"Bayern struggles against top-6 opponents"
Gegen Top 6: 0.792 ppg · gegen Rest: 1.523 ppg (Δ -0.731).
Prediction relevance: Adjustment -24.37pp für Top-6-Gegner.
At a glance
Augsburg sit 10th after matchday 7 with 8 points (2W 2D 2L, goal diff +4). Last 5 form: WDLDL (5/15 pts).
Top Scorers
Bundesliga Top Scorers Season 28321
- 1
Patrik Schick6 Goals - 2
Niclas Füllkrug6 Goals - 3
Michael Olise5 Goals - 4
Younes Ebnoutalib5 Goals - 5
Phillip Tietz5 Goals
| # | Player | Club | Goals |
|---|---|---|---|
| 6 | Harry Kane | Bayern | 4 |
| 7 | Christopher Nkunku | Leipzig | 4 |
| 8 | Luis Díaz | Bayern | 4 |
| 9 | Michael Gregoritsch | Augsburg | 4 |
| 10 | Yuito Suzuki | Freiburg | 4 |
Form & Momentum
Augsburg — Form & Home/Away
Last 5
WDLDL
Home
5 Pts
Away
3 Pts
Last result: Loss. Last 5 form: W-D-L-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).
Assists & Card Ranking
Bundesliga Top Assists
- 1
Marco Grüll5 Assists - 2
Harry Kane5 Assists - 3
Antonio Nusa3 Assists - 4
Joshua Kimmich3 Assists - 5
Lukas Ullrich3 Assists
| # | Player | Club | Assists |
|---|---|---|---|
| 6 | Fabian Rieder | Augsburg | 3 |
| 7 | Sheraldo Becker | Mainz | 3 |
| 8 | Derry Scherhant | Freiburg | 3 |
| 9 | Matthias Ginter | Freiburg | 3 |
| 10 | Miguel Gutiérrez | Leverkusen | 3 |
Bundesliga Card Ranking (Yellow + Red×3)
- 1
Yuito Suzuki2 1 - 2
Bernardo1 1 - 3
Tim Kleindienst1 1 - 4
Raphael Onyedika4 0 - 5 Ron Schallenberg0 1
| # | Player | Club | Y | R | Total |
|---|---|---|---|---|---|
| 6 | Samuele Inácio | BVB | 0 | 1 | 1 |
| 7 | Shuto Machino | Gladbach | 3 | 0 | 3 |
| 8 | Felix Keidel | Elversberg | 3 | 0 | 3 |
| 9 | Kevin Diks | Gladbach | 3 | 0 | 3 |
| 10 | Wouter Burger | Hoffenheim | 3 | 0 | 3 |
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 | Away | +0.35 | [-0.27, 0.97] | 0.28 | ⚪ |
| Versus top-6 opponents vs. rest of the league | Vs top 6 | Vs rest | -0.73 | [-1.33, -0.11] | 0.02 | 🟢 |
| With vs. without Dimitrios Giannoulis in the starting XI | With Dimitrios Giannoulis | Without Dimitrios Giannoulis | +0.12 | [-0.73, 0.92] | 0.78 | 🟡 |
| With vs. without Finn Dahmen in the starting XI | With Finn Dahmen | Without Finn Dahmen | +0.25 | [-0.48, 0.95] | 0.50 | ⚪ |
| With vs. without Alexis Claude-Maurice in the starting XI | With Alexis Claude-Maurice | Without Alexis Claude-Maurice | +0.36 | [-0.35, 1.03] | 0.31 | ⚪ |
| With vs. without Kristijan Jakic in the starting XI | With Kristijan Jakic | Without Kristijan Jakic | +0.01 | [-0.67, 0.67] | 0.98 | ⚪ |
| With vs. without Chrislain Matsima in the starting XI | With Chrislain Matsima | Without Chrislain Matsima | -0.13 | [-0.76, 0.51] | 0.72 | ⚪ |
| Heavy week (after UCL/intl. break) vs. normal week | Heavy week | Normal week | -1.26 | — | — | ⬜ |
| After UCL midweek vs. without UCL before | After UCL | No UCL | -1.26 | — | — | ⬜ |
| Full strength (0 absences) vs. 2+ key-player absences | 0 absences | 2+ absences | +0.04 | [-0.72, 0.82] | 0.91 | ⚪ |
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 1.265 ppg.
Prediction relevance: Kein klares Adjustment.
"Home games are different"
Heim: 1.441 ppg · Auswärts: 1.088 ppg (Δ 0.353).
Prediction relevance: Heimvorteil ist nicht überdurchschnittlich.
Data Analysis
Relegation zone matchday 7: Paderborn (16th, 5 pts), Union (17th, 5 pts), Gladbach (18th, 3 pts). Augsburg are 3 points clear of the relegation place. Points per game: 1.33.
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 FC Augsburg 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 Augsburg currently stand?
- 10th with 8 points after matchday 7 (2W 2D 2L, goal diff +4).
- Who is the Bundesliga top scorer?
- Patrik Schick (Leverkusen) with 6 goals in the 28321 season.
- Will Augsburg be relegated?
- Augsburg are currently 3 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 FC Augsburg File — history, scandals, triumphs