Assyriska BK vs Sävedalen: result 2-1 and analysis
Division 2 - Västra GötalandRegular Season - 19Kick-off on August 27, 2016 at 02:00 PM (UTC)Ruddalens IP 1, Västra Frölunda
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What was the result of Assyriska BK vs Sävedalen?
Assyriska BK won 2-1 on August 27, 2016.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Assyriska BK have 9 wins, 1 draws and 5 defeats; Sävedalen have 6, 3 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 20, 2016 | Tenhult(away) | 2-0 | Division 2 - Västra Götaland |
| Aug 13, 2016 | Halmia(home) | 3-0 | Division 2 - Västra Götaland |
| Aug 6, 2016 | Vinberg(away) | 0-3 | Division 2 - Västra Götaland |
| Jul 30, 2016 | Högaborg(away) | 3-0 | Division 2 - Västra Götaland |
| Jun 30, 2016 | Dalstorps(home) | 3-1 | Division 2 - Västra Götaland |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 20, 2016 | Höganäs(home) | 2-4 | Division 2 - Västra Götaland |
| Aug 12, 2016 | Torslanda(away) | 3-2 | Division 2 - Västra Götaland |
| Aug 6, 2016 | Ullared(home) | 2-1 | Division 2 - Västra Götaland |
| Jul 30, 2016 | Eskilsminne(home) | 0-0 | Division 2 - Västra Götaland |
| Jun 29, 2016 | Akademi HIF(away) | 0-3 | Division 2 - Västra Götaland |
What does the head-to-head say?
Across the last 1 meetings: 1 Assyriska BK win(s), 0 draw(s), 0 Sävedalen win(s).
| Date | Score | Competition |
|---|---|---|
| May 7, 2016 | Sävedalen 0-2 Assyriska BK | Division 2 - Västra Götaland |
Last archived meeting: Sävedalen vs Assyriska BK on May 7, 2016
How many goals should we expect?
Assyriska BK score 2.1 and concede 1.3 goals per match over their last 15; Sävedalen score 1.3 and concede 1.7.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Assyriska BK | 2.1 | 1.3 | 7 | 6/15 | 12/15 |
| Sävedalen | 1.3 | 1.7 | 2 | 9/15 | 9/15 |
Over the last 15 matches in all competitions.
How does Footlab 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. Its accuracy is measured continuously on the predictions actually published. Methodology and measured accuracy