Gais vs Atvidabergs FF: result 1-0 and analysis
SuperettanRegular Season - 7Kick-off on May 11, 2016 at 05:00 PM (UTC)Gamla Ullevi, Göteborg
Full time
What was the result of Gais vs Atvidabergs FF?
Gais won 1-0 on May 11, 2016.
Goalscorers
- 9′L. SinghGais
Official lineup for Gais vs Atvidabergs FF
The starting elevens fielded at kick-off.
Gais
- 2J. Sinclair
- 5L. Singh
- 8C. Henderson
- 10L. Mijaljevic
- 11K. Cadogan
- 21Johan Lundgren
- 4Steven David Old
- 6Carl Nyström
- 16J. Ramhorn
- 26M. Moënza
- 1T. Vaiho
Atvidabergs FF
- 7Mahmoud Eid
- 9Shkodran Maholli
- 18M. Ćosić
- 6Ammar Ahmed
- 10Björn Mikael André Westerblad
- 14Simon Helg
- 2J. Birkfeldt
- 3M. Berg
- 23K. Deeromram
- 28S. Ramhorn
- 1Gustav Jansson
What is the recent form of both teams?
Over their last 6 matches in all competitions, Gais have 1 win, 3 draws and 2 defeats; Atvidabergs FF have 3, 1 and 2.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 8, 2016 | Dalkurd FF(away) | 2-2 | Superettan |
| Apr 30, 2016 | Orgryte IS(home) | 0-0 | Superettan |
| Apr 23, 2016 | Halmstad(away) | 0-2 | Superettan |
| Apr 16, 2016 | Syrianska FC(home) | 1-1 | Superettan |
| Apr 9, 2016 | AFC Eskilstuna(away) | 0-3 | Superettan |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 7, 2016 | Trelleborg(home) | 2-0 | Superettan |
| Apr 30, 2016 | Degerfors IF(away) | 3-0 | Superettan |
| Apr 24, 2016 | Assyriska FF(home) | 2-1 | Superettan |
| Apr 17, 2016 | Ljungskile SK(away) | 2-2 | Superettan |
| Apr 10, 2016 | Sirius(home) | 0-3 | Superettan |
How many goals should we expect?
Gais score 0.8 and concede 1.3 goals per match over their last 6; Atvidabergs FF score 1.7 and concede 1.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Gais | 0.8 | 1.3 | 2 | 2/6 | 2/6 |
| Atvidabergs FF | 1.7 | 1.3 | 2 | 3/6 | 5/6 |
Over the last 6 matches in all competitions.
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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