⚽MatchPredict Pro

La Liga – Matchday 3

Sun, Nov 15, 2026 – 16:00San MamésNot started
Demo
Athletic
3rd • 21 Pts
VS
Sevilla
8th • 14 Pts

Prediction Summary

50%
ATH Win
range 45%–55%
26%
Draw
range 25%–28%
24%
SEV Win
range 20%–28%
Most likely score
1 – 1
only 13% likely — not a forecast of the exact result
Expected goals: ATH 1.64 · SEV 1.06

Other markets

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

Team Comparison

AthleticSevilla
1484Elo rating1356
L-W-L-D-LForm (last 5)W-D-L-L-D
1.50Goals for / game0.70
1.30Goals against / game1.80
1.39xG for / game0.91
1.17xG against / game1.56
48%Home win rate—
—Away win rate10%
14Rest days14

Player Availability

Athletic

No reported absences.

Sevilla
  • G. NovakInjury
  • U. MoreauInjury

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

Analysis & Key Insights

  • Team Strength: Athletic Elo 1484 vs Sevilla 1356 (+128).
  • Recent Form: Athletic (L-W-L-D-L) vs Sevilla (W-D-L-L-D), last 5.
  • Goals: Athletic score 1.50 / concede 1.30 per game; Sevilla 0.70 / 1.80 (last 10).
  • Expected Goals: Athletic average 1.39 xG, Sevilla 0.91 (residualised vs Elo before use).
  • Home Advantage: Athletic have won 48% of home games in the sample; Sevilla 10% away.
  • Player Availability: Athletic: 0 absent/doubtful; Sevilla: 2.
  • Schedule & Rest: Athletic 14 days rest, Sevilla 14 days.
  • Head-to-Head: Average goal difference -0.20 for Athletic over recent meetings.

Predicted Scoreline Distribution

Key Factors (This Match)

  • Home Advantage
    44%
  • Team Strength (Elo)
    40%
  • Recent Form
    7%
  • Expected Goals (xG)
    5%
  • Player Availability
    3%
  • Head-to-Head (H2H)
    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 – 10:00
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.