Lyngby vs Naestved: result 2-0 and analysis
1. DivisionRegular Season - 16Kick-off on November 5, 2015 at 06:00 PM (UTC)Lyngby Stadion, Lyngby
Full time
What was the result of Lyngby vs Naestved?
Lyngby won 2-0 on November 5, 2015.
Goalscorers
- 3′Jeppe Borild KjærLyngby
- 11′L. FosgaardLyngby
What is the recent form of both teams?
Over their last 15 matches in all competitions, Lyngby have 9 wins, 2 draws and 4 defeats; Naestved have 5, 3 and 7.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 31, 2015 | Silkeborg(away) | 2-1 | 1. Division |
| Oct 28, 2015 | Aalborg(home) | 1-2 | DBU Pokalen |
| Oct 22, 2015 | Vestsjælland(home) | 4-4 | 1. Division |
| Oct 18, 2015 | Roskilde(home) | 3-1 | 1. Division |
| Oct 11, 2015 | FC Helsingor(away) | 1-0 | 1. Division |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Nov 1, 2015 | Roskilde(home) | 2-1 | 1. Division |
| Oct 28, 2015 | Vendsyssel FF(away) | 0-0 | 1. Division |
| Oct 25, 2015 | FC Helsingor(away) | 0-1 | 1. Division |
| Oct 18, 2015 | HB Koge(home) | 1-0 | 1. Division |
| Oct 5, 2015 | Silkeborg(away) | 1-1 | 1. Division |
What does the head-to-head say?
In the last meeting: 1 Lyngby win, 0 draws, 0 Naestved wins.
| Date | Score | Competition |
|---|---|---|
| Sep 18, 2015 | Lyngby 3-1 Naestved | 1. Division |
How many goals should we expect?
Lyngby score 2.1 and concede 1.3 goals per match over their last 15; Naestved score 0.9 and concede 1.1.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Lyngby | 2.1 | 1.3 | 4 | 10/15 | 10/15 |
| Naestved | 0.9 | 1.1 | 5 | 4/15 | 4/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 1 | Lyngby | 32 | 18 | 6 | 8 | 69 | 36 | 60 |
A question about Lyngby vs Naestved?
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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