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2. Bundesliga
0–0
Full-time
Bielefeld
S U U T S

Retrospective analysis — the model is trained only on matches played before this one.

🔒 Who wins? Pro

The model's probabilities for a home win, draw and away win — with reasoning and recommended markets.

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Team trends

Erzgebirge Aue Bielefeld
Last 6 — all competitions · 6/6 matches
Win Ø 42%
50%
33%
Points per game
1,5
1,5
Over 2.5 Ø 50%
50%
50%
Both score Ø 50%
50%
50%
Average goals
2,8
2,5
Scored
1,5
1,3
Conceded
1,3
1,2
Goal diff per game
+0,2
+0,2
This season — 2. Bundesliga · 19/19 matches
Win Ø 48%
42%
53%
Points per game
1,5
1,9
Over 2.5 Ø 50%
47%
53%
Both score Ø 61%
58%
63%
Average goals
2,9
3,1
Scored
1,5
1,9
Conceded
1,4
1,1
Goal diff per game
+0,1
+0,8
🔒 Goal markets Pro

Expected goals, over/under and both teams to score — priced by the model before kick-off.

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🔒 Most likely result Pro

The model's top final scores with the best bookmaker odds.

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Match stats

Half-time score: 0–0

8 Shots 9
4 Shots on target 3
2 Corners 9
11 Free kicks against 10
3 Yellow cards 2
0 Red cards 0
The table before the match Erzgebirge Aue 6. · Bielefeld 1.
# Team K V U T +/− P
1 Bielefeld 19 10 7 2 +16 37
2 Hamburg 19 9 7 3 +20 34
3 Stuttgart 19 10 4 5 +9 34
4 Heidenheim 19 8 6 5 +6 30
5 Regensburg 19 8 5 6 +5 29
6 Erzgebirge Aue 19 8 5 6 +2 29
7 Greuther Furth 19 8 4 7 +4 28
8 Sandhausen 19 6 9 4 +3 27
9 Osnabruck 19 7 5 7 +4 26
10 Holstein Kiel 19 6 6 7 -1 24
11 Darmstadt 19 4 10 5 -5 22
12 St Pauli 19 5 6 8 -2 21
13 Hannover 19 5 6 8 -9 21
14 Bochum 19 4 8 7 -4 20
15 Karlsruhe 19 4 8 7 -8 20
16 Wehen 19 5 5 9 -13 20
17 Nurnberg 19 4 7 8 -11 19
18 Dresden 19 4 4 11 -16 16

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.

Odds comparison

Green columns are the outcomes that came in.

1X2
H
3,70
U ✓
3,43
B
1,99
Over/under goals
U1,5 ✓
O2,5
1,93
U2,5 ✓
1,86
U3,5 ✓
Both teams to score
BLS ja
BLS nei ✓

The analysis is a statistical estimate based on the teams' results and underlying performances (xG) — not a guarantee. See the model's results.