Næsby vs Silkeborg KFUM: result 4-0 and analysis
Denmark Series - Group 3Regular Season - 7Kick-off on September 14, 2018 at 03:30 PM (UTC)ALPI Arena Næsby, Odense
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What was the result of Næsby vs Silkeborg KFUM?
Næsby won 4-0 on September 14, 2018.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Næsby have 4 wins, 4 draws and 7 defeats; Silkeborg KFUM have 2, 1 and 8.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 11, 2018 | Randers FC(home) | 2-2 | DBU Pokalen |
| Sep 7, 2018 | B 1913(away) | 1-2 | Denmark Series - Group 3 |
| Sep 1, 2018 | Kolding B(home) | 2-2 | Denmark Series - Group 3 |
| Aug 25, 2018 | Otterup(away) | 5-1 | Denmark Series - Group 3 |
| Aug 18, 2018 | Hedensted(home) | 1-0 | Denmark Series - Group 3 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 8, 2018 | Viborg II(home) | 3-0 | Denmark Series - Group 3 |
| Sep 4, 2018 | Kolding IF(home) | 0-3 | DBU Pokalen |
| Sep 1, 2018 | Varde IF Elite(away) | 1-3 | Denmark Series - Group 3 |
| Aug 25, 2018 | B 1913(away) | 1-1 | Denmark Series - Group 3 |
| Aug 17, 2018 | Kolding B(home) | 1-3 | Denmark Series - Group 3 |
How many goals should we expect?
Næsby score 1.3 and concede 1.8 goals per match over their last 15; Silkeborg KFUM score 1.5 and concede 2.4.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Næsby | 1.3 | 1.8 | 3 | 8/15 | 11/15 |
| Silkeborg KFUM | 1.5 | 2.4 | 2 | 6/11 | 8/11 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 9 | Silkeborg KFUM | 18 | 4 | 3 | 11 | 26 | 33 | 15 |
A question about Næsby vs Silkeborg KFUM?
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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