"Bayern struggles against top-6 opponents"
Gegen Top 6: 0.4 ppg · gegen Rest: 1.368 ppg (Δ -0.968).
Prediction relevance: Top-6-Gegner haben keinen messbaren Sondereffekt.
At a glance
Koeln sit 13th after matchday 29 with 30 points (7W 9D 13L, goal diff -7). Last 5 form: LDDDW (6/15 pts). Next opponent: St. Pauli (16th).
Top Scorers
Bundesliga Top Scorers Season 25646
- 1
Harry Kane31 Goals - 2
Deniz Undav18 Goals - 3
Luis Díaz15 Goals - 4
Serhou Guirassy13 Goals - 5
Michael Olise12 Goals
| # | Player | Club | Goals |
|---|---|---|---|
| 6 | Christoph Baumgartner | Leipzig | 12 |
| 7 | Yan Diomande | Leipzig | 11 |
| 8 | Said El Mala | Koeln | 11 |
| 9 | Haris Tabakovic | Gladbach | 11 |
| 10 | Andrej Kramaric | Hoffenheim | 10 |
Form & Momentum
Koeln — Form & Home/Away
Last 5
LDDDW
Home
19 Pts
Away
11 Pts
Last result: Win. Last 5 form: L-D-D-D-W.
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 Olise18 Assists
- 2
Julian Ryerson13 Assists - 3 Luis Díaz11 Assists
- 4
Farès Chaïbi9 Assists - 5
Bazoumana Touré8 Assists
| # | Player | Club | Assists |
|---|---|---|---|
| 6 | Christoph Baumgartner | Leipzig | 8 |
| 7 | Andrej Ilic | Union | 8 |
| 8 | Jamie Leweling | Stuttgart | 8 |
| 9 | Vladimír Coufal | Hoffenheim | 7 |
| 10 | Fisnik Asllani | Hoffenheim | 7 |
Bundesliga Card Ranking (Yellow + Red×3)
- 1
Dominik Kohr8 2 - 2
Eric Martel10 1 - 3
Niklas Stark6 2 - 4
Marco Friedl8 1 - 5
Johan Manzambi4 2
| # | Player | Club | Y | R | Total |
|---|---|---|---|---|---|
| 6 | Moritz Jenz | Wolfsburg | 7 | 1 | 8 |
| 7 | Rocco Reitz | Gladbach | 7 | 1 | 8 |
| 8 | Nicolai Remberg | HSV | 10 | 0 | 10 |
| 9 | Fábio Vieira | HSV | 3 | 2 | 5 |
| 10 | Miro Muheim | HSV | 6 | 1 | 7 |
Statistical Splits BETA
What actually moves Bayern's result — and what's myth. Bootstrap confidence intervals from 29 matches of the Kompany-Ära.
| Split | Group A | Group B | Δ ppg | 95% CI | p-value | Significance |
|---|---|---|---|---|---|---|
| Home games vs. away games | Home | Away | +0.48 | [-0.35, 1.31] | 0.27 | 🟡 |
| Versus top-6 opponents vs. rest of the league | Vs top 6 | Vs rest | -0.97 | [-1.69, -0.15] | 0.02 | 🟡 |
| With vs. without Marvin Schwäbe in the starting XI | With Marvin Schwäbe | Without Marvin Schwäbe | +1.03 | — | — | ⬜ |
| With vs. without Jakub Kamiński in the starting XI | With Jakub Kamiński | Without Jakub Kamiński | +1.03 | — | — | ⬜ |
| With vs. without Eric Martel in the starting XI | With Eric Martel | Without Eric Martel | +0.78 | [0.06, 1.46] | 0.04 | ⬜ |
| With vs. without Sebastian Sebulonsen in the starting XI | With Sebastian Sebulonsen | Without Sebastian Sebulonsen | +0.25 | [-0.80, 1.17] | 0.61 | 🟡 |
| With vs. without Kristoffer Lund in the starting XI | With Kristoffer Lund | Without Kristoffer Lund | +0.23 | [-0.69, 1.08] | 0.61 | 🟡 |
| Heavy week (after UCL/intl. break) vs. normal week | Heavy week | Normal week | -1.03 | — | — | ⬜ |
| After UCL midweek vs. without UCL before | After UCL | No UCL | -1.03 | — | — | ⬜ |
| Full strength (0 absences) vs. 2+ key-player absences | 0 absences | 2+ absences | +1.39 | — | — | ⬜ |
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.
"Midweek UCL games cost points"
Indikativ: Nach CL 0 ppg, ohne CL 1.034 ppg.
Prediction relevance: Kein klares Adjustment.
"Home games are different"
Heim: 1.267 ppg · Auswärts: 0.786 ppg (Δ 0.481).
Prediction relevance: Heimvorteil ist nicht überdurchschnittlich.
Data Analysis
Last 5 form: Koeln: LDDDW (6/15 pts). Best in league: Bayern (WDWWW, 13/15). Worst: Wolfsburg (LDLLL, 1/15).
This analysis rotates with every matchday through eight data-driven templates: league leadership, relegation battle, Champions League race, home/away splits, form trends, attack/defence, factual summary and overall view. Every statement is grounded in SportsMonks and Pinnacle data — no speculation, no hallucination.
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 1. FC Köln 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
- Where do Koeln currently stand?
- 13th with 30 points after matchday 29 (7W 9D 13L, goal diff -7).
- Who is Koeln's next opponent?
- St. Pauli, kickoff on 2026-04-17.
- Who is the Bundesliga top scorer?
- Harry Kane (Bayern) with 31 goals in the 25646 season.
- Will Koeln be relegated?
- Koeln are currently 5 points clear of the relegation places.
Related
The data shows the status quo. What does this mean for the season?
- Predictions & Forecasts — title probability, transfers, schedule strength
- The 1. FC Köln File — history, scandals, triumphs