Assyriska FF have 1 win, 0 draws and 1 defeat; Orgryte IS have 0, 1 and 1.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 9, 2016 | IK Frej(away) | 1-2 | Superettan |
| Apr 3, 2016 | Dalkurd FF(home) | 2-1 | Superettan |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 11, 2016 | Angelholms FF(home) | 0-1 | Superettan |
| Apr 3, 2016 | Ljungskile SK(away) | 1-1 | Superettan |
How many goals should we expect?
Assyriska FF score 1.5 and concede 1.5 goals per match over their last 2; Orgryte IS score 0.5 and concede 1.0.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Assyriska FF | 1.5 | 1.5 | 0 | 2/2 | 2/2 |
| Orgryte IS | 0.5 | 1.0 | 0 | 1/2 | 0/2 |
Over the last 2 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 3 | Orgryte IS | 30 | 16 | 8 | 6 | 57 | 33 | 56 |
A question about Assyriska FF vs Orgryte IS?
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