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Bundesliga – Matchday 2

Thu, Nov 12, 2026 – 12:00Allianz ArenaNot started
Demo
Bayern
1st • 27 Pts
VS
Freiburg
7th • 15 Pts

Prediction Summary

58%
FCB Win
range 53%–63%
24%
Draw
range 22%–26%
18%
SCF Win
range 14%–21%
Most likely score
1 – 1
only 11% likely — not a forecast of the exact result
Expected goals: FCB 1.86 · SCF 0.94

Other markets

Over 2.5 Goals
53%
Under 2.5 Goals
47%
BTTS – Yes
52%
BTTS – No
48%

Team Comparison

BayernFreiburg
1625Elo rating1385
W-D-W-D-WForm (last 5)L-W-L-L-L
1.90Goals for / game1.60
1.00Goals against / game2.10
1.70xG for / game1.51
1.12xG against / game1.78
62%Home win rate—
—Away win rate38%
11Rest days11

Player Availability

Bayern

No reported absences.

Freiburg
  • P. MoreauDoubtful
  • B. MüllerInjury

Confirmed lineups are published ~1 hour before kickoff and are not yet available.

Analysis & Key Insights

  • Team Strength: Bayern Elo 1625 vs Freiburg 1385 (+240).
  • Recent Form: Bayern (W-D-W-D-W) vs Freiburg (L-W-L-L-L), last 5.
  • Goals: Bayern score 1.90 / concede 1.00 per game; Freiburg 1.60 / 2.10 (last 10).
  • Expected Goals: Bayern average 1.70 xG, Freiburg 1.51 (residualised vs Elo before use).
  • Home Advantage: Bayern have won 62% of home games in the sample; Freiburg 38% away.
  • Player Availability: Bayern: 0 absent/doubtful; Freiburg: 2.
  • Schedule & Rest: Bayern 11 days rest, Freiburg 11 days.
  • Head-to-Head: Average goal difference +1.20 for Bayern over recent meetings.

Predicted Scoreline Distribution

Key Factors (This Match)

  • Team Strength (Elo)
    55%
  • Home Advantage
    32%
  • Head-to-Head (H2H)
    5%
  • Recent Form
    5%
  • Player Availability
    2%
  • Expected Goals (xG)
    1%
  • Schedule & Rest
    0%

Share of the total adjustment to expected goals contributed by each factor in this match.

Model Information

Model:
Elo + Poisson + Dixon-Coles (elo-poisson-dc-v1)
Prediction made:
Nov 12, 2026 – 06:00
Data completeness:
100%
History used:
84 prior matches (both teams)
Data source:
Synthetic demo data

Data completeness = half history depth (40+ prior matches = full) + half optional inputs present (xG, availability, rest, H2H). It is not a win probability.

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Probabilities are estimates, never certainties. The long-term research target is 90%+ accuracy on narrowly defined markets — this is a goal, not a verified result. Figures shown are measured on simulated DEMO matches until real data is connected.