Team comparison
Metrics, head-to-head meetings and a statistical outcome estimate for any two teams side by side.
Form · 7 matches
L
L
L
L
L
D
W
4 of 21
7
league position
VS
8 games
Form · 5 matches
L
L
D
D
W
5 of 15
8
league position
Attack
Average per match in the sample
1.7
Goals
per match
1.1
4.4
Shots on target
per match
4.4
4.2
Corners
per match
3.1
Possession and passing
Average per match in the sample
52
Possession
% за матч
48
283
Accurate passes
per match
274
Discipline
Lower is better
11.4
Fouls
per match
12.6
3.3
Yellow cards
per match
2.9
Defense
Lower is better
1.8
Goals conceded
per match
2.3
Personal Meetings
BLO ahead
draws
JOR ahead
24.09.2025
Jorge Wilstermann
1 : 0
Blooming
11.07.2025
Jorge Wilstermann
1 : 2
Blooming
27.06.2025
Blooming
2 : 0
Jorge Wilstermann
10.05.2025
Blooming
3 : 1
Jorge Wilstermann
01.03.2025
Blooming
6 : 0
Jorge Wilstermann
27.02.2025
Jorge Wilstermann
0 : 1
Blooming
20.10.2024
Jorge Wilstermann
3 : 0
Blooming
23.05.2024
Blooming
3 : 0
Jorge Wilstermann
Statistical estimate
1/X/2 by the Poisson model based on average goals
1X2
The home team scores an average of 1.2 goals per match — more than the opponent (1.2).
The away team concedes an average of 1.0 goals per match — fewer than the home team (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.