"Bayern struggles against top-6 opponents"
Gegen Top 6: 0.682 ppg · gegen Rest: 1.463 ppg (Δ -0.781).
Prediction relevance: Adjustment -26.03pp für Top-6-Gegner.
Borussia Mönchengladbach
Live data for professional portfolio management, trading and predictions.

Gladbach sit 14th after matchday 30 with 30 points (7W 9D 13L, goal diff -14). Last 5 form: LWDDL (5/15 pts). Next opponent: Mainz (9th).
Last result: Loss. Last 5 form: L-W-D-D-L.
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).
Bundesliga Top Assists
| # | Player | Club | Assists |
|---|---|---|---|
| 6 | Andrej Ilic | Union | 8 |
| 7 | Bazoumana Touré | Hoffenheim | 8 |
| 8 | Jamie Leweling | Stuttgart | 8 |
| 9 | Alejandro Grimaldo | Leverkusen | 7 |
| 10 | Fisnik Asllani | Hoffenheim | 7 |
Bundesliga Card Ranking (Yellow + Red×3)
| # | 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 |
What actually moves Bayern's result — and what's myth. Bootstrap confidence intervals from 63 matches of the Kompany-Ära.
| Split | Group A | Group B | Δ ppg | 95% CI | p-value | Significance |
|---|---|---|---|---|---|---|
| Home games vs. away games | Home | Away | +0.26 | [-0.38, 0.90] | 0.40 | ⚪ |
| Versus top-6 opponents vs. rest of the league | Vs top 6 | Vs rest | -0.78 | [-1.35, -0.20] | 0.01 | 🟢 |
| With vs. without Joe Scally in the starting XI | With Joe Scally | Without Joe Scally | +1.26 | [0.85, 1.65] | 0.00 | 🟡 |
| With vs. without Nico Elvedi in the starting XI | With Nico Elvedi | Without Nico Elvedi | -0.30 | [-1.15, 0.52] | 0.52 | 🟡 |
| With vs. without Rocco Reitz in the starting XI | With Rocco Reitz | Without Rocco Reitz | -0.63 | [-1.41, 0.21] | 0.14 | 🟡 |
| With vs. without Moritz Nicolas in the starting XI | With Moritz Nicolas | Without Moritz Nicolas | +0.34 | [-0.44, 1.05] | 0.38 | ⚪ |
| With vs. without Philipp Sander in the starting XI | With Philipp Sander | Without Philipp Sander | -0.11 | [-0.75, 0.53] | 0.75 | ⚪ |
| Heavy week (after UCL/intl. break) vs. normal week | Heavy week | Normal week | -1.19 | — | — | ⬜ |
| After UCL midweek vs. without UCL before | After UCL | No UCL | -1.19 | — | — | ⬜ |
| Full strength (0 absences) vs. 2+ key-player absences | 0 absences | 2+ absences | -0.08 | [-0.84, 0.69] | 0.86 | ⚪ |
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
What fans believe — and what the data says. Every myth is tested against real match data.
Gegen Top 6: 0.682 ppg · gegen Rest: 1.463 ppg (Δ -0.781).
Prediction relevance: Adjustment -26.03pp für Top-6-Gegner.
Indikativ: Nach CL 0 ppg, ohne CL 1.19 ppg.
Prediction relevance: Kein klares Adjustment.
Heim: 1.323 ppg · Auswärts: 1.063 ppg (Δ 0.26).
Prediction relevance: Heimvorteil ist nicht überdurchschnittlich.
Attack ranking: Gladbach have 35 goals in 29 games (1.21 per game). Best attack in league: Bayern (105). Defence: Gladbach with 49 goals against (1.69 per game). Best defence: Bayern (27).
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.
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 Borussia Mönchengladbach 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?