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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FC Koln
Hertha
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: 0–0
| # | Team | K | V | U | T | +/− | P |
|---|---|---|---|---|---|---|---|
| 1 |
Hamburg
|
28 | 14 | 10 | 4 | +29 | 52 |
| 2 |
FC Koln
|
27 | 15 | 5 | 7 | +10 | 50 |
| 3 |
Kaiserslautern
|
27 | 13 | 7 | 7 | +8 | 46 |
| 4 |
Paderborn
|
28 | 12 | 9 | 7 | +10 | 45 |
| 5 |
Fortuna Dusseldorf
|
28 | 12 | 8 | 8 | +4 | 44 |
| 6 |
Magdeburg
|
27 | 11 | 10 | 6 | +12 | 43 |
| 7 |
Hannover
|
28 | 11 | 10 | 7 | +7 | 43 |
| 8 |
Elversberg
|
27 | 11 | 8 | 8 | +13 | 41 |
| 9 |
Nurnberg
|
28 | 12 | 5 | 11 | +3 | 41 |
| 10 |
Karlsruhe
|
28 | 11 | 7 | 10 | -3 | 40 |
| 11 |
Darmstadt
|
28 | 9 | 7 | 12 | +2 | 34 |
| 12 |
Schalke 04
|
27 | 9 | 7 | 11 | -3 | 34 |
| 13 |
Greuther Furth
|
28 | 9 | 7 | 12 | -12 | 34 |
| 14 |
Hertha
|
27 | 9 | 5 | 13 | -3 | 32 |
| 15 |
Preußen Münster
|
28 | 6 | 9 | 13 | -8 | 27 |
| 16 |
Braunschweig
|
28 | 6 | 9 | 13 | -24 | 27 |
| 17 |
Ulm
|
27 | 4 | 11 | 12 | -6 | 23 |
| 18 |
Regensburg
|
27 | 5 | 4 | 18 | -39 | 19 |
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.
M. Schwäbe
G
J. Thielmann
D
J. Schmied
D
L. Paqarada
D
M. Olesen
M
E. Martel
M
D. Huseinbašić
M
L. Waldschmidt
F
I. Rondić
F
T. Lemperle
F
Coach: G. Struber
T. Ernst
G
L. Gechter
D
D. Zeefuik
D
J. Kenny
M
M. Cuisance
M
I. Maza
M
M. Winkler
M
F. Reese
F
D. Scherhant
F
Coach: S. Leitl
Green columns are the outcomes that came in.
Paderborn
FC Koln
FC Koln
Darmstadt
Ulm
FC Koln
Karlsruhe
FC Koln
FC Koln
Fortuna Dusseldorf
S Jablonski · 136 kamper i vår database
🟥 Red cards: 0,13 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.