"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.
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 | +0.12 | [-0.44, 0.65] | 0.71 | ⚪ |
| Versus top-6 opponents vs. rest of the league | Vs top 6 | Vs rest | -0.09 | [-0.67, 0.50] | 0.74 | ⚪ |
| With vs. without Nikola Vasilj in the starting XI | With Nikola Vasilj | Without Nikola Vasilj | -0.15 | [-0.42, 0.15] | 0.34 | ⬜ |
| With vs. without Hauke Wahl in the starting XI | With Hauke Wahl | Without Hauke Wahl | +0.39 | [-0.71, 1.10] | 0.47 | 🟡 |
| With vs. without Eric Smith in the starting XI | With Eric Smith | Without Eric Smith | -0.41 | [-1.27, 0.41] | 0.35 | 🟡 |
| With vs. without Jackson Irvine in the starting XI | With Jackson Irvine | Without Jackson Irvine | +0.41 | [-0.13, 0.92] | 0.13 | 🟡 |
| With vs. without Manolis Saliakas in the starting XI | With Manolis Saliakas | Without Manolis Saliakas | +0.57 | [0.05, 1.09] | 0.03 | 🟢 |
| Heavy week (after UCL/intl. break) vs. normal week | Heavy week | Normal week | -0.85 | — | — | ⬜ |
| After UCL midweek vs. without UCL before | After UCL | No UCL | -0.85 | — | — | ⬜ |
| Full strength (0 absences) vs. 2+ key-player absences | 0 absences | 2+ absences | +0.59 | [-0.14, 1.33] | 0.11 | 🟡 |
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 0.853 ppg.
Prediction relevance: Kein klares Adjustment.
"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.
Related
The data shows the status quo. What does this mean for the season?
- Predictions & Forecasts — title probability, transfers, schedule strength
- The FC St. Pauli File — history, scandals, triumphs