Akte FC St. Pauli
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FC St. Pauli

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FC St. Pauli

Live data for professional portfolio management, trading and predictions.

Akte St. Pauli — Club-Dossier FC St. Pauli
Intelligence
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At a glance

Live data for professional portfolio management, trading and predictions.

Bundesliga Table

Bundesliga table matchday 2
# Club P W D L GF GA GD Pts
1 Augsburg 2 2 0 0 7 1 +6 6
2 Freiburg 2 2 0 0 5 1 +4 6
3 BVB 2 2 0 0 5 2 +3 6
4 Elversberg 2 2 0 0 7 5 +2 6
5 Mainz 2 1 1 0 5 0 +5 4
6 Bayern 2 1 1 0 5 1 +4 4
7 Leverkusen 2 1 0 1 6 3 +3 3
8 Leipzig 2 1 0 1 4 3 +1 3
9 Stuttgart 2 1 0 1 5 6 -1 3
10 Werder 2 1 0 1 4 5 -1 3
11 Koeln 2 1 0 1 4 6 -2 3
12 Paderborn 2 0 1 1 0 1 -1 1
13 Eintracht 2 0 1 1 4 7 -3 1
14 Schalke 04 2 0 1 1 0 3 -3 1
15 Union 2 0 1 1 3 7 -4 1
16 Hoffenheim 2 0 0 2 4 6 -2 0
17 Gladbach 2 0 0 2 3 7 -4 0
18 HSV 2 0 0 2 0 7 -7 0

Top Scorers

Bundesliga Top Scorers Season 28321

  1. 1
    Younes Ebnoutalib
    Younes Ebnoutalib
    Eintracht · 22
    3 Goals
  2. 2
    Yuito Suzuki
    Yuito Suzuki
    Freiburg · 24
    3 Goals
  3. 3
    Patrik Schick
    Patrik Schick
    Leverkusen · 30
    2 Goals
  4. 4
    Serhou Guirassy
    Serhou Guirassy
    BVB · 30
    2 Goals
  5. 5
    Josha Vagnoman
    Josha Vagnoman
    Stuttgart · 25
    2 Goals
# Player Club Goals
6 Thijs Dallinga Koeln 2
7 Maurice Krattenmacher Elversberg 2
8 David Mokwa Elversberg 2
9 Ridle Baku Leipzig 2
10 Phillip Tietz Mainz 2

Pinnacle Oracle

Form & Momentum

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. 1
    Josip Juranovic
    Josip Juranovic
    Union · 31
    2 Assists
  2. 2
    Vladimír Coufal
    Vladimír Coufal
    Hoffenheim · 34
    2 Assists
  3. 3
    Marco Grüll
    Marco Grüll
    Werder · 28
    2 Assists
  4. 4
    Tidiam Gomis
    Tidiam Gomis
    Leipzig · 20
    2 Assists
  5. 5
    Ismael Saibari
    Ismael Saibari
    Bayern · 25
    2 Assists
# Player Club Assists
6 Miguel Gutiérrez Leverkusen 2
7 Joshua Kimmich  Bayern 2
8 Franck Honorat Gladbach 2
9 Sheraldo Becker Mainz 2
10 Jae-sung Lee Mainz 1

Bundesliga Card Ranking (Yellow + Red×3)

  1. 1
    Ron Schallenberg
    Ron Schallenberg
    Schalke 04 · 27
    0 1
  2. 2
    Samuele Inácio
    Samuele Inácio
    BVB · 18
    0 1
  3. 3
    Phillipp Mwene
    Phillipp Mwene
    Mainz · 32
    2 0
  4. 4
    Ozan Kabak
    Ozan Kabak
    Hoffenheim · 26
    2 0
  5. 5
    Ibrahim Maza
    Ibrahim Maza
    Leverkusen · 20
    2 0
# Player Club Y R Total
6 Zeno Van Den Bosch Union 2 0 2
7 Dayot Upamecano Bayern 1 0 1
8 Grischa Prömel Stuttgart 1 0 1
9 Felix Uduokhai Union 1 0 1
10 Amara Condé Elversberg 1 0 1

Statistical Splits BETA

What actually moves Bayern's result — and what's myth. Bootstrap confidence intervals from 68 matches of the Kompany-Ära.

Split Group A Group B Δ ppg 95% CI p-value Significance
Home games vs. away games Home 0.91 ppg · n=34 Away 0.79 ppg · n=34 +0.12 [-0.44, 0.65] 0.74 ⚪
Versus top-6 opponents vs. rest of the league Vs top 6 0.79 ppg · n=24 Vs rest 0.89 ppg · n=44 -0.09 [-0.67, 0.50] 0.74 ⚪
With vs. without Nikola Vasilj in the starting XI With Nikola Vasilj 0.85 ppg · n=67 Without Nikola Vasilj 1.00 ppg · n=1 -0.15 [-0.42, 0.13] 0.31 ⬜
With vs. without Hauke Wahl in the starting XI With Hauke Wahl 0.89 ppg · n=62 Without Hauke Wahl 0.50 ppg · n=6 +0.39 [-0.69, 1.11] 0.45 🟡
With vs. without Eric Smith in the starting XI With Eric Smith 0.79 ppg · n=58 Without Eric Smith 1.20 ppg · n=10 -0.41 [-1.26, 0.38] 0.35 🟡
With vs. without Jackson Irvine in the starting XI With Jackson Irvine 0.98 ppg · n=47 Without Jackson Irvine 0.57 ppg · n=21 +0.41 [-0.13, 0.92] 0.13 🟡
With vs. without Manolis Saliakas in the starting XI With Manolis Saliakas 1.10 ppg · n=38 Without Manolis Saliakas 0.53 ppg · n=30 +0.57 [0.05, 1.09] 0.03 🟢
Heavy week (after UCL/intl. break) vs. normal week Heavy week 0.00 ppg · n=0 Normal week 0.85 ppg · n=68 -0.85 — — ⬜
After UCL midweek vs. without UCL before After UCL 0.00 ppg · n=0 No UCL 0.85 ppg · n=68 -0.85 — — ⬜
Full strength (0 absences) vs. 2+ key-player absences 0 absences 1.38 ppg · n=21 2+ absences 0.79 ppg · n=19 +0.59 [-0.17, 1.33] 0.12 🟡

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

Myth Check BETA

What fans believe — and what the data says. Every myth is tested against real match data.

Refuted

"Bayern struggles against top-6 opponents"

Gegen Top 6: 0.792 ppg · gegen Rest: 0.886 ppg (Δ -0.094).

Prediction relevance: Top-6-Gegner haben keinen messbaren Sondereffekt.

Untested

"Midweek UCL games cost points"

Indikativ: Nach CL 0 ppg, ohne CL 0.853 ppg.

Prediction relevance: Kein klares Adjustment.

Refuted

"Home games are different"

Heim: 0.912 ppg · Auswärts: 0.794 ppg (Δ 0.118).

Prediction relevance: Heimvorteil ist nicht überdurchschnittlich.

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 FC St. Pauli 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.

Frequently Asked

Who is the Bundesliga top scorer?
Younes Ebnoutalib (Eintracht) with 3 goals in the 28321 season.

Related

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