Rågsved vs Assyriska FF: result 0-1 and analysis
Division 2 - Södra SvealandSödra Svealand - 8Kick-off on May 19, 2023 at 06:00 PM (UTC)Hagsätra IP, Stockholm
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What was the result of Rågsved vs Assyriska FF?
Assyriska FF won 0-1 on May 19, 2023.
Goalscorers
- 63′?Assyriska FF
What is the recent form of both teams?
Over their last 15 matches in all competitions, Rågsved have 4 wins, 4 draws and 7 defeats; Assyriska FF have 11, 2 and 2.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 13, 2023 | Smedby(away) | 1-3 | Division 2 - Södra Svealand |
| May 5, 2023 | Huddinge(home) | 1-1 | Division 2 - Södra Svealand |
| Apr 28, 2023 | Nacka Iliria(away) | 0-4 | Division 2 - Södra Svealand |
| Apr 22, 2023 | Karlslund(home) | 1-1 | Division 2 - Södra Svealand |
| Apr 15, 2023 | Arameiska / Syrianska(away) | 2-3 | Division 2 - Södra Svealand |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 14, 2023 | Farsta(home) | 1-0 | Division 2 - Södra Svealand |
| May 5, 2023 | Sleipner(away) | 1-2 | Division 2 - Södra Svealand |
| Apr 30, 2023 | Haninge(home) | 1-2 | Division 2 - Södra Svealand |
| Apr 21, 2023 | IFK Eskilstuna(away) | 3-1 | Division 2 - Södra Svealand |
| Apr 15, 2023 | Mjölby(home) | 4-0 | Division 2 - Södra Svealand |
How many goals should we expect?
Rågsved score 1.5 and concede 1.7 goals per match over their last 15; Assyriska FF score 2.4 and concede 0.7.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Rågsved | 1.5 | 1.7 | 1 | 10/15 | 9/15 |
| Assyriska FF | 2.4 | 0.7 | 7 | 8/15 | 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 |
|---|---|---|---|---|---|---|---|---|
| 6 | Rågsved | 25 | 12 | 6 | 7 | 49 | 40 | 42 |
A question about Rågsved vs Assyriska 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