Naestved vs B 93: result 2-0 and analysis
2. DivisionRegular Season - 11Kick-off on October 15, 2017 at 11:00 AM (UTC)MTM Service Park, Næstved
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What was the result of Naestved vs B 93?
Naestved won 2-0 on October 15, 2017.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Naestved have 7 wins, 2 draws and 6 defeats; B 93 have 5, 4 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 8, 2017 | Frem(home) | 1-0 | 2. Division |
| Sep 30, 2017 | Brønshøj(away) | 1-2 | 2. Division |
| Sep 24, 2017 | Hvidovre(home) | 1-2 | 2. Division |
| Sep 20, 2017 | HB Koge(home) | 1-3 | DBU Pokalen |
| Sep 16, 2017 | AB Copenhagen(away) | 1-1 | 2. Division |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 7, 2017 | Brønshøj(home) | 1-0 | 2. Division |
| Sep 30, 2017 | AB Copenhagen(away) | 1-1 | 2. Division |
| Sep 23, 2017 | Hillerød(away) | 1-3 | 2. Division |
| Sep 16, 2017 | Skovshoved(home) | 3-3 | 2. Division |
| Sep 9, 2017 | Frem(away) | 3-3 | 2. Division |
What does the head-to-head say?
Across the last 1 meetings: 1 Naestved win(s), 0 draw(s), 0 B 93 win(s).
| Date | Score | Competition |
|---|---|---|
| Sep 2, 2017 | B 93 1-5 Naestved | 2. Division |
How many goals should we expect?
Naestved score 1.6 and concede 1.3 goals per match over their last 15; B 93 score 1.8 and concede 1.9.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Naestved | 1.6 | 1.3 | 4 | 9/15 | 9/15 |
| B 93 | 1.8 | 1.9 | 4 | 9/15 | 10/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
Naestved sit 8th in 2. Division (5 points from 4 matches) and B 93 sit 5th (6 points from 4 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 5 | B 93 | 4 | 2 | 0 | 2 | 7 | 7 | 6 |
| 8 | Naestved | 4 | 1 | 2 | 1 | 4 | 5 | 5 |
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