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Bundesliga – Matchday 1

Mon, Nov 9, 2026 – 14:30Europa-Park StadionNot started
Demo
Freiburg
7th • 15 Pts
VS
Dortmund
2nd • 27 Pts

Prediction Summary

30%
SCF Win
range 25%–35%
28%
Draw
range 26%–29%
42%
BVB Win
range 37%–48%
Most likely score
1 – 1
only 13% likely — not a forecast of the exact result
Expected goals: SCF 1.19 · BVB 1.46

Other markets

Over 2.5 Goals
50%
Under 2.5 Goals
50%
BTTS – Yes
55%
BTTS – No
45%

Team Comparison

FreiburgDortmund
1385Elo rating1619
L-W-L-L-LForm (last 5)W-W-W-W-L
1.60Goals for / game2.00
2.10Goals against / game1.30
1.51xG for / game1.65
1.78xG against / game1.18
29%Home win rate—
—Away win rate48%
8Rest days8

Player Availability

Freiburg
  • X. LopezDoubtful
Dortmund
  • X. SchmidtInjury

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

Analysis & Key Insights

  • Team Strength: Freiburg Elo 1385 vs Dortmund 1619 (-234).
  • Recent Form: Freiburg (L-W-L-L-L) vs Dortmund (W-W-W-W-L), last 5.
  • Goals: Freiburg score 1.60 / concede 2.10 per game; Dortmund 2.00 / 1.30 (last 10).
  • Expected Goals: Freiburg average 1.51 xG, Dortmund 1.65 (residualised vs Elo before use).
  • Home Advantage: Freiburg have won 29% of home games in the sample; Dortmund 48% away.
  • Player Availability: Freiburg: 1 absent/doubtful; Dortmund: 1.
  • Schedule & Rest: Freiburg 8 days rest, Dortmund 8 days.
  • Head-to-Head: Average goal difference -1.20 for Freiburg over recent meetings.

Predicted Scoreline Distribution

Key Factors (This Match)

  • Team Strength (Elo)
    54%
  • Home Advantage
    32%
  • Recent Form
    6%
  • Head-to-Head (H2H)
    5%
  • Expected Goals (xG)
    2%
  • Player Availability
    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 9, 2026 – 08:30
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.