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2. Bundesliga
Ingolstadt
U T T T T
3–2
Full-time

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

Ingolstadt Erzgebirge Aue
Last 6 — all competitions · 6/6 matches
Win Ø 9%
0%
17%
Points per game
0,3
0,7
Over 2.5 Ø 59%
50%
67%
Both score Ø 42%
33%
50%
Average goals
2,2
3,5
Scored
0,3
1,2
Conceded
1,8
2,3
Goal diff per game
-1,5
-1,2
This season — 2. Bundesliga · 27/26 matches
Win Ø 13%
11%
15%
Points per game
0,6
0,7
Over 2.5 Ø 61%
63%
58%
Both score Ø 49%
44%
54%
Average goals
2,7
2,9
Scored
0,8
0,9
Conceded
1,9
2,0
Goal diff per game
-1,1
-1,0
🔒 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: 2–0

10 Shots 5
5 Shots on target 2
8 Corners 2
15 Free kicks against 18
1 Yellow cards 2
0 Red cards 1
The table before the match Ingolstadt 18. · Erzgebirge Aue 17.
# Team K V U T +/− P
1 St Pauli 27 15 6 6 +16 51
2 Werder Bremen 27 15 6 6 +15 51
3 Darmstadt 27 14 6 7 +19 48
4 Schalke 04 27 14 5 8 +21 47
5 Nurnberg 27 13 7 7 +6 46
6 Hamburg 26 10 12 4 +19 42
7 Heidenheim 27 12 6 9 -1 42
8 Paderborn 27 9 10 8 +8 37
9 Karlsruhe 27 9 10 8 +6 37
10 Regensburg 27 10 6 11 +5 36
11 Hansa Rostock 27 9 7 11 -8 34
12 Holstein Kiel 27 9 7 11 -9 34
13 Fortuna Dusseldorf 27 8 8 11 -1 32
14 Hannover 27 8 7 12 -15 31
15 Sandhausen 27 7 9 11 -14 30
16 Dresden 27 7 7 13 -10 28
17 Erzgebirge Aue 26 4 7 15 -27 19
18 Ingolstadt 27 3 6 18 -30 15

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 ✓
2,28
U
3,43
B
3,08
Over/under goals
O1,5 ✓
O2,5 ✓
1,86
U2,5
1,94
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.