Volos NFC vs Panetolikos: result 3-2 and analysis
Super League 1Regular Season - 10Kick-off on November 9, 2019 at 03:15 PM (UTC)Panthessaliko Stadio, Volos
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What was the result of Volos NFC vs Panetolikos?
Volos NFC won 3-2 on November 9, 2019.
Goalscorers
- 39′P. SagnaPanetolikos
- 55′Juan MuñizVolos NFC
- 66′V. MantzisVolos NFC
- 68′G. AriyibiPanetolikos
- 78′E. JendrišekVolos NFC
What is the recent form of both teams?
Over their last 15 matches in all competitions, Volos NFC have 5 wins, 2 draws and 8 defeats; Panetolikos have 2, 3 and 10.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Nov 4, 2019 | Lamia(away) | 0-1 | Super League 1 |
| Oct 29, 2019 | Panserraikos(away) | 1-1 | Cup |
| Oct 26, 2019 | PAOK(home) | 0-2 | Super League 1 |
| Oct 20, 2019 | AEK Athens FC(away) | 2-3 | Super League 1 |
| Oct 6, 2019 | Atromitos(home) | 2-3 | Super League 1 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Nov 3, 2019 | Asteras Tripolis(home) | 1-1 | Super League 1 |
| Oct 31, 2019 | Ialysos(away) | 4-0 | Cup |
| Oct 27, 2019 | Aris Thessalonikis(away) | 0-2 | Super League 1 |
| Oct 19, 2019 | Larisa(home) | 2-2 | Super League 1 |
| Oct 7, 2019 | Lamia(away) | 0-0 | Super League 1 |
How many goals should we expect?
Volos NFC score 1.4 and concede 1.7 goals per match over their last 15; Panetolikos score 0.8 and concede 2.0.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Volos NFC | 1.4 | 1.7 | 4 | 7/15 | 8/15 |
| Panetolikos | 0.8 | 2.0 | 3 | 6/15 | 9/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
Volos NFC sit 12th in Super League 1 (0 points from 1 matches) and Panetolikos sit 3rd (3 points from 1 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 3 | Panetolikos | 1 | 1 | 0 | 0 | 3 | 1 | 3 |
| 12 | Volos NFC | 1 | 0 | 0 | 1 | 0 | 2 | 0 |
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