⚽MatchPredict Pro

Bundesliga – Matchday 3

Sun, Nov 15, 2026 – 14:30MHPArenaNot started
Demo
Stuttgart
3rd • 26 Pts
VS
Freiburg
7th • 15 Pts

Prediction Summary

53%
VFB Win
range 47%–58%
26%
Draw
range 24%–27%
22%
SCF Win
range 18%–26%
Most likely score
1 – 1
only 12% likely — not a forecast of the exact result
Expected goals: VFB 1.71 · SCF 1.02

Other markets

Over 2.5 Goals
51%
Under 2.5 Goals
49%
BTTS – Yes
53%
BTTS – No
47%

Team Comparison

StuttgartFreiburg
1553Elo rating1385
W-D-D-D-WForm (last 5)L-W-L-L-L
1.70Goals for / game1.60
1.20Goals against / game2.10
1.53xG for / game1.51
1.20xG against / game1.78
48%Home win rate—
—Away win rate38%
14Rest days14

Player Availability

Stuttgart
  • T. FernandesSuspension
Freiburg

No reported absences.

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

Analysis & Key Insights

  • Team Strength: Stuttgart Elo 1553 vs Freiburg 1385 (+168).
  • Recent Form: Stuttgart (W-D-D-D-W) vs Freiburg (L-W-L-L-L), last 5.
  • Goals: Stuttgart score 1.70 / concede 1.20 per game; Freiburg 1.60 / 2.10 (last 10).
  • Expected Goals: Stuttgart average 1.53 xG, Freiburg 1.51 (residualised vs Elo before use).
  • Home Advantage: Stuttgart have won 48% of home games in the sample; Freiburg 38% away.
  • Player Availability: Stuttgart: 1 absent/doubtful; Freiburg: 0.
  • Schedule & Rest: Stuttgart 14 days rest, Freiburg 14 days.
  • Head-to-Head: Average goal difference +0.40 for Stuttgart over recent meetings.

Predicted Scoreline Distribution

Key Factors (This Match)

  • Team Strength (Elo)
    50%
  • Home Advantage
    42%
  • Recent Form
    3%
  • Head-to-Head (H2H)
    2%
  • 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 15, 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.