Torns vs Rosengård: result 3-1 and analysis
Division 2 - Södra GötalandRegular Season - 11Kick-off on June 12, 2016 at 02:00 PM (UTC)Tornvallen, Lund
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What was the result of Torns vs Rosengård?
Torns won 3-1 on June 12, 2016.
What is the recent form of both teams?
Over their last 10 matches in all competitions, Torns have 2 wins, 4 draws and 4 defeats; Rosengård have 8, 1 and 1.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 2, 2016 | Lindsdal(away) | 1-0 | Division 2 - Södra Götaland |
| May 28, 2016 | IFK Hässleholm(home) | 4-4 | Division 2 - Södra Götaland |
| May 22, 2016 | Karlskrona(away) | 1-3 | Division 2 - Södra Götaland |
| May 13, 2016 | Kvarnby(home) | 3-0 | Division 2 - Södra Götaland |
| May 9, 2016 | Lund(away) | 2-2 | Division 2 - Södra Götaland |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 4, 2016 | Berga(home) | 4-1 | Division 2 - Södra Götaland |
| May 28, 2016 | Asarum(away) | 0-3 | Division 2 - Södra Götaland |
| May 21, 2016 | Hässleholms IF(home) | 8-1 | Division 2 - Södra Götaland |
| May 14, 2016 | Nybro(away) | 3-0 | Division 2 - Södra Götaland |
| May 9, 2016 | IFK Malmö(home) | 3-1 | Division 2 - Södra Götaland |
How many goals should we expect?
Torns score 1.4 and concede 1.7 goals per match over their last 10; Rosengård score 2.9 and concede 1.1.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Torns | 1.4 | 1.7 | 2 | 6/10 | 6/10 |
| Rosengård | 2.9 | 1.1 | 2 | 7/10 | 9/10 |
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 | Torns | 25 | 7 | 0 | 18 | 31 | 71 | 21 |
A question about Torns vs Rosengård?
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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