Bundesliga
Retrospective analysis — the model is trained only on matches played before this one.
The model's probabilities for a home win, draw and away win — with reasoning and recommended markets.
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Bielefeld
FC Koln
Expected goals, over/under and both teams to score — priced by the model before kick-off.
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The model's top final scores with the best bookmaker odds.
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Half-time score: 0–1
| # | Team | K | V | U | T | +/− | P |
|---|---|---|---|---|---|---|---|
| 1 |
Bayern Munich
|
13 | 10 | 1 | 2 | +29 | 31 |
| 2 |
Dortmund
|
13 | 10 | 0 | 3 | +14 | 30 |
| 3 |
Leverkusen
|
13 | 7 | 3 | 3 | +10 | 24 |
| 4 |
Union Berlin
|
14 | 6 | 5 | 3 | +2 | 23 |
| 5 |
Freiburg
|
13 | 6 | 4 | 3 | +6 | 22 |
| 6 |
Hoffenheim
|
13 | 6 | 2 | 5 | +7 | 20 |
| 7 |
Wolfsburg
|
13 | 6 | 2 | 5 | -2 | 20 |
| 8 |
RB Leipzig
|
14 | 5 | 3 | 6 | +7 | 18 |
| 9 |
Mainz
|
13 | 5 | 3 | 5 | +3 | 18 |
| 10 |
FC Koln
|
13 | 4 | 6 | 3 | +0 | 18 |
| 11 |
M'gladbach
|
13 | 5 | 3 | 5 | +0 | 18 |
| 12 |
Ein Frankfurt
|
13 | 4 | 6 | 3 | -1 | 18 |
| 13 |
Bochum
|
13 | 5 | 1 | 7 | -8 | 16 |
| 14 |
Hertha
|
13 | 4 | 2 | 7 | -14 | 14 |
| 15 |
Stuttgart
|
13 | 3 | 4 | 6 | -5 | 13 |
| 16 |
Augsburg
|
13 | 3 | 4 | 6 | -10 | 13 |
| 17 |
Bielefeld
|
13 | 1 | 6 | 6 | -10 | 9 |
| 18 |
Greuther Furth
|
13 | 0 | 1 | 12 | -28 | 1 |
Calculated from our results data. “xG +/−” is expected goal difference — a positive number with a low league position suggests an undervalued team. Ties on points are sorted by goal difference; some leagues use other rules.
S. Ortega Moreno
G
A. Pieper
D
A. Schöpf
M
F. Kunze
M
P. Wimmer
M
Coach: F. Kramer
M. Schwäbe
G
E. Skhiri
M
S. Özcan
M
D. Ljubičić
M
Coach: S. Baumgart
Green columns are the outcomes that came in.
Bayern Munich
Bielefeld
Bielefeld
Wolfsburg
Stuttgart
Bielefeld
Bielefeld
Mainz
Bielefeld
Dortmund
F Brych · 113 kamper i vår database
🟥 Red cards: 0,10 per match
The analysis is a statistical estimate based on the teams' results and underlying performances (xG) — not a guarantee. See the model's results.