· Bundesliga
Borussia Monchengladbach
ATT
5/10
DEF
5/10
1:2
TSG 1899 Hoffenheim
6/10
ATT
5/10
DEF
Full-time
Best Pick
BTTS
62%
Correct Score93′
Top
1-1
10.5%
9.00
Top
2-1
9.1%
12.00
1-2
7.4%
10.00
1-0
7.4%
21.00
2-2
6.5%
10.00
2-0
6.5%
23.00
0-1
6%
17.00
3-1
5.3%
21.00
145%
2.21TOP
X23%
4.29
231%
3.19
1X68%
X254%
1276%
xG — Expected Goals
Borussia Monchengladbach
Borussia Monchengladbach exp
TSG 1899 Hoffenheim
TSG 1899 Hoffenheim exp
goal
per 15 min
0–15′
15–30′
30–45′
45–60′
60–75′
75–90′
Borussia Monchengladbach
TSG 1899 Hoffenheim
Confirmed XI4-4-2
1
Nicolas
16
Sander
4
Diks
2
Chiarodia
26
Ullrich
29
Scally
47
Uno
10
Neuhaus
36
Mohya
38
Bolin
3
Lidberg
Impact Player Hot Head
Borussia Monchengladbach27 players
50.1/ 99Average
Top Rated
1Giovanni Reyna MID74
2Philipp SanderMID72
3David HeroldDEF64
TSG 1899 Hoffenheim23 players
54.9/ 99Average
Top Rated
1Koki MachidaDEF70
2Alexander PrassMID69
3Wouter BurgerMID66
Player Rankings
Snipers
Top goal threats
1
Shuto MachinoBorussia Monchengladbach
59
2
Adam DaghimTSG 1899 Hoffenheim
53
3
Fisnik AsllaniTSG 1899 Hoffenheim
53
4
Tim LemperleTSG 1899 Hoffenheim
51
5
Nicolas KühnBorussia Monchengladbach
50
Wall
Top defenders
1
Nico ElvediBorussia Monchengladbach
80
2
Ozan Kabak TSG 1899 Hoffenheim
70
3
Fabio ChiarodiaBorussia Monchengladbach
66
4
Jan LeszczynskiBorussia Monchengladbach
59
5
Arthur ChavesTSG 1899 Hoffenheim
59
Control
Top playmakers
1
Giovanni Reyna Borussia Monchengladbach
96
2
Wouter BurgerTSG 1899 Hoffenheim
76
3
Kevin StögerBorussia Monchengladbach
73
4
Leon AvdullahuTSG 1899 Hoffenheim
64
5
Fritz FleckBorussia Monchengladbach
62
Bad Boys
Most likely to get booked
1
Kevin DiksBorussia Monchengladbach
1
2
Shuto MachinoBorussia Monchengladbach
1
3
Adam DaghimTSG 1899 Hoffenheim
1
4
Max MoerstedtTSG 1899 Hoffenheim
8
5
Andrej KramaricTSG 1899 Hoffenheim
13
Power Rankings
Strongest overall
1
Giovanni Reyna Borussia Monchengladbach
74
2
Philipp SanderBorussia Monchengladbach
72
3
Koki MachidaTSG 1899 Hoffenheim
70
4
Alexander PrassTSG 1899 Hoffenheim
69
5
Wouter BurgerTSG 1899 Hoffenheim
66

Frequently Asked Questions

Our Poisson model calculates the probability of every possible scoreline for Borussia Monchengladbach vs TSG 1899 Hoffenheim 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 TSG 1899 Hoffenheim 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 TSG 1899 Hoffenheim 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.

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