Team comparison
Metrics, head-to-head meetings and a statistical outcome estimate for any two teams side by side.
Form · 10 matches
W
L
W
W
W
W
W
D
D
L
20 of 30
1
league position
VS
10 games
Form · 10 matches
L
D
W
W
L
L
W
W
W
D
17 of 30
4
league position
Attack
Average per match in the sample
1.7
Goals
per match
1.3
2.5
Shots on target
per match
0.0
2.0
Corners
per match
0.0
Possession and passing
Average per match in the sample
34
Possession
% за матч
0
232
Accurate passes
per match
0
Discipline
Lower is better
7.0
Fouls
per match
0.0
2.0
Yellow cards
per match
0.0
Defense
Lower is better
0.8
Goals conceded
per match
0.8
Personal Meetings
MOU ahead
draws
WAT ahead
28.04.2026
Mount Pleasant Academy
2 : 1
Waterhouse
25.01.2026
Mount Pleasant Academy
0 : 1
Waterhouse
05.10.2025
Waterhouse
1 : 1
Mount Pleasant Academy
05.03.2025
Mount Pleasant Academy
1 : 0
Waterhouse
29.12.2024
Waterhouse
0 : 3
Mount Pleasant Academy
24.10.2024
Mount Pleasant Academy
0 : 0
Waterhouse
12.05.2024
Mount Pleasant Academy
2 : 1
Waterhouse
06.05.2024
Waterhouse
1 : 1
Mount Pleasant Academy
03.03.2024
Waterhouse
0 : 1
Mount Pleasant Academy
03.12.2023
Mount Pleasant Academy
0 : 0
Waterhouse
Statistical estimate
1/X/2 by the Poisson model based on average goals
1X2
The home team scores an average of 1.8 goals per match — more than the opponent (1.3).
The home team concedes an average of 0.6 goals per match — fewer than the opponent (0.8).
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.