B 93 W vs Naestved W: result 2-1 and analysis
B-Liga WomenRegular Season - 5Kick-off on September 12, 2026 at 11:00 AM (UTC)
Full time
What was the result of B 93 W vs Naestved W?
B 93 W won 2-1 on September 12, 2026.
Goalscorers
- 13′?B 93 W
- 58′F. AbildåB 93 W
- 73′?Naestved W
What is the recent form of both teams?
Over their last 15 matches in all competitions, B 93 W have 4 wins, 0 draws and 11 defeats; Naestved W have 2, 0 and 2.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 5, 2026 | Osterbro W(away) | 1-3 | B-Liga Women |
| Aug 29, 2026 | AaB W(home) | 4-0 | B-Liga Women |
| Aug 22, 2026 | Sundby W(away) | 0-2 | B-Liga Women |
| Aug 15, 2026 | Viborg W(home) | 2-1 | B-Liga Women |
| Jun 15, 2025 | Midtjylland W(home) | 0-1 | Kvindeliga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 6, 2026 | Viborg W(home) | 1-2 | B-Liga Women |
| Aug 29, 2026 | Osterbro W(home) | 0-1 | B-Liga Women |
| Aug 23, 2026 | Esbjerg W(away) | 2-1 | B-Liga Women |
| Aug 15, 2026 | AaB W(home) | 1-0 | B-Liga Women |
How many goals should we expect?
B 93 W score 1.0 and concede 2.5 goals per match over their last 15; Naestved W score 1.0 and concede 1.0.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| B 93 W | 1.0 | 2.5 | 3 | 6/15 | 11/15 |
| Naestved W | 1.0 | 1.0 | 1 | 2/4 | 2/4 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
B 93 W sit 1st in B-Liga Women (27 points from 11 matches) and Naestved W sit 2nd (25 points from 12 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 1 | B 93 W | 11 | 9 | 0 | 2 | 24 | 14 | 27 |
| 2 | Naestved W | 12 | 8 | 1 | 3 | 26 | 10 | 25 |
A question about B 93 W vs Naestved W?
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