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2. Bundesliga

Referee: S Stegemann

Hannover

S S T S S

0–3

Full-time

Hertha

T U U U 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

Hannover Hertha

Last 6 — all competitions · 6/6 matches

Win Ø 34%

67%

Points per game

2,2

0,7

Over 2.5 Ø 25%

33%

17%

Both score Ø 42%

50%

33%

Average goals

2,2

1,2

Scored

1,5

0,3

Conceded

0,7

0,8

Goal diff per game

+0,8

-0,5

This season — 2. Bundesliga · 4/4 matches

Win Ø 50%

100%

Points per game

3,0

0,5

Over 2.5 Ø 38%

50%

25%

Both score Ø 38%

50%

25%

Average goals

2,5

1,3

Scored

2,0

0,3

Conceded

0,5

1,0

Goal diff per game

+1,5

-0,8

🔒 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

66% Possession 34%

21 Shots 9

3 Shots on target 3

12 Blocked shots 1

0 Goalkeeper saves 2

15 Corners 0

13 Free kicks against 19

2 Yellow cards 5

0 Red cards 0

The table before the match Hannover 1. · Hertha 17. ▾

#	Team	K	V	U	T	+/−	xG +/−	P
1	Hannover	4	4	0	0	+6	+2.5	12
2	Karlsruhe	5	3	2	0	+4	+0.3	11
3	Bielefeld	5	3	1	1	+7	+1.7	10
4	Darmstadt	5	3	1	1	+3	+0.9	10
5	Elversberg	4	3	0	1	+2	-2.9	9
6	Schalke 04	5	3	0	2	+1	+0.8	9
7	Paderborn	5	2	2	1	+1	+2.8	8
8	Preußen Münster	4	2	1	1	+1	-2.5	7
9	Braunschweig	5	2	1	2	-1	-1.1	7
10	Kaiserslautern	4	2	0	2	+1	-0.2	6
11	Greuther Furth	4	2	0	2	-1	-0.2	6
12	Holstein Kiel	5	2	0	3	-1	+0.1	6
13	Fortuna Dusseldorf	4	1	1	2	-5	-3.5	4
14	Dresden	4	1	0	3	-2	+1.8	3
15	Bochum	5	1	0	4	-4	+1.8	3
16	Magdeburg	5	1	0	4	-5	-0.5	3
17	Hertha	4	0	2	2	-3	-1.9	2
18	Nurnberg	5	0	1	4	-4	+0.1	1

#	Team	K	V	U	T	+/−	xG +/−	P
1	Karlsruhe	3	3	0	0	+4	+0.1	9
2	Darmstadt	3	2	1	0	+4	+0.6	7
3	Bielefeld	3	2	0	1	+5	+2.2	6
4	Hannover	2	2	0	0	+3	+1.2	6
5	Kaiserslautern	2	2	0	0	+3	+1.0	6
6	Elversberg	2	2	0	0	+2	-0.4	6
7	Paderborn	3	2	0	1	+1	+0.4	6
8	Schalke 04	3	2	0	1	+1	+1.7	6
9	Braunschweig	2	1	1	0	+1	+0.3	4
10	Preußen Münster	2	1	1	0	+1	-2.4	4
11	Bochum	2	1	0	1	+1	+2.4	3
12	Greuther Furth	2	1	0	1	-1	+0.1	3
13	Nurnberg	2	0	1	1	-1	-0.4	1
14	Hertha	2	0	1	1	-2	-0.2	1
15	Fortuna Dusseldorf	2	0	1	1	-2	-1.3	1
16	Magdeburg	2	0	0	2	-2	+1.3	0
17	Dresden	2	0	0	2	-2	+1.8	0
18	Holstein Kiel	2	0	0	2	-3	+0.5	0

#	Team	K	V	U	T	+/−	xG +/−	P
1	Hannover	2	2	0	0	+3	+1.3	6
2	Holstein Kiel	3	2	0	1	+2	-0.4	6
3	Bielefeld	2	1	1	0	+2	-0.5	4
4	Greuther Furth	2	1	0	1	+0	-0.3	3
5	Dresden	2	1	0	1	+0	-0.1	3
6	Preußen Münster	2	1	0	1	+0	-0.1	3
7	Elversberg	2	1	0	1	+0	-2.4	3
8	Schalke 04	2	1	0	1	+0	-1.0	3
9	Darmstadt	2	1	0	1	-1	+0.4	3
10	Braunschweig	3	1	0	2	-2	-1.3	3
11	Fortuna Dusseldorf	2	1	0	1	-3	-2.2	3
12	Magdeburg	3	1	0	2	-3	-1.8	3
13	Paderborn	2	0	2	0	+0	+2.4	2
14	Karlsruhe	2	0	2	0	+0	+0.2	2
15	Hertha	2	0	1	1	-1	-1.7	1
16	Kaiserslautern	2	0	0	2	-2	-1.2	0
17	Nurnberg	3	0	0	3	-3	+0.4	0
18	Bochum	3	0	0	3	-5	-0.6	0

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.