AOK Kerkyra vs Panionios: result 0-3 and analysis
Super League 1Regular Season - 4Kick-off on September 24, 2011 at 02:15 PM (UTC)Stadio Kerkyras, Corfu
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What was the result of AOK Kerkyra vs Panionios?
Panionios won 0-3 on September 24, 2011.
Goalscorers
- 34′N. KuqiPanionios
- 78′N. KuqiPanionios
- 83′F. GoundoulakisPanionios
Official lineup for AOK Kerkyra vs Panionios
The starting elevens fielded at kick-off.
AOK Kerkyra
- 7Christos Kalantzis
- 10A. Agritis
- 5A. Venetis
- 11Tumer Metin
- 22A. Osman
- 23G. Barkoglou
- 25Gustavo Veronezi Nacarato
- 28F. Lovin
- 3Lefteris Sakellariou
- 4Timo Wenzel
- 15M. Galinović
Panionios
- 9N. Kuqi
- 10F. Estoyanoff
- 6Souleiman Akim Omolade
- 15B. Kumordzi
- 20F. Goundoulakis
- 22A. Samaris
- 32Dejan Milovanovic
- 4Per Markus Jonsson
- 23D. Siovas
- 26E. Cocalić
- 21Dimitrios Eleftheropoulos
What is the recent form of both teams?
Over their last 3 matches in all competitions, AOK Kerkyra have 0 wins, 1 draw and 2 defeats; Panionios have 1, 1 and 1.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 17, 2011 | Panetolikos(home) | 2-3 | Super League 1 |
| Sep 11, 2011 | Asteras Tripolis(away) | 0-0 | Super League 1 |
| Aug 28, 2011 | Panathinaikos(home) | 0-2 | Super League 1 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 18, 2011 | PAOK(home) | 1-2 | Super League 1 |
| Sep 10, 2011 | Panetolikos(away) | 1-0 | Super League 1 |
| Aug 28, 2011 | Ergotelis(home) | 2-2 | Super League 1 |
How many goals should we expect?
AOK Kerkyra score 0.7 and concede 1.7 goals per match over their last 3; Panionios score 1.3 and concede 1.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| AOK Kerkyra | 0.7 | 1.7 | 1 | 1/3 | 1/3 |
| Panionios | 1.3 | 1.3 | 1 | 2/3 | 2/3 |
Over the last 3 matches in all competitions.
A question about AOK Kerkyra vs Panionios?
Ask Footlab AI: lineups, absences, player form, stats, how the match could unfold.
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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