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2. Bundesliga
Osnabruck
T S T S T
0–1
Full-time
Paderborn
S T T T 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

Osnabruck Paderborn
Last 6 — all competitions · 6/6 matches
Win Ø 42%
50%
33%
Points per game
1,5
1,2
Over 2.5 Ø 59%
67%
50%
Both score Ø 34%
50%
17%
Average goals
3,3
2,7
Scored
1,5
1,3
Conceded
1,8
1,3
Goal diff per game
-0,3
+0,0
This season — 2. Bundesliga · 12/12 matches
Win Ø 38%
42%
33%
Points per game
1,6
1,3
Over 2.5 Ø 46%
50%
42%
Both score Ø 50%
67%
33%
Average goals
2,7
2,6
Scored
1,3
1,3
Conceded
1,3
1,3
Goal diff per game
+0,0
+0,1
🔒 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

10 Shots 19
3 Shots on target 7
1 Corners 9
14 Free kicks against 14
1 Yellow cards 5
1 Red cards 1
The table before the match Osnabruck 8. · Paderborn 13.
# Team K V U T +/− P
1 Holstein Kiel 12 7 4 1 +9 25
2 Bochum 13 7 2 4 +10 23
3 Hamburg 12 7 2 3 +9 23
4 Greuther Furth 12 6 3 3 +7 21
5 Fortuna Dusseldorf 12 6 2 4 -2 20
6 Erzgebirge Aue 12 5 4 3 +6 19
7 Heidenheim 13 5 4 4 +1 19
8 Osnabruck 12 5 4 3 +0 19
9 Hannover 13 5 2 6 +1 17
10 Regensburg 13 4 5 4 +0 17
11 Nurnberg 12 4 4 4 +3 16
12 Karlsruhe 12 5 1 6 +1 16
13 Paderborn 12 4 3 5 +1 15
14 Darmstadt 12 4 3 5 +0 15
15 Braunschweig 12 3 3 6 -13 12
16 Sandhausen 12 3 2 7 -13 11
17 St Pauli 11 1 5 5 -6 8
18 Wurzburger Kickers 11 1 1 9 -14 4

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
2,74
U
3,27
B ✓
2,54
Over/under goals
U1,5 ✓
O2,5
1,81
U2,5 ✓
1,98
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.