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2. Bundesliga
Germany · 36 matches in the next 30 days
Average goals
3,02
Over 1.5
75 %
Over 2.5
56 %
BLS
56 %
Match outcome H / D / A
46
30
25
Season progress
26 %
81 of 306 matches played · season 2026/27
| Match | 1X2 odds | Model % | xGoals | PPG L10 |
Goal diff L10 |
Goals/game L10 |
xG L10 |
xG-diff L10 |
Value |
|---|---|---|---|---|---|---|---|---|---|
|
Saturday 7. November
9
|
|||||||||
|
7. Nov
13:30
Hertha
Wolfsburg
|
2,07 / 3,92 / 3,08 | 🔒 | 🔒 | 2,6 1,7 |
+12 +9 |
3,0 4,3 |
🔒 | 🔒 | 🔒 |
|
7. Nov
13:30
Nurnberg
Darmstadt
|
1,73 / 4,10 / 4,00 | 🔒 | 🔒 | 1,9 1,1 |
+9 -9 |
3,5 2,9 |
🔒 | 🔒 | 🔒 |
|
7. Nov
13:30
Bochum
Karlsruhe
|
1,81 / 3,90 / 3,90 | 🔒 | 🔒 | 1,1 1,1 |
-3 -8 |
1,9 3,4 |
🔒 | 🔒 | 🔒 |
|
7. Nov
13:30
Magdeburg
St Pauli
|
2,32 / 3,60 / 2,75 | 🔒 | 🔒 | 1,9 1,2 |
+12 +0 |
3,6 2,2 |
🔒 | 🔒 | 🔒 |
|
7. Nov
13:30
Heidenheim
Hannover
|
2,05 / 3,80 / 3,15 | 🔒 | 🔒 | 1,5 1,1 |
-3 +1 |
3,9 3,3 |
🔒 | 🔒 | 🔒 |
|
7. Nov
13:30
Dresden
Greuther Furth
|
1,87 / 3,80 / 3,65 | 🔒 | 🔒 | 1,1 0,9 |
-1 -5 |
3,5 3,1 |
🔒 | 🔒 | 🔒 |
|
7. Nov
13:30
Holstein Kiel
Bielefeld
|
2,42 / 3,40 / 2,75 | 🔒 | 🔒 | 1,1 1,2 |
+1 -1 |
2,3 3,1 |
🔒 | 🔒 | 🔒 |
|
7. Nov
13:30
Braunschweig
Cottbus
|
1,86 / 4,00 / 3,54 | 🔒 | 🔒 | 1,0 1,0 |
-2 -3 |
3,6 3,7 |
🔒 | 🔒 | 🔒 |
|
7. Nov
13:30
Osnabruck
Kaiserslautern
|
2,60 / 3,60 / 2,45 | 🔒 | 🔒 | 1,1 2,1 |
-4 +6 |
3,4 1,4 |
🔒 | 🔒 | 🔒 |
|
Saturday 21. November
9
|
|||||||||
|
21. Nov
13:30
Wolfsburg
Holstein Kiel
|
– | – | – | 1,7 1,1 |
+9 +1 |
4,3 2,3 |
🔒 | 🔒 | – |
|
21. Nov
13:30
Hannover
Greuther Furth
|
– | – | – | 1,1 0,9 |
+1 -5 |
3,3 3,1 |
🔒 | 🔒 | – |
|
21. Nov
13:30
Nurnberg
Braunschweig
|
– | – | – | 1,9 1,0 |
+9 -2 |
3,5 3,6 |
🔒 | 🔒 | – |
|
21. Nov
13:30
Darmstadt
Heidenheim
|
– | – | – | 1,1 1,5 |
-9 -3 |
2,9 3,9 |
🔒 | 🔒 | – |
|
21. Nov
13:30
St Pauli
Bochum
|
– | – | – | 1,2 1,1 |
+0 -3 |
2,2 1,9 |
🔒 | 🔒 | – |
|
21. Nov
13:30
Bielefeld
Magdeburg
|
– | – | – | 1,2 1,9 |
-1 +12 |
3,1 3,6 |
🔒 | 🔒 | – |
|
21. Nov
13:30
Kaiserslautern
Dresden
|
– | – | – | 2,1 1,1 |
+6 -1 |
1,4 3,5 |
🔒 | 🔒 | – |
|
21. Nov
13:30
Karlsruhe
Osnabruck
|
– | – | – | 1,1 1,1 |
-8 -4 |
3,4 3,4 |
🔒 | 🔒 | – |
|
21. Nov
13:30
Cottbus
Hertha
|
– | – | – | 1,0 2,6 |
-3 +12 |
3,7 3,0 |
🔒 | 🔒 | – |
|
Saturday 28. November
9
|
|||||||||
|
28. Nov
13:30
Hertha
Karlsruhe
|
– | – | – | 2,6 1,1 |
+12 -8 |
3,0 3,4 |
🔒 | 🔒 | – |
|
28. Nov
13:30
Bochum
Darmstadt
|
– | – | – | 1,1 1,1 |
-3 -9 |
1,9 2,9 |
🔒 | 🔒 | – |
|
28. Nov
13:30
Greuther Furth
Bielefeld
|
– | – | – | 0,9 1,2 |
-5 -1 |
3,1 3,1 |
🔒 | 🔒 | – |
|
28. Nov
13:30
Magdeburg
Cottbus
|
– | – | – | 1,9 1,0 |
+12 -3 |
3,6 3,7 |
🔒 | 🔒 | – |
|
28. Nov
13:30
Heidenheim
Nurnberg
|
– | – | – | 1,5 1,9 |
-3 +9 |
3,9 3,5 |
🔒 | 🔒 | – |
|
28. Nov
13:30
Dresden
St Pauli
|
– | – | – | 1,1 1,2 |
-1 +0 |
3,5 2,2 |
🔒 | 🔒 | – |
|
28. Nov
13:30
Holstein Kiel
Kaiserslautern
|
– | – | – | 1,1 2,1 |
+1 +6 |
2,3 1,4 |
🔒 | 🔒 | – |
|
28. Nov
13:30
Braunschweig
Wolfsburg
|
– | – | – | 1,0 1,7 |
-2 +9 |
3,6 4,3 |
🔒 | 🔒 | – |
|
28. Nov
13:30
Osnabruck
Hannover
|
– | – | – | 1,1 1,1 |
-4 +1 |
3,4 3,3 |
🔒 | 🔒 | – |
|
Saturday 5. December
9
|
|||||||||
|
5. Dec
13:30
Wolfsburg
Magdeburg
|
– | – | – | 1,7 1,9 |
+9 +12 |
4,3 3,6 |
🔒 | 🔒 | – |
|
5. Dec
13:30
Hannover
Hertha
|
– | – | – | 1,1 2,6 |
+1 +12 |
3,3 3,0 |
🔒 | 🔒 | – |
|
5. Dec
13:30
Nurnberg
Bochum
|
– | – | – | 1,9 1,1 |
+9 -3 |
3,5 1,9 |
🔒 | 🔒 | – |
|
5. Dec
13:30
Darmstadt
Braunschweig
|
– | – | – | 1,1 1,0 |
-9 -2 |
2,9 3,6 |
🔒 | 🔒 | – |
|
5. Dec
13:30
St Pauli
Heidenheim
|
– | – | – | 1,2 1,5 |
+0 -3 |
2,2 3,9 |
🔒 | 🔒 | – |
|
5. Dec
13:30
Bielefeld
Dresden
|
– | – | – | 1,2 1,1 |
-1 -1 |
3,1 3,5 |
🔒 | 🔒 | – |
|
5. Dec
13:30
Kaiserslautern
Greuther Furth
|
– | – | – | 2,1 0,9 |
+6 -5 |
1,4 3,1 |
🔒 | 🔒 | – |
|
5. Dec
13:30
Karlsruhe
Holstein Kiel
|
– | – | – | 1,1 1,1 |
-8 +1 |
3,4 2,3 |
🔒 | 🔒 | – |
|
5. Dec
13:30
Cottbus
Osnabruck
|
– | – | – | 1,0 1,1 |
-3 -4 |
3,7 3,4 |
🔒 | 🔒 | – |
General
Stats window
Number of recent matches behind the PPG, goal diff, goals/game and xG columns.
Model filters Pro
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Favourite chance (model)
0%
Min. expected goals
0
Max expected goals
6
Min. both teams to score
0%
Min. value edge
0%
All numbers are statistical estimates from our model. The Value column shows the model's largest deviation from the odds — history shows the market is usually right when the gap is large. Click a row for the full match analysis.