Team comparison
Metrics, head-to-head meetings and a statistical outcome estimate for any two teams side by side.
Form · 10 matches
D
L
W
L
W
L
L
L
W
W
13 of 30
6
league position
VS
10 games
Form · 10 matches
W
D
W
W
D
W
W
W
L
W
23 of 30
2
league position
Attack
Average per match in the sample
1.4
Goals
per match
1.7
0.0
Shots on target
per match
0.0
0.0
Corners
per match
0.0
Possession and passing
Average per match in the sample
0
Possession
% за матч
0
0
Accurate passes
per match
0
Discipline
Lower is better
0.0
Fouls
per match
0.0
0.0
Yellow cards
per match
0.0
Defense
Lower is better
1.3
Goals conceded
per match
1.2
Personal Meetings
SEO ahead
draws
SUW ahead
10.07.2026
Seoul W
0 : 3
Suwon FMC W
01.07.2026
Seoul W
0 : 3
Suwon FMC W
04.04.2026
Suwon FMC W
2 : 1
Seoul W
18.09.2025
Suwon FMC W
1 : 2
Seoul W
23.06.2025
Seoul W
1 : 1
Suwon FMC W
12.05.2025
Suwon FMC W
1 : 3
Seoul W
10.04.2025
Seoul W
3 : 2
Suwon FMC W
29.08.2024
Suwon FMC W
2 : 0
Seoul W
27.06.2024
Seoul W
5 : 6
Suwon FMC W
06.05.2024
Suwon FMC W
4 : 1
Seoul W
Statistical estimate
1/X/2 by the Poisson model based on average goals
1X2
The away team scores an average of 1.7 goals per match — more than the home team (1.2).
The away team concedes an average of 1.1 goals per match — fewer than the home team (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.