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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Augsburg
Mainz
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: 2–1
| # | Team | K | V | U | T | +/− | xG +/− | P |
|---|---|---|---|---|---|---|---|---|
| 1 |
Stuttgart
|
5 | 4 | 0 | 1 | +10 | +5.3 | 12 |
| 2 |
Leverkusen
|
4 | 3 | 1 | 0 | +8 | +3.8 | 10 |
| 3 |
Bayern Munich
|
4 | 3 | 1 | 0 | +7 | +6.6 | 10 |
| 4 |
RB Leipzig
|
4 | 3 | 0 | 1 | +9 | +1.2 | 9 |
| 5 |
Hoffenheim
|
4 | 3 | 0 | 1 | +4 | -0.2 | 9 |
| 6 |
Wolfsburg
|
4 | 3 | 0 | 1 | +2 | +1.3 | 9 |
| 7 |
Dortmund
|
4 | 2 | 2 | 0 | +3 | +3.7 | 8 |
| 8 |
Union Berlin
|
4 | 2 | 0 | 2 | +2 | -1.1 | 6 |
| 9 |
Ein Frankfurt
|
4 | 1 | 3 | 0 | +1 | -0.2 | 6 |
| 10 |
Freiburg
|
4 | 2 | 0 | 2 | -5 | +0.5 | 6 |
| 11 |
Heidenheim
|
4 | 1 | 1 | 2 | -1 | -3.4 | 4 |
| 12 |
Werder Bremen
|
4 | 1 | 0 | 3 | -3 | -0.7 | 3 |
| 13 |
Bochum
|
4 | 0 | 3 | 1 | -5 | -2.0 | 3 |
| 14 |
M'gladbach
|
4 | 0 | 2 | 2 | -4 | -1.5 | 2 |
| 15 |
Augsburg
|
4 | 0 | 2 | 2 | -5 | -0.2 | 2 |
| 16 |
FC Koln
|
4 | 0 | 1 | 3 | -4 | -3.0 | 1 |
| 17 |
Mainz
|
4 | 0 | 1 | 3 | -9 | -2.3 | 1 |
| 18 |
Darmstadt
|
5 | 0 | 1 | 4 | -10 | -7.9 | 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.
F. Dahmen
G
P. Pfeiffer
D
J. Gouweleeuw
D
F. Uduokhai
D
K. Mbabu
M
E. Rexhbeçaj
M
A. Engels
M
R. Vargas
F
E. Demirović
F
P. Tietz
F
Coach: E. Maaßen
R. Zentner
G
S. Bell
D
D. Kohr
D
E. Fernandes
D
D. da Costa
M
L. Barreiro
M
T. Krauß
M
A. Caci
M
Lee Jae-Sung
F
L. Ajorque
F
Coach: B. Svensson
Green columns are the outcomes that came in.
RB Leipzig
Augsburg
Augsburg
Bochum
Bayern Munich
Augsburg
Augsburg
M'gladbach
SpVgg Unterhaching
Augsburg
M Fritz · 83 kamper i vår database
🟥 Red cards: 0,08 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.