Naestved vs Silkeborg: result 1-0 and analysis
DBU Pokalen3rd RoundKick-off on September 26, 2018 at 04:00 PM (UTC)MTM Service Park, Næstved
Full time
What was the result of Naestved vs Silkeborg?
Naestved won 1-0 on September 26, 2018.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Naestved have 7 wins, 5 draws and 3 defeats; Silkeborg have 8, 1 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 23, 2018 | Fremad Amager(home) | 2-1 | 1. Division |
| Sep 16, 2018 | Lyngby(away) | 3-1 | 1. Division |
| Sep 9, 2018 | Viborg(away) | 1-2 | 1. Division |
| Sep 5, 2018 | FC Helsingor(away) | 2-2 | DBU Pokalen |
| Sep 1, 2018 | Roskilde(home) | 3-1 | 1. Division |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 23, 2018 | Nykobing FC(home) | 3-1 | 1. Division |
| Sep 16, 2018 | FC Helsingor(home) | 3-0 | 1. Division |
| Sep 10, 2018 | Hvidovre(away) | 4-2 | 1. Division |
| Sep 5, 2018 | Brabrand(away) | 3-2 | DBU Pokalen |
| Sep 2, 2018 | Fremad Amager(away) | 0-2 | 1. Division |
What does the head-to-head say?
Across the last 4 meetings: 0 Naestved win(s), 1 draw(s), 3 Silkeborg win(s).
| Date | Score | Competition |
|---|---|---|
| Aug 26, 2018 | Silkeborg 3-1 Naestved | 1. Division |
| Apr 24, 2016 | Silkeborg 3-0 Naestved | 1. Division |
| Nov 15, 2015 | Naestved 1-3 Silkeborg | 1. Division |
| Oct 5, 2015 | Silkeborg 1-1 Naestved | 1. Division |
Last archived meeting: Silkeborg vs Naestved on Aug 26, 2018
How many goals should we expect?
Naestved score 1.9 and concede 1.4 goals per match over their last 15; Silkeborg score 1.8 and concede 1.5.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Naestved | 1.9 | 1.4 | 2 | 13/15 | 11/15 |
| Silkeborg | 1.8 | 1.5 | 5 | 7/15 | 10/15 |
Over the last 15 matches in all competitions.
How does Footlab 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. Its accuracy is measured continuously on the predictions actually published. Methodology and measured accuracy