Statistiche / Calcio / Indonesia. Liga 2 Indonesia / Persipura Jayapura vs Cilegon United

Persipura Jayapura vs Cilegon United Statistics & Analysis

Oct 09, 2026 - 08:30
1 1.72
3 0.88
xG Accuracy: 46%
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Mercati tracciati vs risultato finale

Ogni riga confronta la tendenza del modello pre-partita con il risultato finale.

  • Mercato Previsione Risultato Esito
  • Over / Under 2.5 Under 2.5 Over 2.5 (4 gol) ✖ Errato
  • Entrambe le Squadre Segnano Entrambe le squadre segnano (BTTS) No Sì ✖ Errato
  • 1X2 Persipura Jayapura Cilegon United ✖ Errato
  • Approfondimenti sul Risultato Esatto 1-0, 1-1, 2-0, 2-1, 0-0 1-3 ✖ Errato

Validation Report

Immutable Snapshot

Prediction Time: Oct 03, 2026 · 00:53 UTC Snapshot ID: dp-12678219

Closing Odds Pending
AI Fair Odds —
CLV Pending
Final Result Cilegon United win · Persipura Jayapura 1–3 Cilegon United
Prediction ✖ Missed
Decision Grade F

Model Performance

This prediction contributes to:

  • Primary Bets ROI (180d): -100.0%

Briefing AI della partita

Riepilogo AI della partita

Below is a compact, numbers-first snapshot aligned with the same engine as the cards above.

  • League: Liga 2 Indonesia
  • Fixture: Persipura Jayapura vs Cilegon United
  • Kickoff: 2026-10-09 08:30:00
  • 1X2 (model): Home 55.8% · Draw 26.6% · Away 17.6%
  • xG (showing): Persipura Jayapura 1.72 — Cilegon United 0.88 (total xG ≈ 2.6)
  • Best +EV line (same label as hero card when Primary thresholds are not met): Under 2.5 goals
  • Model: 51.8% · Implied: 48.3% · Probability edge: +3.5 pts · Est. EV: +3.6%
  • BTTS (model): Yes 49.5% · No 50.5%
  • Correct score (top bin): 1-0 (12.8%)

Use the cards for tiering; this text only restates the same inputs in narrative form.

Correct score remains high-variance even when a line is most likely on paper.

Raccomandazione Storica

Decisione Storica: Selective Lean - No Primary Bet

Esito: Missed — Pre-match 1X2 lean did not match the full-time result.

Fattori di Rischio Considerati Prima del Calcio d'Inizio

  • Price movement: implied probabilities and EV move with odds.
  • Sample / data gaps: low-information leagues widen forecast bands.
  • In-play state: goals and red cards are not modelled here.
  • Scoreline variance: the most likely scoreline is still usually a low absolute probability outcome (often well below 20%).

Ultimo aggiornamento

October 10, 2026 (UTC)

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