Næsby vs HIK: result 2-3 and analysis
2nd Division - Group 2Regular Season - 12Kick-off on October 21, 2017 at 01:00 PM (UTC)ALPI Arena Næsby, Odense
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What was the result of Næsby vs HIK?
HIK won 2-3 on October 21, 2017.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Næsby have 2 wins, 2 draws and 11 defeats; HIK have 7, 2 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 14, 2017 | Kolding IF(home) | 0-0 | 2nd Division - Group 2 |
| Oct 8, 2017 | Avarta(away) | 0-3 | 2nd Division - Group 2 |
| Sep 30, 2017 | Greve(home) | 0-1 | 2nd Division - Group 2 |
| Sep 23, 2017 | Marienlyst(away) | 1-1 | 2nd Division - Group 2 |
| Sep 16, 2017 | Kolding IF(away) | 0-1 | 2nd Division - Group 2 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 14, 2017 | Greve(home) | 4-4 | 2nd Division - Group 2 |
| Oct 7, 2017 | Marienlyst(away) | 0-5 | 2nd Division - Group 2 |
| Sep 30, 2017 | Kolding IF(home) | 4-1 | 2nd Division - Group 2 |
| Sep 24, 2017 | Avarta(away) | 2-0 | 2nd Division - Group 2 |
| Sep 16, 2017 | Dalum(home) | 2-0 | 2nd Division - Group 2 |
What does the head-to-head say?
In the last meeting: 0 Næsby wins, 0 draws, 1 HIK win.
| Date | Score | Competition |
|---|---|---|
| Aug 19, 2017 | HIK 4-3 Næsby | 2nd Division - Group 2 |
How many goals should we expect?
Næsby score 1.1 and concede 2.1 goals per match over their last 15; HIK score 1.7 and concede 1.8.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Næsby | 1.1 | 2.1 | 3 | 7/15 | 9/15 |
| HIK | 1.7 | 1.8 | 4 | 7/15 | 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 |
|---|---|---|---|---|---|---|---|---|
| 2 | HIK | 26 | 16 | 5 | 5 | 39 | 25 | 53 |
A question about Næsby vs HIK?
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