Prediction Audit: KMC vs Kitayosce Prediction, Odds & AI Betting Tips

Jun 12, 2026 - 17:00
0 0.97
1 1.07
xG Accuracy: 75%

AI correctly predicted the Kitayosce win.

The match finished 0–1, validating the model's directional assessment.

Tracked markets vs full-time result

Prediction grade A

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 Kitayosce Kitayosce ✔ Correct
  • Correct Score Insights 0-1, 1-1, 0-0, 1-0, 0-2 0-1 ✔ Correct

Post Match Insights

What worked

  • Low-scoring profile materialised (ΣxG 2.04, 1 goals)
  • Both Teams To Score (No) matched the full-time result
  • Under 2.5 goals aligned with the xG profile

Market lesson

The model's directional lean matched the full-time result (Kitayosce win 0–1).

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Prediction Timeline

How this prediction moved from forecast to full-time review.

  1. Jun 12, 2026 · 12:38 UTC Forecast generated
    • xG · KMC 0.97 — Kitayosce 1.07
  2. Jun 12, 2026 · 17:00 UTC Kickoff
  3. FT Full-time result Kitayosce win · 0–1
  4. FT Prediction validated Directional lean matched full-time result
  5. Archived Prediction review

Historical Snapshot

Frozen at kickoff — the model output as it stood before the match started.

Historical verdict: Observe
Historical Decision No Primary Bet
Outcome Validated
Pre-match metrics (historical context)
Prediction Reliability 57/100 · Moderate
  • Validation: Pending
Evidence ★★★★★
  • No strong statistical edge
  • Market has already priced much of the edge
  • Validation pending
Market Compatibility 100/100
Betting Confidence 59/100

Validation Report

Immutable Snapshot

Prediction Time: Jul 24, 2026 · 16:13 UTC Snapshot ID: dp-1616383

Closing Odds Pending
AI Fair Odds —
CLV Pending
Final Result Kitayosce win · KMC 0–1 Kitayosce
Prediction ✔ Correct
Decision Grade A

Model Performance

This prediction contributes to:

  • Primary Bets ROI (180d): -100.0%

Review FAQ

How accurate was the prediction?
This page grades directional markets (1X2, Over/Under 2.5, BTTS) against the full-time result. The prediction grade reflects how many of those tracked markets matched reality.
What does xG Accuracy measure?
xG Accuracy compares the model's pre-match expected-goals profile to the actual scoreline — not whether every market hit. A strong directional review can coexist with a moderate xG accuracy score.
Why wasn't the exact score predicted?
Correct-score outcomes are low-probability tails even when the model reads the match profile well. We highlight top score bins for context; missing the exact line does not invalidate a directional review.
Does this improve the AI record?
Each finished match is logged in our validation pipeline. Aggregated hit rates and CLV studies are published separately — this page is the per-match audit trail.

Predictions are for informational purposes only. Always gamble responsibly and within your limits. Past performance does not guarantee future results.

AI match briefing

AI Match Summary

Quick read on how the model reads this matchup.

  • League: Ligi kuu Bara
  • Fixture: KMC vs Kitayosce
  • Kickoff: 2026-06-12 15:30:00
  • 1X2 (model): Home 30.4% · Draw 33.9% · Away 35.6%
  • xG (showing): KMC 0.97 — Kitayosce 1.07 (total xG ≈ 2.04)
  • 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 66.6% · Over 2.5 33.4%); BTTS No (Yes 42.5% · No 57.5%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS No
  • BTTS (model): Yes 42.5% · No 57.5%
  • Correct score (top bin): 0-1 (13.9%)

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: 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 02, 2026 (UTC)

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Back to Predictions
Ligi kuu Bara Ligi kuu Bara — Standings
# TEAM MP W D L PTS
1 Young Africans 30 23 6 1 75
2 Simba 30 22 7 1 73
3 Azam 30 18 10 2 64
4 Singida Fountain Gate 30 15 5 10 50
5 Kitayosce 30 11 10 9 43
6 JKT Tanzania 30 10 12 8 42
7 Pamba Jiji 30 9 9 12 36
8 Coastal Union 30 9 9 12 36
9 Dodoma Jiji 30 8 11 11 35
10 Namungo 30 7 13 10 34
11 Mashujaa 30 7 12 11 33
12 Singida Big Stars 30 9 6 15 33
13 Tanzania Prisons 30 9 5 16 32
14 Mbeya City 30 7 9 14 30
15 Mtibwa Sugar 30 6 9 15 27
16 KMC 30 2 3 25 9
# TEAM MP GS GC +/- PTS
1 Young Africans 30 71 9 +62 75
2 Simba 30 54 11 +43 73
3 Singida Fountain Gate 30 47 35 +12 50
4 Azam 30 46 12 +34 64
5 Kitayosce 30 33 28 +5 43
6 Pamba Jiji 30 32 35 -3 36
7 Coastal Union 30 31 37 -6 36
8 JKT Tanzania 30 30 33 -3 42
9 Namungo 30 25 32 -7 34
10 Dodoma Jiji 30 25 36 -11 35
11 Singida Big Stars 30 25 44 -19 33
12 Mtibwa Sugar 30 25 48 -23 27
13 Mbeya City 30 24 41 -17 30
14 Tanzania Prisons 30 23 41 -18 32
15 KMC 30 16 53 -37 9
16 Mashujaa 30 15 27 -12 33