Kasuka vs Karketu Dili Statistics & Analysis

Sep 15, 2026 - 12:15
2 1.23
1 1.37
xG Accuracy: 73%
Premium betting site stake: New users can use the promo code FHn2uDc1 to receive $100 cash.

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 (3 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 Karketu Dili Kasuka ✖ Incorrect
  • Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 2-1 ✔ Correct

Validation Report

Immutable Snapshot

Prediction Time: Sep 02, 2026 · 02:10 UTC Snapshot ID: dp-6578365

Closing Odds Pending
AI Fair Odds —
CLV Pending
Final Result Kasuka win · Kasuka 2–1 Karketu Dili
Prediction ✖ Missed
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: AFC Challenge League
  • Fixture: Kasuka vs Karketu Dili
  • Kickoff: 2026-09-08 12:15:00
  • 1X2 (model): Home 31.9% · Draw 29.6% · Away 38.5%
  • xG (showing): Kasuka 1.23 — Karketu Dili 1.37 (total xG ≈ 2.6)
  • Value headline: None — no positive EV could be estimated on tracked lines at current best prices (missing odds or thin book depth).
  • 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 54.4% · No 45.6%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes
  • BTTS (model): Yes 54.4% · No 45.6%
  • Correct score (top bin): 1-1 (12.5%)

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: No Primary Bet

Outcome: Missed — Pre-match 1X2 lean did not match 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

September 29, 2026 (UTC)

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