Huddinge vs Assyriska IF: result 2-3 and analysis
Division 2 - Södra SvealandRegular Season - 11Kick-off on June 12, 2016 at 03:00 PM (UTC)Källbrinks IP, Huddinge
Full time
What was the result of Huddinge vs Assyriska IF?
Assyriska IF won 2-3 on June 12, 2016.
What is the recent form of both teams?
Over their last 10 matches in all competitions, Huddinge have 5 wins, 3 draws and 2 defeats; Assyriska IF have 3, 3 and 4.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 4, 2016 | Motala(away) | 3-3 | Division 2 - Södra Svealand |
| May 29, 2016 | Värmbols(home) | 2-2 | Division 2 - Södra Svealand |
| May 20, 2016 | Aspudden-Tellus(away) | 2-1 | Division 2 - Södra Svealand |
| May 15, 2016 | Eskilstuna City(home) | 3-0 | Division 2 - Södra Svealand |
| May 8, 2016 | Arameiska / Syrianska(away) | 0-1 | Division 2 - Södra Svealand |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 5, 2016 | Vimmerby(away) | 0-0 | Division 2 - Södra Svealand |
| May 28, 2016 | Motala(home) | 2-1 | Division 2 - Södra Svealand |
| May 22, 2016 | Värmbols(away) | 1-4 | Division 2 - Södra Svealand |
| May 14, 2016 | Aspudden-Tellus(home) | 0-2 | Division 2 - Södra Svealand |
| May 9, 2016 | Eskilstuna City(away) | 2-4 | Division 2 - Södra Svealand |
How many goals should we expect?
Huddinge score 2.3 and concede 1.8 goals per match over their last 10; Assyriska IF score 1.3 and concede 1.7.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Huddinge | 2.3 | 1.8 | 1 | 8/10 | 9/10 |
| Assyriska IF | 1.3 | 1.7 | 3 | 6/10 | 6/10 |
Over the last 10 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 12 | Huddinge | 26 | 9 | 3 | 14 | 48 | 64 | 30 |
A question about Huddinge vs Assyriska IF?
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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