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2. Bundesliga
3–1
Full-time
Regensburg
S U S T 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

Greuther Furth Regensburg
Last 6 — all competitions · 6/6 matches
Win Ø 42%
50%
33%
Points per game
1,8
1,3
Over 2.5 Ø 59%
50%
67%
Both score Ø 59%
67%
50%
Average goals
3,0
3,0
Scored
2,0
1,5
Conceded
1,0
1,5
Goal diff per game
+1,0
+0,0
This season — 2. Bundesliga · 7/7 matches
Win Ø 36%
43%
29%
Points per game
1,7
1,3
Over 2.5 Ø 50%
43%
57%
Both score Ø 64%
71%
57%
Average goals
2,9
2,9
Scored
1,9
1,4
Conceded
1,0
1,4
Goal diff per game
+0,9
+0,0
🔒 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: 1–1

20 Shots 21
10 Shots on target 4
5 Corners 7
12 Free kicks against 18
1 Yellow cards 3
0 Red cards 0
The table before the match Greuther Furth 5. · Regensburg 11.
# Team K V U T +/− P
1 Hamburg 7 5 2 0 +8 17
2 Paderborn 8 4 2 2 +7 14
3 Osnabruck 7 3 4 0 +4 13
4 Holstein Kiel 8 3 4 1 +2 13
5 Greuther Furth 7 3 3 1 +6 12
6 Bochum 7 3 2 2 +1 11
7 Fortuna Dusseldorf 8 3 2 3 -2 11
8 Karlsruhe 8 3 1 4 +3 10
9 Hannover 7 3 1 3 +3 10
10 Heidenheim 8 2 3 3 +1 9
11 Regensburg 7 2 3 2 +0 9
12 Erzgebirge Aue 7 2 3 2 -1 9
13 Darmstadt 7 2 3 2 -3 9
14 Sandhausen 8 2 2 4 -4 8
15 Braunschweig 8 2 2 4 -8 8
16 Nurnberg 7 1 4 2 -1 7
17 St Pauli 8 1 4 3 -4 7
18 Wurzburger Kickers 7 0 1 6 -12 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 ✓
1,91
U
3,69
B
3,72
Over/under goals
O1,5 ✓
O2,5 ✓
1,68
U2,5
2,15
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.