Statistics / Football / Hungary. Magyar Kupa / TFSE Budapest vs Vasas

TFSE Budapest vs Vasas Statistics & Analysis

TFSE Budapest TFSE Budapest
Sep 12, 2026 - 13:00
1 1.18
3 1.42
xG Accuracy: 62%
Vasas Vasas
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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 (4 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 Vasas Vasas ✔ Correct
  • Correct Score Insights 1-1, 0-1, 1-2, 1-0, 0-2 1-3 ✖ Incorrect

Validation Report

Immutable Snapshot

Prediction Time: Sep 07, 2026 · 01:30 UTC Snapshot ID: dp-7436635

Closing Odds Pending
AI Fair Odds —
CLV Pending
Final Result Vasas win · TFSE Budapest 1–3 Vasas
Prediction ✔ Correct
Decision Grade B-

Model Performance

This prediction contributes to:

  • Primary Bets ROI (180d): -100.0%

AI match briefing

AI Match Summary

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

  • League: Magyar Kupa
  • Fixture: TFSE Budapest vs Vasas
  • Kickoff: 2026-09-12 13:00:00
  • 1X2 (model): Home 29.6% · Draw 29.4% · Away 41.0%
  • xG (showing): TFSE Budapest 1.18 — Vasas 1.42 (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 54.1% · No 45.9%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes
  • BTTS (model): Yes 54.1% · No 45.9%
  • 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: 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

September 28, 2026 (UTC)

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