Skjold Sæby vs LSF: result 1-2 and analysis
Denmark Series - Group 1Regular Season - 8Kick-off on October 2, 2012 at 05:00 PM (UTC)Fælledparken, København
Full time
What was the result of Skjold Sæby vs LSF?
LSF won 1-2 on October 2, 2012.
What is the recent form of both teams?
Over their last 8 matches in all competitions, Skjold Sæby have 1 win, 3 draws and 4 defeats; LSF have 4, 2 and 1.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 22, 2012 | B 93(away) | 1-2 | Denmark Series - Group 1 |
| Sep 18, 2012 | Kastrup(home) | 4-4 | Denmark Series - Group 1 |
| Sep 14, 2012 | Frederikssund(home) | 0-0 | Denmark Series - Group 1 |
| Sep 8, 2012 | B 1903(away) | 1-2 | Denmark Series - Group 1 |
| Sep 4, 2012 | Vanløse(home) | 0-3 | Denmark Series - Group 1 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 22, 2012 | Skovshoved(home) | 0-0 | Denmark Series - Group 1 |
| Sep 15, 2012 | FA 2000(away) | 0-0 | Denmark Series - Group 1 |
| Sep 8, 2012 | Øresund OKF(home) | 4-0 | Denmark Series - Group 1 |
| Sep 1, 2012 | BGA(away) | 1-0 | Denmark Series - Group 1 |
| Aug 25, 2012 | Virum-Sorgenfri(away) | 3-0 | Denmark Series - Group 1 |
How many goals should we expect?
Skjold Sæby score 1.0 and concede 1.9 goals per match over their last 8; LSF score 2.0 and concede 0.6.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Skjold Sæby | 1.0 | 1.9 | 3 | 3/8 | 5/8 |
| LSF | 2.0 | 0.6 | 6 | 1/7 | 4/7 |
Over the last 8 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 7 | LSF | 18 | 7 | 1 | 10 | 32 | 32 | 22 |
A question about Skjold Sæby vs LSF?
Ask Footlab AI: lineups, absences, player form, stats, how the match could unfold.
Sign-in required. No odds displayed, no affiliation: the method is published and the accuracy is measured.
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