Statistics / Football / Germany. Bundesliga

Germany Germany Bundesliga Statistics (36)

Predictions

Bundesliga 2025/26 Season Overview

08-22
100%
05-16
  • League goals trend: Average goals per match 3.24
  • Home win rate: About 44%
  • Away win rate: About 32%
  • BTTS rate (both teams to score): About 62%
  • Over 2.5 average hit rate: About 64%
  • Most attacking teams: Bayern München
  • Best defensive teams: Borussia Dortmund
Germany Germany. Bundesliga (36)
xG Accuracy
May 16
13:30
Bayern München Bayern München
5 3.14 1 1.58
1. FC Köln 1. FC Köln
51%
May 16
13:30
SC Freiburg SC Freiburg
4 1.56 1 1.84
RB Leipzig RB Leipzig
41%
May 16
13:30
FC St. Pauli FC St. Pauli
1 1.21 3 1.20
VfL Wolfsburg VfL Wolfsburg
58%
May 16
13:30
Werder Bremen Werder Bremen
0 1.26 2 1.65
Borussia Dortmund Borussia Dortmund
64%
May 16
13:30
Borussia Mönchengladbach Borussia Mönchengladbach
4 1.37 0 1.34
1899 Hoffenheim 1899 Hoffenheim
34%
May 16
13:30
1. FC Heidenheim 1. FC Heidenheim
0 1.42 2 1.71
FSV Mainz 05 FSV Mainz 05
62%
May 16
13:30
Bayer Leverkusen Bayer Leverkusen
1 3.23 1 0.93
Hamburger SV Hamburger SV
53%
May 16
13:30
Eintracht Frankfurt Eintracht Frankfurt
2 1.48 2 1.66
VfB Stuttgart VfB Stuttgart
79%
May 16
13:30
Union Berlin Union Berlin
4 1.53 0 1.88
FC Augsburg FC Augsburg
30%
May 10
17:30
FSV Mainz 05 FSV Mainz 05
1 2.62 3 0.88
Union Berlin Union Berlin
36%
May 10
15:30
1. FC Köln 1. FC Köln
1 2.08 3 1.24
1. FC Heidenheim 1. FC Heidenheim
46%
May 10
13:30
Hamburger SV Hamburger SV
3 1.38 2 1.66
SC Freiburg SC Freiburg
58%
May 09
16:30
VfL Wolfsburg VfL Wolfsburg
0 1.32 1 3.12
Bayern München Bayern München
39%
May 09
13:30
1899 Hoffenheim 1899 Hoffenheim
1 1.69 0 1.06
Werder Bremen Werder Bremen
62%
May 09
13:30
FC Augsburg FC Augsburg
3 1.87 1 1.12
Borussia Mönchengladbach Borussia Mönchengladbach
71%
May 09
13:30
VfB Stuttgart VfB Stuttgart
3 2.21 1 1.73
Bayer Leverkusen Bayer Leverkusen
66%
May 09
13:30
RB Leipzig RB Leipzig
2 2.79 1 0.72
FC St. Pauli FC St. Pauli
74%
May 08
18:30
Borussia Dortmund Borussia Dortmund
3 2.60 2 0.92
Eintracht Frankfurt Eintracht Frankfurt
67%
May 03
17:30
SC Freiburg SC Freiburg
1 1.82 1 1.16
VfL Wolfsburg VfL Wolfsburg
76%
May 03
15:30
Borussia Mönchengladbach Borussia Mönchengladbach
1 1.00 0 1.87
Borussia Dortmund Borussia Dortmund
60%
May 03
13:30
FC St. Pauli FC St. Pauli
1 0.97 2 1.69
FSV Mainz 05 FSV Mainz 05
91%
May 02
16:30
Bayer Leverkusen Bayer Leverkusen
4 1.78 1 2.00
RB Leipzig RB Leipzig
41%
May 02
13:30
Bayern München Bayern München
3 3.24 3 1.16
1. FC Heidenheim 1. FC Heidenheim
56%
May 02
13:30
Werder Bremen Werder Bremen
1 1.73 3 1.31
FC Augsburg FC Augsburg
51%
May 02
13:30
1899 Hoffenheim 1899 Hoffenheim
3 1.83 3 1.60
VfB Stuttgart VfB Stuttgart
49%
May 02
13:30
Eintracht Frankfurt Eintracht Frankfurt
1 2.06 2 1.10
Hamburger SV Hamburger SV
58%
May 02
13:30
Union Berlin Union Berlin
2 1.33 2 2.08
1. FC Köln 1. FC Köln
81%
Apr 26
15:30
Borussia Dortmund Borussia Dortmund
4 2.02 0 1.12
SC Freiburg SC Freiburg
43%
Apr 26
13:30
VfB Stuttgart VfB Stuttgart
1 2.26 1 1.06
Werder Bremen Werder Bremen
70%
Apr 25
16:30
Hamburger SV Hamburger SV
1 1.47 2 2.23
1899 Hoffenheim 1899 Hoffenheim
82%
Apr 25
13:30
FSV Mainz 05 FSV Mainz 05
3 1.51 4 2.32
Bayern München Bayern München
42%
Apr 25
13:30
VfL Wolfsburg VfL Wolfsburg
0 1.58 0 1.57
Borussia Mönchengladbach Borussia Mönchengladbach
42%
Apr 25
13:30
1. FC Köln 1. FC Köln
1 1.84 2 1.76
Bayer Leverkusen Bayer Leverkusen
74%
Apr 25
13:30
FC Augsburg FC Augsburg
1 1.86 1 1.53
Eintracht Frankfurt Eintracht Frankfurt
68%
Apr 25
13:30
1. FC Heidenheim 1. FC Heidenheim
2 1.80 0 0.88
FC St. Pauli FC St. Pauli
74%
Apr 24
18:30
RB Leipzig RB Leipzig
3 2.52 1 1.10
Union Berlin Union Berlin
85%

Germany Bundesliga Betting & Prediction Guides

Want to understand how AI identifies value in Germany Bundesliga matches? Explore our strategy guides:

Bundesliga Predictions FAQ

Q1: What defines the probability structure and upset patterns in the Germany Bundesliga during the 2025/26 season? ▼
The Germany Bundesliga 2025/26 presents a distinct hierarchy where home advantage remains a formidable barrier compared to more volatile European divisions. With a 47% home win rate against just 30% for visitors, the 17% gap creates a structural bias that often inflates the price of away underdogs. Unlike leagues where travel fatigue is negligible, German venues maintain a "fortress" identity that anchors the odds distribution toward the hosts.

Upset patterns in this environment are mathematically significant when they occur. While probability never guarantees a specific result, the 30% away win rate suggests that finding value requires looking beyond the league's dominant home bias. Risk management is essential here, as long-term EV depends on identifying when the market overestimates the 47% home win probability in specific tactical matchups.
Q2: How does the Over/Under and BTTS structure in the Germany Bundesliga 2025/26 differ from other top-flight competitions? ▼
The Germany Bundesliga 2025/26 is structurally one of the highest-scoring environments in elite football, boasting a massive 3.22 goals per game. This offensive output pushes the Over 2.5 market to a 64% frequency, significantly higher than the typical 50-52% seen in more conservative top-flight competitions. This high-scoring nature forces bookmakers to set lines higher, often making the "Over" a baseline expectation rather than a speculative choice for analysts.

Similarly, the 59% BTTS rate reflects a league where defensive clean sheets are secondary to transition play. This statistical profile creates a tight relationship between goal volume and both teams scoring. However, probability ≠ certainty, and even in a league averaging 3.22 goals, risk management is essential. Success relies on assessing whether specific defensive setups can defy these league-wide trends to find long-term EV.
Q3: How does the specific data profile of the Germany Bundesliga 2025/26 shape its odds structure and analytical edges? ▼
Because the Germany Bundesliga 2025/26 features a 64% Over 2.5 rate and a 17% home-away win gap, the odds behave with a heavy lean toward high-scoring home victories. This pronounced home bias often pushes away-side odds to levels that don't fully reflect the 30% away win probability. Analytical models find edges by identifying matches where the 59% BTTS trend is likely to fail, as the market typically prices in goals by default.

The extreme 3.22 goals per game average creates a unique odds structure where the standard "Under 2.5" is priced as a significant outlier. Navigating this requires understanding that while the data suggests frequent scoring, long-term EV is found by spotting defensive outliers. Remember, probability ≠ certainty; disciplined risk management is essential when betting against such a dominant offensive statistical fingerprint.
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