Team comparison
Metrics, head-to-head meetings and a statistical outcome estimate for any two teams side by side.
Form · 5 matches
W
W
L
L
D
7 of 15
9
league position
VS
10 games
Form · 5 matches
L
L
L
D
L
1 of 15
12
league position
Attack
Average per match in the sample
1.0
Goals
per match
1.3
2.9
Shots on target
per match
3.6
3.8
Corners
per match
4.1
Possession and passing
Average per match in the sample
45
Possession
% за матч
47
291
Accurate passes
per match
303
Discipline
Lower is better
13.5
Fouls
per match
14.8
2.4
Yellow cards
per match
3.2
Defense
Lower is better
1.4
Goals conceded
per match
1.6
Personal Meetings
PAN ahead
draws
VOL ahead
20.12.2025
Volos NFC
1 : 0
Panetolikos
13.09.2025
Panetolikos
1 : 2
Volos NFC
10.05.2025
Panetolikos
0 : 3
Volos NFC
06.04.2025
Volos NFC
0 : 0
Panetolikos
08.02.2025
Volos NFC
0 : 1
Panetolikos
26.10.2024
Panetolikos
0 : 1
Volos NFC
31.07.2024
Panetolikos
2 : 2
Volos NFC
06.04.2024
Panetolikos
0 : 1
Volos NFC
03.02.2024
Volos NFC
1 : 1
Panetolikos
21.10.2023
Panetolikos
2 : 0
Volos NFC
Statistical estimate
1/X/2 by the Poisson model based on average goals
1X2
The home team scores an average of 0.8 goals per match — more than the opponent (0.8).
The home team concedes an average of 0.9 goals per match — fewer than the opponent (1.6).
Estimate — a statistical Poisson model based on average goals, not an AI-model prediction.
This is not an AI model prediction — it's a simple statistical estimate based on average figures, without accounting for lineups, injuries or opponents' form.