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2. Bundesliga
Stuttgart
T T T S T
3–0
Full-time
Karlsruhe
U U U U 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

Stuttgart Karlsruhe
Last 6 — all competitions · 6/6 matches
Win Ø 17%
33%
0%
Points per game
1,0
1,0
Over 2.5 Ø 50%
50%
50%
Both score Ø 75%
50%
100%
Average goals
3,0
3,7
Scored
1,2
1,8
Conceded
1,8
1,8
Goal diff per game
-0,7
+0,0
This season — 2. Bundesliga · 13/13 matches
Win Ø 39%
54%
23%
Points per game
1,8
1,2
Over 2.5 Ø 62%
62%
62%
Both score Ø 74%
62%
85%
Average goals
2,9
3,5
Scored
1,5
1,7
Conceded
1,4
1,8
Goal diff per game
+0,2
-0,2
🔒 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

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

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 ✓
1,54
U
4,27
B
5,49
Over/under goals
O1,5 ✓
O2,5 ✓
1,50
U2,5
2,53
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.