Llagostera vs Sabadell: result 0-1 and analysis
Primera División RFEF - Group 3Group 3 - 8Kick-off on October 12, 2019 at 04:00 PM (UTC)Estadio Municipal de Llagostera, Llagostera
Full time
What was the result of Llagostera vs Sabadell?
Sabadell won 0-1 on October 12, 2019.
Goalscorers
- 86′Edgar HernándezSabadell
What is the recent form of both teams?
Over their last 7 matches in all competitions, Llagostera have 4 wins, 1 draws and 2 defeats; Sabadell have 3, 3 and 1.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 5, 2019 | Orihuela(away) | 3-0 | Primera División RFEF - Group 3 |
| Sep 28, 2019 | Hércules(home) | 2-1 | Primera División RFEF - Group 3 |
| Sep 21, 2019 | Levante II(away) | 0-1 | Primera División RFEF - Group 3 |
| Sep 14, 2019 | Villarreal II(home) | 0-3 | Primera División RFEF - Group 3 |
| Sep 7, 2019 | Prat(away) | 2-1 | Primera División RFEF - Group 3 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 6, 2019 | Olot(home) | 1-1 | Primera División RFEF - Group 3 |
| Sep 29, 2019 | Orihuela(away) | 1-1 | Primera División RFEF - Group 3 |
| Sep 22, 2019 | La Nucía(home) | 1-0 | Primera División RFEF - Group 3 |
| Sep 15, 2019 | Hércules(away) | 2-0 | Primera División RFEF - Group 3 |
| Sep 8, 2019 | Valencia II(home) | 0-0 | Primera División RFEF - Group 3 |
How many goals should we expect?
Llagostera score 1.7 and concede 1.3 goals per match over their last 7; Sabadell score 1.0 and concede 0.7.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Llagostera | 1.7 | 1.3 | 1 | 4/7 | 6/7 |
| Sabadell | 1.0 | 0.7 | 3 | 3/7 | 1/7 |
Over the last 7 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 4 | Llagostera | 20 | 7 | 8 | 5 | 19 | 19 | 29 |
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