Team comparison
Metrics, head-to-head meetings and a statistical outcome estimate for any two teams side by side.
Form · 5 matches
W
W
W
W
L
12 of 15
6
league position
VS
8 games
Form · 5 matches
L
D
D
L
L
2 of 15
11
league position
Attack
Average per match in the sample
1.3
Goals
per match
1.3
4.3
Shots on target
per match
4.4
5.3
Corners
per match
5.1
Possession and passing
Average per match in the sample
53
Possession
% за матч
48
380
Accurate passes
per match
333
Discipline
Lower is better
11.9
Fouls
per match
10.6
1.9
Yellow cards
per match
2.6
Defense
Lower is better
1.1
Goals conceded
per match
1.4
Personal Meetings
MEL ahead
draws
BRI ahead
18.04.2026
Brisbane Roar
2 : 3
Melbourne City
06.01.2026
Melbourne City
1 : 0
Brisbane Roar
31.10.2025
Brisbane Roar
0 : 0
Melbourne City
11.04.2025
Melbourne City
3 : 2
Brisbane Roar
11.01.2025
Melbourne City
1 : 0
Brisbane Roar
06.12.2024
Brisbane Roar
1 : 4
Melbourne City
10.02.2024
Brisbane Roar
5 : 1
Melbourne City
28.12.2023
Melbourne City
8 : 1
Brisbane Roar
Statistical estimate
1/X/2 by the Poisson model based on average goals
1X2
The home team scores an average of 1.3 goals per match — more than the opponent (1.0).
The home team concedes an average of 1.3 goals per match — fewer than the opponent (1.4).
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.