Vendsyssel FF vs HB Koge: result 1-0 and analysis
1. DivisionRegular Season - 4Kick-off on August 12, 2012 at 01:00 PM (UTC)Nord Energi Arena, Hjørring
Full time
What was the result of Vendsyssel FF vs HB Koge?
Vendsyssel FF won 1-0 on August 12, 2012.
Goalscorers
- 29′Dennis Ramonn OlsenVendsyssel FF
What is the recent form of both teams?
Over their last 15 matches in all competitions, Vendsyssel FF have 5 wins, 3 draws and 7 defeats; HB Koge have 2, 5 and 8.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 8, 2012 | Lyngby(away) | 1-3 | 1. Division |
| Aug 3, 2012 | Hobro(home) | 2-0 | 1. Division |
| Jul 29, 2012 | Vestsjælland(away) | 0-1 | 1. Division |
| Jun 10, 2012 | Jammerbugt(away) | 3-0 | 1. Division |
| Jun 5, 2012 | Hobro(home) | 0-0 | 1. Division |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 8, 2012 | AB Copenhagen(home) | 2-2 | 1. Division |
| Aug 5, 2012 | Fyn(away) | 2-2 | 1. Division |
| Jul 29, 2012 | Vejle(home) | 1-1 | 1. Division |
| May 23, 2012 | Odense(home) | 1-1 | Superliga |
| May 20, 2012 | Aalborg(away) | 0-1 | Superliga |
How many goals should we expect?
Vendsyssel FF score 1.1 and concede 1.3 goals per match over their last 15; HB Koge score 1.2 and concede 2.1.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Vendsyssel FF | 1.1 | 1.3 | 7 | 3/15 | 7/15 |
| HB Koge | 1.2 | 2.1 | 0 | 12/15 | 10/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
Vendsyssel FF sit 9th in 1. Division (10 points from 10 matches) and HB Koge sit 8th (10 points from 10 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 8 | HB Koge | 10 | 2 | 4 | 4 | 13 | 17 | 10 |
| 9 | Vendsyssel FF | 10 | 2 | 4 | 4 | 10 | 16 | 10 |
A question about Vendsyssel FF vs HB Koge?
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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