Rodos vs Episkopi: prediction and stats
Super League 2Group B - 7Kick-off on December 12, 2021 at 01:00 PM (UTC)Stadio Diagora, Rodos
Match cancelled
What is the recent form of both teams?
Over their last 15 matches in all competitions, Rodos have 7 wins, 5 draws and 3 defeats; Episkopi have 3, 5 and 7.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Dec 5, 2021 | OF Ierapetra(away) | 1-1 | Super League 2 |
| Nov 28, 2021 | Zakynthos(home) | 4-0 | Super League 2 |
| Nov 24, 2021 | Kissamikos(away) | 2-2 | Super League 2 |
| Nov 21, 2021 | Diagoras(home) | 3-0 | Super League 2 |
| Nov 14, 2021 | Asteras Vlachioti(away) | 0-0 | Super League 2 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Dec 11, 2021 | OF Ierapetra(home) | 0-1 | Super League 2 |
| Dec 5, 2021 | Zakynthos(away) | 3-0 | Super League 2 |
| Nov 28, 2021 | Kissamikos(home) | 1-1 | Super League 2 |
| Nov 24, 2021 | Diagoras(away) | 0-1 | Super League 2 |
| Nov 20, 2021 | Asteras Vlachioti(home) | 0-1 | Super League 2 |
What does the head-to-head say?
Across the last 2 meetings: 0 Rodos wins, 2 draws, 0 Episkopi wins.
| Date | Score | Competition |
|---|---|---|
| May 9, 2021 | Episkopi 0-0 Rodos | Football League |
| Mar 28, 2021 | Rodos 0-0 Episkopi | Football League |
How many goals should we expect?
Rodos score 1.6 and concede 1.0 goals per match over their last 15; Episkopi score 0.9 and concede 0.9.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Rodos | 1.6 | 1.0 | 6 | 8/15 | 8/15 |
| Episkopi | 0.9 | 0.9 | 4 | 5/15 | 5/15 |
Over the last 15 matches in all competitions.
A question about Rodos vs Episkopi?
Ask Footlab AI: lineups, absences, player form, stats, how the match could unfold.
Sign-in required. No odds displayed, no affiliation: the method is published and the accuracy is measured.
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