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2. Bundesliga
Dresden
U S T T T
0–1
Full-time
Bielefeld
S S T S U

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

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

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Team trends

Dresden Bielefeld
Last 6 — all competitions · 6/6 matches
Win Ø 34%
17%
50%
Points per game
0,8
1,8
Over 2.5 Ø 50%
67%
33%
Both score Ø 59%
67%
50%
Average goals
3,7
2,8
Scored
1,3
1,8
Conceded
2,3
1,0
Goal diff per game
-1,0
+0,8
This season — 2. Bundesliga · 10/10 matches
Win Ø 35%
20%
50%
Points per game
0,9
1,9
Over 2.5 Ø 55%
60%
50%
Both score Ø 65%
60%
70%
Average goals
3,2
3,3
Scored
1,2
2,1
Conceded
2,0
1,2
Goal diff per game
-0,8
+0,9
🔒 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

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

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
3,31
U
3,54
B ✓
2,09
Over/under goals
U1,5 ✓
O2,5
1,65
U2,5 ✓
2,22
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.