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2. Bundesliga
Darmstadt
S S T U S
1–3
Full-time
Bielefeld
U S S 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

Darmstadt Bielefeld
Last 6 — all competitions · 6/6 matches
Win Ø 59%
50%
67%
Points per game
1,8
2,3
Over 2.5 Ø 42%
50%
33%
Both score Ø 67%
67%
67%
Average goals
2,5
2,5
Scored
1,3
1,8
Conceded
1,2
0,7
Goal diff per game
+0,2
+1,2
This season — 2. Bundesliga · 14/14 matches
Win Ø 43%
29%
57%
Points per game
1,3
2,1
Over 2.5 Ø 47%
43%
50%
Both score Ø 61%
50%
71%
Average goals
2,5
3,2
Scored
1,1
2,1
Conceded
1,4
1,1
Goal diff per game
-0,2
+1,1
🔒 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

18 Shots 11
9 Shots on target 5
4 Corners 7
5 Free kicks against 11
0 Yellow cards 2
0 Red cards 0
The table before the match Darmstadt 12. · Bielefeld 2.
# Team K V U T +/− P
1 Hamburg 15 8 5 2 +18 29
2 Bielefeld 14 8 5 1 +15 29
3 Stuttgart 14 8 2 4 +5 26
4 Erzgebirge Aue 15 6 5 4 +1 23
5 Holstein Kiel 15 6 3 6 +1 21
6 Heidenheim 14 5 5 4 +5 20
7 Regensburg 15 5 5 5 +3 20
8 Osnabruck 15 5 5 5 +3 20
9 Karlsruhe 15 4 7 4 -2 19
10 Greuther Furth 14 5 4 5 -2 19
11 Sandhausen 14 4 6 4 +0 18
12 Darmstadt 14 4 6 4 -3 18
13 Bochum 15 3 8 4 +0 17
14 Hannover 15 4 5 6 -8 17
15 St Pauli 15 3 6 6 -3 15
16 Nurnberg 15 3 6 6 -8 15
17 Wehen 15 3 4 8 -13 13
18 Dresden 15 3 3 9 -12 12

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
3,41
U
3,52
B ✓
2,05
Over/under goals
O1,5 ✓
O2,5 ✓
1,74
U2,5
2,08
O3,5 ✓
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.