Naestved vs Ishøj: result 1-2 and analysis
2. DivisionRegular Season - 21Kick-off on April 4, 2025 at 04:30 PM (UTC)MTM Service Park, Næstved
Full time
What was the result of Naestved vs Ishøj?
Ishøj won 1-2 on April 4, 2025.
Goalscorers
- 80′M. KongstedtNaestved
- 89′E. SalamounIshøj
- 90′E. SalamounIshøj
What is the recent form of both teams?
Over their last 15 matches in all competitions, Naestved have 8 wins, 3 draws and 4 defeats; Ishøj have 7, 3 and 5.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Mar 28, 2025 | Nykobing FC(away) | 2-0 | 2. Division |
| Mar 21, 2025 | Fremad Amager(home) | 1-1 | 2. Division |
| Mar 16, 2025 | Frem(home) | 1-3 | 2. Division |
| Mar 9, 2025 | Thisted FC(home) | 2-1 | 2. Division |
| Feb 28, 2025 | HIK(away) | 0-3 | Friendlies Clubs |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Mar 29, 2025 | Skive(home) | 0-1 | 2. Division |
| Mar 21, 2025 | AB Copenhagen(away) | 0-3 | 2. Division |
| Mar 18, 2025 | B 93(away) | 1-0 | Friendlies Clubs |
| Mar 15, 2025 | Nykobing FC(home) | 2-1 | 2. Division |
| Mar 8, 2025 | Middelfart(home) | 1-1 | 2. Division |
What does the head-to-head say?
In the last meeting: 0 Naestved wins, 1 draw, 0 Ishøj wins.
| Date | Score | Competition |
|---|---|---|
| Sep 14, 2024 | Ishøj 2-2 Naestved | 2. Division |
How many goals should we expect?
Naestved score 1.3 and concede 1.2 goals per match over their last 15; Ishøj score 1.3 and concede 1.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Naestved | 1.3 | 1.2 | 6 | 7/15 | 7/15 |
| Ishøj | 1.3 | 1.3 | 2 | 10/15 | 8/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 6 | Naestved | 11 | 3 | 7 | 1 | 15 | 13 | 16 |
A question about Naestved vs Ishøj?
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