"Bayern struggles against top-6 opponents"
Gegen Top 6: 0.375 ppg · gegen Rest: 1.045 ppg (Δ -0.67).
Prediction relevance: Adjustment -22.33pp für Top-6-Gegner.
At a glance
Live data for professional portfolio management, trading and predictions.
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).
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 | +0.03 | [-0.53, 0.59] | 0.97 | ⚪ |
| Versus top-6 opponents vs. rest of the league | Vs top 6 | Vs rest | -0.67 | [-1.14, -0.18] | 0.01 | 🟢 |
| With vs. without Patrick Mainka in the starting XI | With Patrick Mainka | Without Patrick Mainka | +0.81 | — | — | ⬜ |
| With vs. without Jan Schöppner in the starting XI | With Jan Schöppner | Without Jan Schöppner | +0.27 | [-0.65, 0.97] | 0.51 | 🟡 |
| With vs. without Benedikt Gimber in the starting XI | With Benedikt Gimber | Without Benedikt Gimber | -0.18 | [-0.83, 0.43] | 0.58 | ⚪ |
| With vs. without Jonas Föhrenbach in the starting XI | With Jonas Föhrenbach | Without Jonas Föhrenbach | -0.00 | [-0.61, 0.58] | 1.00 | ⚪ |
| With vs. without Omar Traoré in the starting XI | With Omar Traoré | Without Omar Traoré | -0.22 | [-0.83, 0.38] | 0.49 | ⚪ |
| Heavy week (after UCL/intl. break) vs. normal week | Heavy week | Normal week | -0.81 | — | — | ⬜ |
| After UCL midweek vs. without UCL before | After UCL | No UCL | -0.81 | — | — | ⬜ |
| Full strength (0 absences) vs. 2+ key-player absences | 0 absences | 2+ absences | -0.24 | [-1.00, 0.52] | 0.52 | ⚪ |
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 0.809 ppg.
Prediction relevance: Kein klares Adjustment.
"Home games are different"
Heim: 0.824 ppg · Auswärts: 0.794 ppg (Δ 0.03).
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 1. FC Heidenheim 1846 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.
Related
The data shows the status quo. What does this mean for the season?
- Predictions & Forecasts — title probability, transfers, schedule strength
- The 1. FC Heidenheim 1846 File — history, scandals, triumphs