Sleipner vs Sylvia: result 2-1 and analysis
Division 2 - Södra SvealandRegular Season - 13Kick-off on June 26, 2017 at 05:00 PM (UTC)PlatinumCars Arena, Norrköping
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What was the result of Sleipner vs Sylvia?
Sleipner won 2-1 on June 26, 2017.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Sleipner have 7 wins, 5 draws and 3 defeats; Sylvia have 6, 5 and 4.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 15, 2017 | Motala(away) | 3-2 | Division 2 - Södra Svealand |
| Jun 11, 2017 | Kumla(home) | 1-1 | Division 2 - Södra Svealand |
| Jun 3, 2017 | Assyriska IF(away) | 0-0 | Division 2 - Södra Svealand |
| May 28, 2017 | Haninge(home) | 2-1 | Division 2 - Södra Svealand |
| May 25, 2017 | Huddinge(away) | 1-0 | Division 2 - Södra Svealand |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 17, 2017 | Rynninge(home) | 0-2 | Division 2 - Södra Svealand |
| Jun 10, 2017 | Örebro Syrianska(away) | 2-2 | Division 2 - Södra Svealand |
| Jun 3, 2017 | Boo(home) | 0-1 | Division 2 - Södra Svealand |
| May 29, 2017 | Linköping City(away) | 0-1 | Division 2 - Södra Svealand |
| May 25, 2017 | Värmdö(home) | 4-2 | Division 2 - Södra Svealand |
How many goals should we expect?
Sleipner score 1.6 and concede 1.2 goals per match over their last 15; Sylvia score 1.5 and concede 1.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Sleipner | 1.6 | 1.2 | 6 | 8/15 | 7/15 |
| Sylvia | 1.5 | 1.3 | 2 | 10/15 | 8/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 2 | Sleipner | 25 | 14 | 6 | 5 | 51 | 36 | 48 |
A question about Sleipner vs Sylvia?
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