Episkopi vs Fostiras: result 3-0 and analysis
Football LeagueNotios - 1Kick-off on September 30, 2013 at 01:00 PM (UTC)Dimotiko Gipedo Episkopis, Episkopi
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What was the result of Episkopi vs Fostiras?
Episkopi won 3-0 on September 30, 2013.
Goalscorers
- 24′Dimitris SoubasakisEpiskopi
- 27′Antonis ManousakisEpiskopi
- 82′Stylianos DelibasisEpiskopi
Official lineup for Episkopi vs Fostiras
The starting elevens fielded at kick-off.
Episkopi
- 7Dimitris Soubasakis
- 23Giorgos Velonakis
- 3Georgios Vidalis
- 5V. Poulakis
- 10Bozidar Tadic
- 26C. Vourvahakis
- 28G. González
- 32Antonis Manousakis
- 8Stylianos Delibasis
- 21D. Spatharas
- 31M. Kalogerakis
Fostiras
- 11G. Panagiotopoulos
- 17A. Vouzas
- 4S. Andrikos
- 15Dionysios Giannoulis
- 16Anthony Tochukwu Emeka
- 23C. Coulibaly
- 27Stelios Makridis
- 77K. Kimani
- 6G. Kargas
- 22Ilias Kakaras
- 28T. Moschonas
What is the recent form of both teams?
Over their last 2 matches in all competitions, Episkopi have 0 wins, 0 draws and 2 defeats; Fostiras have 3, 1 and 4.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 15, 2013 | Asteras Magoula(away) | 1-2 | Cup |
| Oct 24, 2012 | Vyzas(home) | 0-1 | Cup |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 26, 2013 | Atromitos(home) | 0-1 | Cup |
| Sep 18, 2013 | Paniliakos(away) | 2-1 | Cup |
| Jan 24, 2013 | PAS Giannina(home) | 2-3 | Cup |
| Jan 10, 2013 | PAS Giannina(away) | 0-2 | Cup |
| Dec 19, 2012 | Panionios(away) | 1-2 | Cup |
How many goals should we expect?
Episkopi score 0.5 and concede 1.5 goals per match over their last 2; Fostiras score 1.3 and concede 1.1.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Episkopi | 0.5 | 1.5 | 0 | 1/2 | 1/2 |
| Fostiras | 1.3 | 1.1 | 3 | 3/8 | 4/8 |
Over the last 2 matches in all competitions.
A question about Episkopi vs Fostiras?
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