⚽MatchPredict Pro

Serie A – Matchday 2

Thu, Nov 12, 2026 – 19:30Allianz StadiumNot started
Demo
Juventus
2nd • 22 Pts
VS
Napoli
4th • 18 Pts

Prediction Summary

50%
JUV Win
range 44%–55%
26%
Draw
range 25%–28%
24%
NAP Win
range 20%–28%
Most likely score
1 – 1
only 13% likely — not a forecast of the exact result
Expected goals: JUV 1.63 · NAP 1.07

Other markets

Over 2.5 Goals
51%
Under 2.5 Goals
49%
BTTS – Yes
54%
BTTS – No
46%

Team Comparison

JuventusNapoli
1570Elo rating1484
W-L-W-L-WForm (last 5)D-W-L-L-L
2.20Goals for / game1.50
1.20Goals against / game1.70
1.91xG for / game1.37
1.05xG against / game1.61
43%Home win rate—
—Away win rate24%
11Rest days11

Player Availability

Juventus
  • S. NovakInjury
  • M. SchmidtInjury
Napoli

No reported absences.

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

Analysis & Key Insights

  • Team Strength: Juventus Elo 1570 vs Napoli 1484 (+86).
  • Recent Form: Juventus (W-L-W-L-W) vs Napoli (D-W-L-L-L), last 5.
  • Goals: Juventus score 2.20 / concede 1.20 per game; Napoli 1.50 / 1.70 (last 10).
  • Expected Goals: Juventus average 1.91 xG, Napoli 1.37 (residualised vs Elo before use).
  • Home Advantage: Juventus have won 43% of home games in the sample; Napoli 24% away.
  • Player Availability: Juventus: 2 absent/doubtful; Napoli: 0.
  • Schedule & Rest: Juventus 11 days rest, Napoli 11 days.
  • Head-to-Head: Average goal difference -0.40 for Juventus over recent meetings.

Predicted Scoreline Distribution

Key Factors (This Match)

  • Home Advantage
    47%
  • Team Strength (Elo)
    29%
  • Expected Goals (xG)
    13%
  • Recent Form
    6%
  • Player Availability
    3%
  • Head-to-Head (H2H)
    2%
  • 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 – 13:30
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.