Both attacks may lack polish, but porous defenses and a lively chance-creation profile point toward an open contest. Union’s home pressure and Cologne’s threat should expose enough space for goals to carry the match beyond the cautious start.
Match GoalsOver 2.5
En iyi tahmin
KG VAR
60%
Doğru skor
Mükemmel
1-1
10.8%
7.00
Mükemmel
2-1
9.4%
10.00
1-0
8.3%
11.00
2-0
7.3%
15.00
1-2
7%
10.00
0-1
6.2%
11.00
2-2
6.1%
12.00
3-1
5.5%
19.00
148%
2.50TOP
X23%
3.60
229%
2.60
1X71%
X252%
1277%
Kombine
2 seçim
Union’s home advantage gives them the steadier platform, while both sides’ porous defending leaves the door open to a lively, chance-filled contest. Their attacking records may be modest, but the combined threat should produce goals; Union look best placed to avoid defeat, making the home-or-draw and over-goals combination the compelling script.
1Match GoalsOver 2.5
2Double Chance1. FC Union Berlin or Draw
Confirmed XI3-5-2
1
Rönnow
4
Bosch
14
Querfeld
15
Rothe
19
Haberer
13
Schäfer
8
Khedira
20
Aebischer
21
Skarke
11
Jeong
9
Burcu
Impact Player Hot Head
1. FC Union Berlin30 oyuncu
48.1/ 99Orta
En İyiler
1Marvin FriedrichDEF86
2Dmytro BogdanovFWD83
3Leopold QuerfeldDEF82
Cologne25 oyuncu
48.1/ 99Orta
En İyiler
1Luca WaldschmidtFWD78
2Rav van den BergDEF66
3Thijs DallingaFWD66
Oyuncu sıralamaları
Keskin nişancılar
En büyük gol tehdidi
1
Dmytro Bogdanov1. FC Union Berlin
99
2
Luca WaldschmidtCologne
99
3
Thijs DallingaCologne
70
4
Andrej Ilic1. FC Union Berlin
58
5
Ragnar AcheCologne
58
Duvar
En iyi savunmacılar
1
Marvin Friedrich1. FC Union Berlin
99
2
Leopold Querfeld1. FC Union Berlin
76
3
Felix Uduokhai1. FC Union Berlin
71
4
Stanley Nsoki1. FC Union Berlin
68
5
Jahmai Simpson-Pusey Cologne
64
Kontrol
En iyi oyun kurucular
1
Aljoscha Kemlein 1. FC Union Berlin
67
2
Ellyes Skhiri Cologne
58
3
Ísak JóhannessonCologne
55
4
Kastriot Imeri1. FC Union Berlin
54
5
Janik Haberer1. FC Union Berlin
53
Yaramaz çocuklar
Kart görme olasılığı en yüksek
1
Janik Haberer1. FC Union Berlin
1
Agresiflik 68
2
Livan Burcu1. FC Union Berlin
1
Agresiflik 53
3
Oliver Burke1. FC Union Berlin
1
Agresiflik 26
4
Tim Skarke1. FC Union Berlin
1
Agresiflik 54
5
Jahmai Simpson-Pusey Cologne
1
Agresiflik 21
Güç sıralaması
Genel olarak en güçlüler
1
Marvin Friedrich1. FC Union Berlin
86
2
Dmytro Bogdanov1. FC Union Berlin
83
3
Leopold Querfeld1. FC Union Berlin
82
4
Luca WaldschmidtCologne
78
5
Rav van den BergCologne
66
Sıkça Sorulan Sorular
Our Poisson model calculates the probability of every possible scoreline for 1. FC Union Berlin vs Cologne based on each team's expected goals (xG). The top-3 most likely scorelines are shown above with their probability percentages. Even the highest-probability score rarely exceeds 12-15% chance, as football is a low-scoring sport.
The Bet Builder combines multiple selections from the 1. FC Union Berlin vs Cologne match into one bet. Our AI identifies outcomes that complement each other — for example, a home win paired with over 2.5 goals and both teams to score. All selections must win for the combined bet to pay out, which means higher combined odds but also higher risk.
xG (expected goals) measures the quality of scoring chances. If 1. FC Union Berlin has an xG of 1.8, it means they are expected to score around 1-2 goals based on chance quality. The model uses pre-match xG to build a probability table for all possible scorelines. A team can overperform xG (score more than expected) or underperform xG (score fewer).
Yes, all predictions on ProSoccer are completely free. You can view predicted scorelines, over/under probabilities, and bet builder suggestions for 1. FC Union Berlin vs Cologne without paying or registering. Odds values are revealed after a tap to keep the page compliant with search engine guidelines.
A value bet occurs when the probability of an outcome is higher than what the bookmaker odds suggest. For example, if our model gives 1. FC Union Berlin a 55% chance of winning but the odds imply only 40%, that is a value bet. Our AI highlights selections where the model probability exceeds the implied probability from the odds.
AI predictions use statistical modeling (Poisson distribution) based on historical data and pre-match metrics. They are more reliable over large samples than for any single match. No prediction is guaranteed — football has inherent unpredictability. Our model typically identifies the correct top-3 scorelines in 25-30% of matches, which is significantly better than random chance.