Slagelse B&I vs Frem: result 2-3 and analysis
2. DivisionGroup 1 - 14Kick-off on October 27, 2019 at 11:00 AM (UTC)Harboe Arena Slagelse, Slagelse
Full time
What was the result of Slagelse B&I vs Frem?
Frem won 2-3 on October 27, 2019.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Slagelse B&I have 3 wins, 3 draws and 9 defeats; Frem have 5, 5 and 5.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 19, 2019 | Vanløse(away) | 1-2 | 2. Division |
| Oct 12, 2019 | B 93(away) | 1-2 | 2. Division |
| Oct 6, 2019 | FC Helsingor(home) | 1-3 | 2. Division |
| Sep 29, 2019 | Avarta(away) | 0-1 | 2. Division |
| Sep 22, 2019 | Brønshøj(home) | 0-1 | 2. Division |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 22, 2019 | B 93(home) | 0-1 | 2. Division |
| Oct 12, 2019 | Hillerød(home) | 1-0 | 2. Division |
| Oct 5, 2019 | Skovshoved(away) | 4-0 | 2. Division |
| Sep 27, 2019 | FC Helsingor(away) | 1-1 | 2. Division |
| Sep 21, 2019 | Vanløse(home) | 1-1 | 2. Division |
What does the head-to-head say?
Across the last 3 meetings: 2 Slagelse B&I wins, 1 draw, 0 Frem wins.
| Date | Score | Competition |
|---|---|---|
| Aug 17, 2019 | Frem 1-2 Slagelse B&I | 2. Division |
| Oct 21, 2018 | Slagelse B&I 0-0 Frem | 2nd Division - Group 2 |
| Aug 4, 2018 | Frem 0-1 Slagelse B&I | 2nd Division - Group 2 |
How many goals should we expect?
Slagelse B&I score 0.8 and concede 1.5 goals per match over their last 15; Frem score 1.3 and concede 1.1.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Slagelse B&I | 0.8 | 1.5 | 5 | 7/15 | 7/15 |
| Frem | 1.3 | 1.1 | 5 | 8/15 | 8/15 |
Over the last 15 matches in all competitions.
A question about Slagelse B&I vs Frem?
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