At a glance

Live data for professional portfolio management, trading and predictions.

Bundesliga Table

Bundesliga table matchday 32
#	Club	P	W	D	L	GF	GA	GD	Pts
1	Bayern	32	26	5	1	116	35	+81	83
2	BVB	32	20	7	5	65	32	+33	67
3	Leipzig	32	19	5	8	63	42	+21	62
4	Leverkusen	32	17	7	8	66	43	+23	58
5	Stuttgart	32	17	7	8	66	46	+20	58
6	Hoffenheim	32	17	7	8	64	48	+16	58
7	Freiburg	32	12	8	12	45	53	-8	44
8	Eintracht	32	11	10	11	57	60	-3	43
9	Augsburg	32	11	7	14	42	56	-14	40
10	Mainz	32	9	10	13	41	50	-9	37
11	Gladbach	32	8	11	13	37	50	-13	35
12	HSV	32	8	10	14	36	51	-15	34
13	Union	32	8	9	15	37	57	-20	33
14	Koeln	32	7	11	14	47	55	-8	32
15	Werder	32	8	8	16	37	57	-20	32
16	Wolfsburg	32	6	8	18	42	67	-25	26
17	St. Pauli	32	6	8	18	27	55	-28	26
18	Heidenheim	32	5	8	19	38	69	-31	23

Top Scorers

Bundesliga Top Scorers Season 25646

1

Harry Kane

Bayern · 32

33 Goals
2

Deniz Undav

Stuttgart · 29

18 Goals
3

Patrik Schick

Leverkusen · 30

16 Goals
4

Luis Díaz

Bayern · 29

15 Goals
5

Serhou Guirassy

BVB · 30

15 Goals

#	Player	Club	Goals
6	Michael Olise	Bayern	14
7	Andrej Kramaric	Hoffenheim	14
8	Christoph Baumgartner	Leipzig	13
9	Yan Diomande	Leipzig	12
10	Said El Mala	Koeln	12

Form & Momentum

Wolfsburg — Form & Home/Away

Last 5

LLWDD

Home

10 Pts

Record: 2-4-10 Goals: 21:31

Away

16 Pts

Record: 4-4-8 Goals: 21:36

Last result: Draw. Last 5 form: L-L-W-D-D.

The form of the last five matches is the most important leading indicator for short-term bets. A team on a three-match win streak is significantly underpriced when the odds movement hasn't yet caught up with the momentum. The Pinnacle Oracle weights this form at roughly 30 percent against table position (40 percent), home/away splits (20 percent) and opponent strength (10 percent).

Assists & Card Ranking

Bundesliga Top Assists

1

Michael Olise

Bayern · 24

19 Assists
2

Julian Ryerson

BVB · 28

14 Assists
3

Luis Díaz

Bayern · 29

13 Assists
4

Jamie Leweling

Stuttgart · 25

9 Assists
5

Andrej Ilic

Union · 26

9 Assists

#	Player	Club	Assists
6	Bazoumana Touré	Hoffenheim	9
7	Farès Chaïbi	Eintracht	9
8	Fisnik Asllani	Hoffenheim	8
9	Konrad Laimer	Bayern	8
10	Christoph Baumgartner	Leipzig	8

Bundesliga Card Ranking (Yellow + Red×3)

1

Dominik Kohr

Mainz · 32

10 2
2

Eric Martel

Koeln · 24

11 1
3

Niklas Stark

Werder · 31

6 2
4

Marco Friedl

Werder · 28

9 1
5

Rocco Reitz

Gladbach · 23

8 1

#	Player	Club	Y	R	Total
6	Nicolai Remberg	HSV	11	0	11
7	Johan Manzambi	Freiburg	4	2	6
8	Miro Muheim	HSV	7	1	8
9	Moritz Jenz	Wolfsburg	7	1	8
10	Wouter Burger	Hoffenheim	7	1	8

Split	Group A	Group B	Δ ppg	95% CI	p-value	Significance
Home games vs. away games	Home 0.77 ppg · n=34	Away 1.35 ppg · n=34	-0.59	[-1.18, -0.03]	0.05	🟢
Versus top-6 opponents vs. rest of the league	Vs top 6 0.58 ppg · n=24	Vs rest 1.32 ppg · n=44	-0.73	[-1.26, -0.15]	0.01	🟢
With vs. without Kamil Grabara in the starting XI	With Kamil Grabara 1.00 ppg · n=63	Without Kamil Grabara 1.80 ppg · n=5	-0.80	[-1.75, 0.08]	0.08	🟡
With vs. without Konstantinos Koulierakis in the starting XI	With Konstantinos Koulierakis 1.24 ppg · n=55	Without Konstantinos Koulierakis 0.31 ppg · n=13	+0.93	[0.33, 1.43]	0.00	🟡
With vs. without Mohamed Amoura in the starting XI	With Mohamed Amoura 1.11 ppg · n=52	Without Mohamed Amoura 0.88 ppg · n=16	+0.24	[-0.49, 0.93]	0.50	⚪
With vs. without Maximilian Arnold in the starting XI	With Maximilian Arnold 1.13 ppg · n=47	Without Maximilian Arnold 0.91 ppg · n=21	+0.22	[-0.39, 0.81]	0.48	⚪
With vs. without Patrick Wimmer in the starting XI	With Patrick Wimmer 1.14 ppg · n=43	Without Patrick Wimmer 0.92 ppg · n=25	+0.22	[-0.38, 0.79]	0.48	⚪
Heavy week (after UCL/intl. break) vs. normal week	Heavy week 0.00 ppg · n=0	Normal week 1.06 ppg · n=68	-1.06	—	—	⬜
After UCL midweek vs. without UCL before	After UCL 0.00 ppg · n=0	No UCL 1.06 ppg · n=68	-1.06	—	—	⬜
Full strength (0 absences) vs. 2+ key-player absences	0 absences 1.56 ppg · n=16	2+ absences 0.78 ppg · n=23	+0.78	[0.00, 1.55]	0.05	🟡

Reading: 🟢 statistically significant · 🟡 indicative (sample or effect too small) · ⚪ no effect detectable · ⬜ untested

ppg = points per game (3 for a win, 1 for a draw, 0 for a loss). Δ ppg = difference in ppg between the two groups. 95% CI = bootstrap confidence interval (10,000 resamples). p-value < 0.05 = statistically significant at n ≥ 20.

Methodology: Single-Regime-Analyse (nur Kompany-Ära). xG fehlt im Plan und ist nicht enthalten. Bootstrap-CIs statt parametrischer Tests.
Not in dataset: xG, PPDA, Distance Covered

Confirmed

"Bayern struggles against top-6 opponents"

Gegen Top 6: 0.583 ppg · gegen Rest: 1.318 ppg (Δ -0.735).

Prediction relevance: Adjustment -24.5pp für Top-6-Gegner.

Untested

"Midweek UCL games cost points"

Indikativ: Nach CL 0 ppg, ohne CL 1.059 ppg.

Prediction relevance: Kein klares Adjustment.

Confirmed

"Home games are different"

Heim: 0.765 ppg · Auswärts: 1.353 ppg (Δ -0.588).

Prediction relevance: Adjustment -19.6pp für Heimspiele.

What the data doesn't say

Table, form and odds show the status quo. They say nothing about whether a coach is on the verge of being sacked, a key player is injured, or the board is internally under pressure. This is exactly where the Predictions page comes in: there season markets (Polymarket), transfer rumours and schedule strength feed into the assessment — factors that don't show up in any standard statistic.

The VfL Wolfsburg File in turn provides the historical context: which crises has the club survived, which not. Anyone moving money on Bundesliga markets needs all three layers — hard stats, forward markets and institutional memory.

The data shows the status quo. What does this mean for the season?

Predictions & Forecasts — title probability, transfers, schedule strength
The VfL Wolfsburg File — history, scandals, triumphs

Prediction Intelligence
VfL Wolfsburg

Bundesliga Table

Top Scorers

Pinnacle Oracle