Varbergs GIF vs Assyriska BK: result 1-4 and analysis
Division 2 - Västra GötalandRegular Season - 6Kick-off on May 12, 2018 at 01:00 PM (UTC)Påskbergsvallen, Varberg
Full time
What was the result of Varbergs GIF vs Assyriska BK?
Assyriska BK won 1-4 on May 12, 2018.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Varbergs GIF have 3 wins, 1 draw and 11 defeats; Assyriska BK 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 |
|---|---|---|---|
| May 5, 2018 | Lindome(away) | 1-4 | Division 2 - Västra Götaland |
| Apr 28, 2018 | Halmia(home) | 1-2 | Division 2 - Västra Götaland |
| Apr 22, 2018 | Högaborg(away) | 2-4 | Division 2 - Västra Götaland |
| Apr 14, 2018 | Rosengård(home) | 1-3 | Division 2 - Västra Götaland |
| Apr 7, 2018 | Ullared(away) | 2-0 | Division 2 - Västra Götaland |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 5, 2018 | IFK Malmö(home) | 4-2 | Division 2 - Västra Götaland |
| Apr 28, 2018 | Kvarnby(away) | 3-1 | Division 2 - Västra Götaland |
| Apr 21, 2018 | Sävedalen(home) | 1-3 | Division 2 - Västra Götaland |
| Apr 14, 2018 | Prespa Birlik(away) | 1-3 | Division 2 - Västra Götaland |
| Apr 7, 2018 | Vinberg(home) | 0-0 | Division 2 - Västra Götaland |
How many goals should we expect?
Varbergs GIF score 1.3 and concede 2.8 goals per match over their last 15; Assyriska BK score 1.7 and concede 1.7.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Varbergs GIF | 1.3 | 2.8 | 1 | 11/15 | 13/15 |
| Assyriska BK | 1.7 | 1.7 | 5 | 9/15 | 10/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 13 | Varbergs GIF | 26 | 7 | 1 | 18 | 29 | 58 | 22 |
A question about Varbergs GIF vs Assyriska BK?
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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