Statistics / Football / World. Friendlies Clubs / Tottenham vs Milton Keynes Dons

Tottenham vs Milton Keynes Dons Statistics & Analysis

Tottenham Tottenham
Jul 22, 2026 - 16:00
1 1.39
0 1.21
xG Accuracy: 64%
Milton Keynes Dons Milton Keynes Dons
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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 Under 2.5 (1 goals) ✔ Correct
  • Both Teams To Score BTTS No No ✔ Correct
  • 1X2 Tottenham Tottenham ✔ Correct
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 1-0 ✔ Correct

Validation Report

Immutable Snapshot

Prediction Time: Aug 03, 2026 · 05:30 UTC Snapshot ID: dp-2913687

Closing Odds Pending
AI Fair Odds —
CLV Pending
Final Result Tottenham win · Tottenham 1–0 Milton Keynes Dons
Prediction ✔ Correct
Decision Grade A

AI match briefing

AI Match Summary

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

  • League: Club Friendlies
  • Fixture: Tottenham Hotspur vs Milton Keynes Dons
  • Kickoff: 2026-07-22 16:00:00
  • 1X2 (model): Home 39.5% · Draw 29.5% · Away 31.0%
  • xG (showing): Tottenham Hotspur 1.39 — Milton Keynes Dons 1.21 (total xG ≈ 2.6)
  • Value headline: At least one tracked line reaches the headline EV threshold — align with the hero / Primary card if shown.
  • Structural leans (not bets): Value lean (pricing): O/U 2.5 Under 2.5; BTTS No
  • BTTS (model): Yes N/A · No N/A
  • Correct score (top bin): N/A

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.

Most likely correct score stays a low-probability tail: use it for context, not as a must-bet story.

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 15, 2026 (UTC)

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