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2. Bundesliga
1–1
Full-time
Holstein Kiel
S U S S T

Retrospective analysis — the model is trained only on matches played before this one.

🔒 Who wins? Pro

The model's probabilities for a home win, draw and away win — with reasoning and recommended markets.

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Team trends

Erzgebirge Aue Holstein Kiel
Last 6 — all competitions · 6/6 matches
Win Ø 50%
50%
50%
Points per game
1,7
1,8
Over 2.5 Ø 50%
67%
33%
Both score Ø 50%
50%
50%
Average goals
2,7
2,0
Scored
1,3
1,2
Conceded
1,3
0,8
Goal diff per game
+0,0
+0,3
This season — 2. Bundesliga · 5/5 matches
Win Ø 50%
40%
60%
Points per game
1,4
2,0
Over 2.5 Ø 50%
60%
40%
Both score Ø 40%
40%
40%
Average goals
2,6
2,0
Scored
1,2
1,2
Conceded
1,4
0,8
Goal diff per game
-0,2
+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

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

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
3,14
U ✓
3,41
B
2,22
Over/under goals
O1,5 ✓
O2,5
1,78
U2,5 ✓
2,02
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.