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

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 Stuttgart
Last 6 — all competitions · 6/6 matches
Win Ø 42%
33%
50%
Points per game
1,3
1,5
Over 2.5 Ø 75%
67%
83%
Both score Ø 67%
67%
67%
Average goals
2,7
3,8
Scored
1,2
2,0
Conceded
1,5
1,8
Goal diff per game
-0,3
+0,2
This season — 2. Bundesliga · 16/16 matches
Win Ø 41%
25%
56%
Points per game
1,2
1,8
Over 2.5 Ø 57%
44%
69%
Both score Ø 57%
50%
63%
Average goals
2,4
3,0
Scored
1,1
1,7
Conceded
1,4
1,3
Goal diff per game
-0,3
+0,4
🔒 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: 1–1

12 Shots 18
6 Shots on target 8
5 Corners 10
6 Free kicks against 15
1 Yellow cards 5
0 Red cards 0
The table before the match Darmstadt 14. · Stuttgart 3.
# Team K V U T +/− P
1 Bielefeld 17 9 7 1 +17 34
2 Hamburg 17 8 6 3 +17 30
3 Stuttgart 16 9 2 5 +6 29
4 Heidenheim 17 7 6 4 +7 27
5 Osnabruck 17 7 5 5 +8 26
6 Erzgebirge Aue 17 7 5 5 +1 26
7 Greuther Furth 17 7 4 6 +3 25
8 Regensburg 17 6 5 6 +3 23
9 Sandhausen 17 5 8 4 +1 23
10 Holstein Kiel 17 6 4 7 -1 22
11 Bochum 17 4 8 5 -1 20
12 Karlsruhe 17 4 8 5 -6 20
13 Hannover 17 5 5 7 -8 20
14 Darmstadt 16 4 7 5 -5 19
15 St Pauli 17 4 6 7 -2 18
16 Nurnberg 17 3 7 7 -10 16
17 Wehen 17 3 5 9 -15 14
18 Dresden 17 3 4 10 -15 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
4,21
U ✓
3,62
B
1,81
Over/under goals
O1,5 ✓
O2,5
1,69
U2,5 ✓
2,14
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.