Naestved vs Skive: result 1-3 and analysis
1. DivisionRegular Season - 22Kick-off on March 24, 2016 at 12:45 PM (UTC)MTM Service Park, Næstved
Full time
What was the result of Naestved vs Skive?
Skive won 1-3 on March 24, 2016.
Goalscorers
- 8′M. UhreSkive
- 81′Musefiu Olasunkanmi AshiruSkive
- 86′J. ChristiansenNaestved
- 90′Razak Adebayo OdeyemiSkive
What is the recent form of both teams?
Over their last 15 matches in all competitions, Naestved have 5 wins, 2 draws and 8 defeats; Skive have 5, 2 and 8.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Mar 20, 2016 | FC Fredericia(away) | 1-2 | 1. Division |
| Mar 13, 2016 | Vejle(away) | 2-1 | 1. Division |
| Nov 29, 2015 | AC Horsens(away) | 3-1 | 1. Division |
| Nov 22, 2015 | Vestsjælland(home) | 2-3 | 1. Division |
| Nov 15, 2015 | Silkeborg(home) | 1-3 | 1. Division |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Mar 20, 2016 | Silkeborg(home) | 1-1 | 1. Division |
| Mar 13, 2016 | Lyngby(away) | 1-1 | 1. Division |
| Mar 6, 2016 | FC Helsingor(away) | 1-2 | 1. Division |
| Mar 2, 2016 | Brondby(home) | 0-3 | DBU Pokalen |
| Nov 29, 2015 | Roskilde(home) | 0-1 | 1. Division |
What does the head-to-head say?
Across the last 3 meetings: 0 Naestved wins, 1 draw, 2 Skive wins.
| Date | Score | Competition |
|---|---|---|
| Sep 27, 2015 | Naestved 0-1 Skive | 1. Division |
| Jun 2, 2012 | Naestved 2-2 Skive | 1. Division |
| Oct 23, 2011 | Skive 1-0 Naestved | 1. Division |
How many goals should we expect?
Naestved score 1.1 and concede 1.5 goals per match over their last 15; Skive score 0.9 and concede 1.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Naestved | 1.1 | 1.5 | 3 | 8/15 | 8/15 |
| Skive | 0.9 | 1.3 | 3 | 6/15 | 5/15 |
Over the last 15 matches in all competitions.
A question about Naestved vs Skive?
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