Sävedalen vs Rosengård: result 1-1 and analysis
Division 2 - Västra GötalandRegular Season - 25Kick-off on October 13, 2018 at 01:00 PM (UTC)Vallhamra IP, Sävedalen
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What was the result of Sävedalen vs Rosengård?
Sävedalen and Rosengård drew 1-1 on October 13, 2018.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Sävedalen have 9 wins, 2 draws and 4 defeats; Rosengård have 7, 0 and 8.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 6, 2018 | Högaborg(away) | 3-2 | Division 2 - Västra Götaland |
| Sep 29, 2018 | IFK Malmö(away) | 3-1 | Division 2 - Västra Götaland |
| Sep 22, 2018 | Varbergs GIF(home) | 6-1 | Division 2 - Västra Götaland |
| Sep 15, 2018 | Kvarnby(home) | 9-0 | Division 2 - Västra Götaland |
| Sep 8, 2018 | Hittarp(away) | 1-2 | Division 2 - Västra Götaland |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 8, 2018 | Kvarnby(home) | 3-4 | Division 2 - Västra Götaland |
| Oct 1, 2018 | Olympic(home) | 4-2 | Division 2 - Västra Götaland |
| Sep 22, 2018 | Vinberg(away) | 2-1 | Division 2 - Västra Götaland |
| Sep 14, 2018 | Assyriska BK(away) | 0-1 | Division 2 - Västra Götaland |
| Sep 8, 2018 | Lindome(home) | 2-1 | Division 2 - Västra Götaland |
What does the head-to-head say?
Across the last 1 meetings: 0 Sävedalen win(s), 0 draw(s), 1 Rosengård win(s).
| Date | Score | Competition |
|---|---|---|
| Jun 24, 2018 | Rosengård 6-1 Sävedalen | Division 2 - Västra Götaland |
Last archived meeting: Rosengård vs Sävedalen on Jun 24, 2018
How many goals should we expect?
Sävedalen score 2.8 and concede 1.5 goals per match over their last 15; Rosengård score 1.9 and concede 1.7.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Sävedalen | 2.8 | 1.5 | 3 | 10/15 | 11/15 |
| Rosengård | 1.9 | 1.7 | 2 | 9/15 | 10/15 |
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