Assyriska FF vs Umea FF: result 3-2 and analysis
Ettan - NorraRegular Season - 9Kick-off on June 11, 2017 at 02:00 PM (UTC)Södertälje Fotbollsarena, Södertälje
Full time
What was the result of Assyriska FF vs Umea FF?
Assyriska FF won 3-2 on June 11, 2017.
Goalscorers
- 14′Timothy McNeilUmea FF
- 21′Sebastian HolmqvistAssyriska FF
- 38′Timothy McNeilUmea FF
- 49′Sebastian HolmqvistAssyriska FF
- 83′226592Assyriska FF
What is the recent form of both teams?
Over their last 15 matches in all competitions, Assyriska FF have 4 wins, 6 draws and 5 defeats; Umea FF have 8, 2 and 5.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 4, 2017 | Sandviken(away) | 1-1 | Ettan - Norra |
| May 28, 2017 | Akropolis(home) | 2-1 | Ettan - Norra |
| May 20, 2017 | Enskede(home) | 4-0 | Ettan - Norra |
| May 13, 2017 | Sollentuna(away) | 1-1 | Ettan - Norra |
| May 7, 2017 | Carlstad United(home) | 1-1 | Ettan - Norra |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 4, 2017 | Sollentuna(home) | 1-1 | Ettan - Norra |
| May 28, 2017 | Arameiska / Syrianska(away) | 2-3 | Ettan - Norra |
| May 21, 2017 | Carlstad United(home) | 1-0 | Ettan - Norra |
| May 15, 2017 | Umeå FC(away) | 4-0 | Ettan - Norra |
| May 7, 2017 | Enskede(home) | 4-2 | Ettan - Norra |
How many goals should we expect?
Assyriska FF score 1.4 and concede 1.7 goals per match over their last 15; Umea FF score 1.5 and concede 1.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Assyriska FF | 1.4 | 1.7 | 2 | 10/15 | 9/15 |
| Umea FF | 1.5 | 1.3 | 5 | 7/15 | 7/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 8 | Assyriska FF | 26 | 10 | 5 | 11 | 44 | 45 | 35 |
A question about Assyriska FF vs Umea FF?
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