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2. Bundesliga

Referee: M Bacher

Hertha

U T T S S

1–1

Full-time

Bochum

U U U T S

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

Hertha Bochum

Last 6 — all competitions · 6/6 matches

Win Ø 42%

50%

33%

Points per game

1,7

1,5

Over 2.5 Ø 58%

83%

33%

Both score Ø 67%

67%

Average goals

3,5

2,3

Scored

1,8

1,3

Conceded

1,7

1,0

Goal diff per game

+0,2

+0,3

xG created Pro

xG conceded Pro

xG diff Pro

This season — 2. Bundesliga · 25/25 matches

Win Ø 38%

44%

32%

Points per game

1,6

1,3

Over 2.5 Ø 50%

52%

48%

Both score Ø 52%

44%

60%

Average goals

2,6

2,7

Scored

1,4

Conceded

1,2

1,3

Goal diff per game

+0,2

+0,1

xG created Pro

xG conceded Pro

xG diff Pro

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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: 1–0

1,31 xG 0,55

48% Possession 52%

11 Shots 8

2 Shots on target 2

2 Blocked shots 4

1 Goalkeeper saves 1

5 Corners 6

1 Offside 3

12 Free kicks against 13

2 Yellow cards 3

0 Red cards 0

The table before the match Hertha 6. · Bochum 10. ▾

#	Team	K	V	U	T	+/−	xG +/−	P
1	Schalke 04	25	15	5	5	+14	+11.4	50
2	Darmstadt	26	13	10	3	+19	+7.7	49
3	Elversberg	26	14	6	6	+16	+2.9	48
4	Paderborn	26	14	6	6	+13	+11.7	48
5	Hannover	25	13	6	6	+11	+12.0	45
6	Hertha	25	11	7	7	+6	-4.8	40
7	Kaiserslautern	25	11	4	10	+4	-2.1	37
8	Karlsruhe	25	9	7	9	-7	-15.4	34
9	Nurnberg	26	9	6	11	-3	-2.3	33
10	Bochum	25	8	8	9	+3	+6.3	32
11	Fortuna Dusseldorf	26	9	4	13	-11	-1.9	31
12	Braunschweig	26	8	5	13	-14	-0.4	29
13	Greuther Furth	26	8	5	13	-17	-9.9	29
14	Bielefeld	26	7	7	12	+2	+1.9	28
15	Dresden	25	6	8	11	-6	-1.6	26
16	Preußen Münster	25	6	8	11	-8	-10.0	26
17	Holstein Kiel	26	6	7	13	-9	-12.0	25
18	Magdeburg	26	7	3	16	-13	+6.3	24

#	Team	K	V	U	T	+/−	xG +/−	P
1	Darmstadt	13	10	3	0	+19	+9.9	33
2	Schalke 04	12	9	2	1	+9	+6.2	29
3	Paderborn	13	8	2	3	+7	+9.4	26
4	Kaiserslautern	13	8	1	4	+10	+0.3	25
5	Elversberg	12	7	4	1	+10	+1.8	25
6	Bochum	13	6	4	3	+6	+9.8	22
7	Nurnberg	13	6	4	3	+5	+0.2	22
8	Karlsruhe	12	6	3	3	+2	-5.1	21
9	Hannover	12	6	2	4	+3	+9.5	20
10	Hertha	13	5	4	4	-1	-1.8	19
11	Bielefeld	13	5	3	5	+7	+10.2	18
12	Fortuna Dusseldorf	13	5	3	5	-4	-0.4	18
13	Braunschweig	14	5	3	6	-7	+4.0	18
14	Greuther Furth	13	4	4	5	-7	-5.3	16
15	Holstein Kiel	13	4	3	6	+0	-0.7	15
16	Preußen Münster	13	3	6	4	-1	-3.3	15
17	Dresden	12	3	3	6	-1	+3.7	12
18	Magdeburg	13	2	2	9	-10	+6.2	8

#	Team	K	V	U	T	+/−	xG +/−	P
1	Hannover	13	7	4	2	+8	+2.6	25
2	Elversberg	14	7	2	5	+6	+1.2	23
3	Paderborn	13	6	4	3	+6	+2.3	22
4	Hertha	12	6	3	3	+7	-3.0	21
5	Schalke 04	13	6	3	4	+5	+5.2	21
6	Darmstadt	13	3	7	3	+0	-2.2	16
7	Magdeburg	13	5	1	7	-3	+0.1	16
8	Dresden	13	3	5	5	-5	-5.3	14
9	Fortuna Dusseldorf	13	4	1	8	-7	-1.6	13
10	Karlsruhe	13	3	4	6	-9	-10.3	13
11	Greuther Furth	13	4	1	8	-10	-4.7	13
12	Kaiserslautern	12	3	3	6	-6	-2.4	12
13	Braunschweig	12	3	2	7	-7	-4.4	11
14	Preußen Münster	12	3	2	7	-7	-6.7	11
15	Nurnberg	13	3	2	8	-8	-2.5	11
16	Bochum	12	2	4	6	-3	-3.5	10
17	Bielefeld	13	2	4	7	-5	-8.2	10
18	Holstein Kiel	13	2	4	7	-9	-11.3	10

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.