Despite both attacks’ modest ratings, the combined chance creation points toward an open contest. Gladbach’s home urgency should bring sustained pressure, while Paderborn can exploit space on the break; once the game opens, the scoring threshold appears likely to be surpassed.
Match GoalsOver 2.5
En iyi tahmin
KG VAR
61%
Doğru skor
Mükemmel
1-1
10.3%
8.50
Mükemmel
2-1
9.5%
9.00
1-0
7.9%
12.00
2-0
7.3%
12.00
1-2
6.7%
13.00
2-2
6.2%
12.00
3-1
5.9%
13.00
0-1
5.6%
17.00
150%
1.90TOP
X23%
3.90
227%
3.50
1X73%
X250%
1277%
Kombine
3 seçim
Borussia Monchengladbach’s 1.67 xG edges Paderborn’s 1.31, and home advantage supports the hosts taking control. Though both defenses look stable, the combined 2.98 xG points toward a lively contest and Over 2.5 goals. Iaia Manco Danfa is the scorer pick to complete the 2.93-priced builder.
1Match WinnerBorussia Monchengladbach
2Match GoalsOver 2.5
3GoalscorersAnytime
Confirmed XI5-4-1
1
Nicolas
14
Hashioka
16
Sander
2
Chiarodia
29
Scally
26
Ullrich
47
Uno
10
Neuhaus
36
Mohya
38
Bolin
18
Machino
Impact Player Hot Head
Borussia Monchengladbach30 oyuncu
50.3/ 99Orta
En İyiler
1Giovanni Reyna MID75
2Philipp SanderMID72
3David HeroldDEF65
Paderborn19 oyuncu
54.3/ 99Orta
En İyiler
1Steffen TiggesFWD76
2Laurin CurdaMID72
3Felix Götze DEF69
Oyuncu sıralamaları
Keskin nişancılar
En büyük gol tehdidi
1
Steffen TiggesPaderborn
79
2
Shuto MachinoBorussia Monchengladbach
58
3
Rayan PhilippePaderborn
51
4
Nicolas KühnBorussia Monchengladbach
49
5
Isac LidbergBorussia Monchengladbach
46
Duvar
En iyi savunmacılar
1
Nico ElvediBorussia Monchengladbach
78
2
Felix Götze Paderborn
70
3
Fabio ChiarodiaBorussia Monchengladbach
66
4
Tjark SchellerPaderborn
60
5
Jan LeszczynskiBorussia Monchengladbach
59
Kontrol
En iyi oyun kurucular
1
Giovanni Reyna Borussia Monchengladbach
97
2
Kevin StögerBorussia Monchengladbach
77
3
Florian NeuhausBorussia Monchengladbach
67
4
Fritz FleckBorussia Monchengladbach
62
5
Philipp SanderBorussia Monchengladbach
61
Yaramaz çocuklar
Kart görme olasılığı en yüksek
1
Kevin DiksBorussia Monchengladbach
1
Agresiflik 34
2
Shuto MachinoBorussia Monchengladbach
1
Agresiflik 42
3
Joe ScallyBorussia Monchengladbach
18
Agresiflik 62
4
Zento UnoBorussia Monchengladbach
20
Agresiflik 62
5
Kevin StögerBorussia Monchengladbach
21
Agresiflik 67
Güç sıralaması
Genel olarak en güçlüler
1
Steffen TiggesPaderborn
76
2
Giovanni Reyna Borussia Monchengladbach
75
3
Philipp SanderBorussia Monchengladbach
72
4
Laurin CurdaPaderborn
72
5
Felix Götze Paderborn
69
Sıkça Sorulan Sorular
Our Poisson model calculates the probability of every possible scoreline for Borussia Monchengladbach vs Paderborn 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 Borussia Monchengladbach vs Paderborn 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 Borussia Monchengladbach 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 Borussia Monchengladbach vs Paderborn 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 Borussia Monchengladbach 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.