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Bundesliga
Germany · 34 matches in the next 30 days
Average goals
3,81
Over 1.5
86 %
Over 2.5
78 %
BLS
58 %
Match outcome H / D / A
53
19
28
Season progress
12 %
36 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 |
|---|---|---|---|---|---|---|---|---|---|
|
Friday 9. October
1
|
|||||||||
|
9. Oct
20:30
Dortmund
Werder Bremen
|
– | – | – | 2,7 1,4 |
+19 +0 |
3,3 3,2 |
🔒 | 🔒 | – |
|
Saturday 10. October
6
|
|||||||||
|
10. Oct
15:30
Mainz
Leverkusen
|
– | – | – | 1,7 2,0 |
+13 +13 |
4,3 3,5 |
🔒 | 🔒 | – |
|
10. Oct
15:30
Hoffenheim
Hamburg
|
– | – | – | 1,3 1,3 |
-3 -9 |
3,7 3,5 |
🔒 | 🔒 | – |
|
10. Oct
15:30
Augsburg
Bayern Munich
|
– | – | – | 2,0 2,6 |
+8 +28 |
3,6 3,8 |
🔒 | 🔒 | – |
|
10. Oct
15:30
Union Berlin
Elversberg
|
– | – | – | 1,1 2,0 |
-8 +11 |
4,6 4,1 |
🔒 | 🔒 | – |
|
10. Oct
15:30
Paderborn
Stuttgart
|
– | – | – | 1,5 1,4 |
-1 +2 |
2,9 4,0 |
🔒 | 🔒 | – |
|
10. Oct
18:30
RB Leipzig
Ein Frankfurt
|
– | – | – | 1,5 1,0 |
+4 +6 |
4,2 4,8 |
🔒 | 🔒 | – |
|
Sunday 11. October
2
|
|||||||||
|
11. Oct
15:30
FC Koln
M'gladbach
|
– | – | – | 0,9 1,1 |
-9 -2 |
3,7 3,8 |
🔒 | 🔒 | – |
|
11. Oct
17:30
Freiburg
Schalke 04
|
– | – | – | 2,2 2,0 |
+17 +5 |
4,3 2,9 |
🔒 | 🔒 | – |
|
Friday 16. October
1
|
|||||||||
|
16. Oct
20:30
Ein Frankfurt
FC Koln
|
– | – | – | 1,0 0,9 |
+6 -9 |
4,8 3,7 |
🔒 | 🔒 | – |
|
Saturday 17. October
6
|
|||||||||
|
17. Oct
15:30
Werder Bremen
Paderborn
|
– | – | – | 1,4 1,5 |
+0 -1 |
3,2 2,9 |
🔒 | 🔒 | – |
|
17. Oct
15:30
Schalke 04
Mainz
|
– | – | – | 2,0 1,7 |
+5 +13 |
2,9 4,3 |
🔒 | 🔒 | – |
|
17. Oct
15:30
Hamburg
Stuttgart
|
– | – | – | 1,3 1,4 |
-9 +2 |
3,5 4,0 |
🔒 | 🔒 | – |
|
17. Oct
15:30
Union Berlin
Dortmund
|
– | – | – | 1,1 2,7 |
-8 +19 |
4,6 3,3 |
🔒 | 🔒 | – |
|
17. Oct
15:30
Elversberg
Augsburg
|
– | – | – | 2,0 2,0 |
+11 +8 |
4,1 3,6 |
🔒 | 🔒 | – |
|
17. Oct
18:30
Bayern Munich
RB Leipzig
|
– | – | – | 2,6 1,5 |
+28 +4 |
3,8 4,2 |
🔒 | 🔒 | – |
|
Sunday 18. October
2
|
|||||||||
|
18. Oct
15:30
Leverkusen
Freiburg
|
– | – | – | 2,0 2,2 |
+13 +17 |
3,5 4,3 |
🔒 | 🔒 | – |
|
18. Oct
17:30
M'gladbach
Hoffenheim
|
– | – | – | 1,1 1,3 |
-2 -3 |
3,8 3,7 |
🔒 | 🔒 | – |
|
Friday 23. October
1
|
|||||||||
|
23. Oct
20:30
Stuttgart
M'gladbach
|
– | – | – | 1,4 1,1 |
+2 -2 |
4,0 3,8 |
🔒 | 🔒 | – |
|
Saturday 24. October
6
|
|||||||||
|
24. Oct
15:30
Mainz
Werder Bremen
|
– | – | – | 1,7 1,4 |
+13 +0 |
4,3 3,2 |
🔒 | 🔒 | – |
|
24. Oct
15:30
Augsburg
Union Berlin
|
– | – | – | 2,0 1,1 |
+8 -8 |
3,6 4,6 |
🔒 | 🔒 | – |
|
24. Oct
15:30
RB Leipzig
Elversberg
|
– | – | – | 1,5 2,0 |
+4 +11 |
4,2 4,1 |
🔒 | 🔒 | – |
|
24. Oct
15:30
Paderborn
Hamburg
|
– | – | – | 1,5 1,3 |
-1 -9 |
2,9 3,5 |
🔒 | 🔒 | – |
|
24. Oct
15:30
FC Koln
Schalke 04
|
– | – | – | 0,9 2,0 |
-9 +5 |
3,7 2,9 |
🔒 | 🔒 | – |
|
24. Oct
18:30
Dortmund
Ein Frankfurt
|
– | – | – | 2,7 1,0 |
+19 +6 |
3,3 4,8 |
🔒 | 🔒 | – |
|
Sunday 25. October
2
|
|||||||||
|
25. Oct
15:30
Hoffenheim
Leverkusen
|
– | – | – | 1,3 2,0 |
-3 +13 |
3,7 3,5 |
🔒 | 🔒 | – |
|
25. Oct
17:30
Freiburg
Bayern Munich
|
– | – | – | 2,2 2,6 |
+17 +28 |
4,3 3,8 |
🔒 | 🔒 | – |
|
Friday 30. October
1
|
|||||||||
|
30. Oct
20:30
Elversberg
Mainz
|
– | – | – | 2,0 1,7 |
+11 +13 |
4,1 4,3 |
🔒 | 🔒 | – |
|
Saturday 31. October
6
|
|||||||||
|
31. Oct
15:30
Werder Bremen
Hoffenheim
|
– | – | – | 1,4 1,3 |
+0 -3 |
3,2 3,7 |
🔒 | 🔒 | – |
|
31. Oct
15:30
Leverkusen
Stuttgart
|
– | – | – | 2,0 1,4 |
+13 +2 |
3,5 4,0 |
🔒 | 🔒 | – |
|
31. Oct
15:30
Augsburg
Freiburg
|
– | – | – | 2,0 2,2 |
+8 +17 |
3,6 4,3 |
🔒 | 🔒 | – |
|
31. Oct
15:30
Schalke 04
RB Leipzig
|
– | – | – | 2,0 1,5 |
+5 +4 |
2,9 4,2 |
🔒 | 🔒 | – |
|
31. Oct
15:30
M'gladbach
Paderborn
|
– | – | – | 1,1 1,5 |
-2 -1 |
3,8 2,9 |
🔒 | 🔒 | – |
|
31. Oct
18:30
Bayern Munich
Dortmund
|
– | – | – | 2,6 2,7 |
+28 +19 |
3,8 3,3 |
🔒 | 🔒 | – |
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.