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

Heidenheim Bielefeld
Last 6 — all competitions · 6/6 matches
Win Ø 67%
67%
67%
Points per game
2,2
2,3
Over 2.5 Ø 50%
33%
67%
Both score Ø 58%
33%
83%
Average goals
2,2
3,3
Scored
1,5
2,3
Conceded
0,7
1,0
Goal diff per game
+0,8
+1,3
This season — 2. Bundesliga · 16/16 matches
Win Ø 50%
44%
56%
Points per game
1,6
2,1
Over 2.5 Ø 53%
50%
56%
Both score Ø 63%
50%
75%
Average goals
2,6
3,3
Scored
1,5
2,2
Conceded
1,1
1,1
Goal diff per game
+0,4
+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

12 Shots 13
3 Shots on target 3
2 Corners 7
6 Free kicks against 9
0 Yellow cards 2
0 Red cards 0
The table before the match Heidenheim 4. · Bielefeld 1.
# Team K V U T +/− P
1 Bielefeld 16 9 6 1 +17 33
2 Hamburg 16 8 5 3 +17 29
3 Stuttgart 16 9 2 5 +6 29
4 Heidenheim 16 7 5 4 +7 26
5 Erzgebirge Aue 17 7 5 5 +1 26
6 Osnabruck 16 6 5 5 +5 23
7 Regensburg 17 6 5 6 +3 23
8 Sandhausen 16 5 7 4 +1 22
9 Greuther Furth 16 6 4 6 -1 22
10 Holstein Kiel 16 6 3 7 -1 21
11 Bochum 17 4 8 5 -1 20
12 Karlsruhe 16 4 8 4 -2 20
13 Hannover 17 5 5 7 -8 20
14 Darmstadt 16 4 7 5 -5 19
15 St Pauli 16 3 6 7 -4 15
16 Nurnberg 16 3 6 7 -10 15
17 Wehen 16 3 5 8 -13 14
18 Dresden 16 3 4 9 -12 13

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
2,82
U ✓
3,41
B
2,40
Over/under goals
U1,5 ✓
O2,5
1,73
U2,5 ✓
2,09
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.