Kissamikos vs PAS Giannina: result 0-1 and analysis
Super League 2Regular Season - 4Kick-off on November 8, 2019 at 03:00 PM (UTC)Dimotiko Stadio Perivolion, Perivolia
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What was the result of Kissamikos vs PAS Giannina?
PAS Giannina won 0-1 on November 8, 2019.
Goalscorers
- 59′A. KartalisPAS Giannina
What is the recent form of both teams?
Over their last 15 matches in all competitions, Kissamikos have 6 wins, 5 draws and 4 defeats; PAS Giannina have 4, 6 and 5.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Nov 3, 2019 | Platanias(away) | 1-1 | Super League 2 |
| Oct 27, 2019 | Apollon Smirnis(home) | 0-1 | Super League 2 |
| Sep 29, 2019 | Apollon Pontou(away) | 4-0 | Super League 2 |
| Sep 25, 2019 | Kavala(away) | 0-2 | Cup |
| May 5, 2019 | Apollon Pontou(away) | 3-1 | Football League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Nov 4, 2019 | Ergotelis(home) | 2-2 | Super League 2 |
| Oct 29, 2019 | Veria(home) | 1-0 | Cup |
| Oct 25, 2019 | Levadiakos(away) | 2-1 | Super League 2 |
| Oct 2, 2019 | Aspropyrgos Enosis(away) | 2-0 | Cup |
| Sep 29, 2019 | Panachaiki FC(away) | 1-1 | Super League 2 |
How many goals should we expect?
Kissamikos score 1.5 and concede 0.8 goals per match over their last 15; PAS Giannina score 0.8 and concede 0.9.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Kissamikos | 1.5 | 0.8 | 6 | 6/15 | 7/15 |
| PAS Giannina | 0.8 | 0.9 | 6 | 5/15 | 3/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
Kissamikos sit 9th in Super League 2 (12 points from 18 matches) and PAS Giannina sit 9th (10 points from 18 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 9 | PAS Giannina | 18 | 2 | 4 | 12 | 10 | 24 | 10 |
| 9 | Kissamikos | 18 | 3 | 3 | 12 | 11 | 28 | 12 |
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