2. 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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Fortuna Dusseldorf
Kaiserslautern
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: 1–3
| # | Team | K | V | U | T | +/− | P |
|---|---|---|---|---|---|---|---|
| 1 |
St Pauli
|
10 | 5 | 5 | 0 | +12 | 20 |
| 2 |
Hamburg
|
10 | 6 | 2 | 2 | +9 | 20 |
| 3 |
Hannover
|
10 | 5 | 3 | 2 | +10 | 18 |
| 4 |
Kaiserslautern
|
9 | 5 | 2 | 2 | +4 | 17 |
| 5 |
Holstein Kiel
|
9 | 5 | 1 | 3 | +0 | 16 |
| 6 |
Fortuna Dusseldorf
|
9 | 4 | 3 | 2 | +8 | 15 |
| 7 |
Elversberg
|
10 | 4 | 3 | 3 | +0 | 15 |
| 8 |
Paderborn
|
10 | 4 | 3 | 3 | -1 | 15 |
| 9 |
Magdeburg
|
10 | 3 | 4 | 3 | +2 | 13 |
| 10 |
Hertha
|
9 | 4 | 0 | 5 | +2 | 12 |
| 11 |
Wehen
|
10 | 3 | 3 | 4 | -2 | 12 |
| 12 |
Greuther Furth
|
10 | 3 | 3 | 4 | -3 | 12 |
| 13 |
Hansa Rostock
|
9 | 4 | 0 | 5 | -3 | 12 |
| 14 |
Nurnberg
|
9 | 3 | 3 | 3 | -5 | 12 |
| 15 |
Karlsruhe
|
9 | 2 | 3 | 4 | -3 | 9 |
| 16 |
Schalke 04
|
9 | 2 | 1 | 6 | -6 | 7 |
| 17 |
Osnabruck
|
10 | 1 | 3 | 6 | -12 | 6 |
| 18 |
Braunschweig
|
10 | 1 | 2 | 7 | -12 | 5 |
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.
F. Kastenmeier
G
J. Siebert
D
E. Iyoha
D
S. Appelkamp
M
Y. Engelhardt
M
A. Tanaka
M
F. Klaus
F
V. Vermeij
F
C. Tzolis
F
Coach: D. Thioune
J. Krahl
G
J. Elvedi
D
B. Tomiak
D
J. Niehues
M
T. Raschl
M
R. Tachie
F
R. Ache
F
M. Ritter
F
Coach: D. Schuster
Green columns are the outcomes that came in.
Fortuna Dusseldorf
Osnabruck
Hamburg
Fortuna Dusseldorf
Fortuna Dusseldorf
Hannover
Hansa Rostock
Fortuna Dusseldorf
Fortuna Dusseldorf
Karlsruhe
B Brand · 70 kamper i vår database
🟥 Red cards: 0,20 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.