Kumla vs Huddinge: result 0-0 and analysis
Division 2 - Södra SvealandRegular Season - 12Kick-off on June 17, 2017 at 02:00 PM (UTC)Kumla IP, Kumla
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What was the result of Kumla vs Huddinge?
Kumla and Huddinge drew 0-0 on June 17, 2017.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Kumla have 3 wins, 4 draws and 8 defeats; Huddinge have 6, 2 and 7.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 11, 2017 | Sleipner(away) | 1-1 | Division 2 - Södra Svealand |
| Jun 2, 2017 | Rynninge(home) | 2-6 | Division 2 - Södra Svealand |
| May 28, 2017 | Örebro Syrianska(away) | 2-3 | Division 2 - Södra Svealand |
| May 25, 2017 | Boo(home) | 0-2 | Division 2 - Södra Svealand |
| May 19, 2017 | Linköping City(away) | 2-2 | Division 2 - Södra Svealand |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 11, 2017 | Assyriska IF(home) | 3-3 | Division 2 - Södra Svealand |
| Jun 3, 2017 | Haninge(away) | 1-2 | Division 2 - Södra Svealand |
| May 28, 2017 | Södertälje(home) | 0-0 | Division 2 - Södra Svealand |
| May 25, 2017 | Sleipner(home) | 0-1 | Division 2 - Södra Svealand |
| May 20, 2017 | Rynninge(away) | 0-2 | Division 2 - Södra Svealand |
How many goals should we expect?
Kumla score 1.3 and concede 2.3 goals per match over their last 15; Huddinge score 1.5 and concede 1.5.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Kumla | 1.3 | 2.3 | 1 | 11/15 | 9/15 |
| Huddinge | 1.5 | 1.5 | 2 | 9/15 | 9/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 12 | Huddinge | 26 | 9 | 3 | 14 | 48 | 64 | 30 |
A question about Kumla vs Huddinge?
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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