Statistics / Football / World. Friendlies / Argentina vs Burkina Faso

Argentina vs Burkina Faso Statistics & Analysis

Oct 04, 2026 - 00:00
7 1.44
0 1.16
xG Accuracy: 16%
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Tracked markets vs full-time result

Each row compares the pre-match model lean to the full-time result.

  • Market Prediction Result Outcome
  • Over / Under 2.5 Under 2.5 Over 2.5 (7 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 Argentina Argentina ✔ Correct
  • Correct Score Insights 1-1, 1-0, 2-1, 0-1, 2-0 7-0 ✖ Incorrect

Validation Report

Immutable Snapshot

Prediction Time: Sep 29, 2026 · 00:45 UTC Snapshot ID: dp-11655933

Closing Odds Pending
AI Fair Odds —
CLV Pending
Final Result Argentina win · Argentina 7–0 Burkina Faso
Prediction ✔ Correct
Decision Grade F

Model Performance

This prediction contributes to:

  • Primary Bets ROI (180d): -100.0%

AI match briefing

AI Match Summary

Quick read on how the model reads this matchup.

  • League: Friendlies
  • Fixture: Argentina vs Burkina Faso
  • Kickoff: 2026-10-04 00:00:00
  • 1X2 (model): Home 41.9% · Draw 29.3% · Away 28.8%
  • xG (showing): Argentina 1.44 — Burkina Faso 1.16 (total xG ≈ 2.6)
  • Value headline: None (actionable) — best tracked EV is about +1.8%, still below the +2.0% minimum for a headline / default stake (no default bet).
  • Structural leans (not bets): Structural lean (model): O/U 2.5 Under 2.5 (Under 2.5 51.8% · Over 2.5 48.2%); BTTS Yes (Yes 54.0% · No 46.0%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes
  • BTTS (model): Yes 54.0% · No 46.0%
  • Correct score (top bin): 1-1 (12.4%)

When book depth is thin or odds are missing, EV may be unavailable even though the model still prefers one side on totals or BTTS — wait for cleaner prices or skip.

Prefer skipping to over-staking when the engine is honest about missing edge.

Historical Recommendation

Historical Decision: AI–Market Conflict - No Primary Bet

Outcome: Validated — Pre-match lean validated against the full-time result.

Risk Factors Considered Before Kickoff

  • 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%).

Last Updated

October 04, 2026 (UTC)

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