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2. Bundesliga

Referee: Felix Prigan

Hertha

U U U T S

0–2

Full-time

Paderborn

U S T U S

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

Hertha Paderborn

Last 6 — all competitions · 6/6 matches

Win Ø 34%

17%

50%

Points per game

1,0

1,8

Over 2.5 Ø 42%

33%

50%

Both score Ø 42%

17%

67%

Average goals

1,3

2,2

Scored

0,7

1,3

Conceded

0,7

0,8

Goal diff per game

+0,0

+0,5

This season — 2. Bundesliga · 5/5 matches

Win Ø 30%

20%

40%

Points per game

1,0

1,6

Over 2.5 Ø 40%

40%

Both score Ø 40%

20%

60%

Average goals

1,6

1,8

Scored

0,8

1,0

Conceded

0,8

Goal diff per game

+0,0

+0,2

🔒 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: 0–1

49% Possession 51%

9 Shots 17

3 Shots on target 6

2 Blocked shots 6

4 Goalkeeper saves 2

7 Corners 4

0 Offside 1

12 Free kicks against 8

4 Yellow cards 1

0 Red cards 0

The table before the match Hertha 14. · Paderborn 9. ▾

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

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