Predictions / Football / World. Africa Cup of Nations - Qualification / Tanzania vs Guinea-Bissau

Prediction Audit: Tanzania vs Guinea-Bissau Prediction, Odds & AI Betting Tips

Tanzania Tanzania
Sep 25, 2026 - 13:00
0 1.37
2 1.23
xG Accuracy: 56%
Guinea-Bissau Guinea-Bissau

The model missed the final outcome (Guinea-Bissau win 0–2).

The model had projected Tanzania at 38.5%, but the full-time result went the other way.

Tracked markets vs full-time result

Prediction grade F

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

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

Model vs Closing Market

Moderate Disagreement

The model rates Guinea-Bissau considerably stronger than the closing betting market.

Largest probability gap: Guinea-Bissau +7.4 pp

Outcome Model Closing Market Difference Signal
Tanzania 38.5% 42.4% -3.9 pp Aligned
Draw 29.6% 33.1% -3.5 pp Aligned
Guinea-Bissau 31.9% 24.6% +7.4 pp Model Higher

The statistical model estimates Guinea-Bissau's win probability at 31.9%, compared with the closing market's implied probability of 24.6%, a difference of 7.4 percentage points. This highlights a substantial disagreement between the model's assessment and the market consensus, rather than indicating which view is ultimately correct.

Model probabilities are generated from the statistical xG model using a Poisson distribution. Closing market probabilities are derived from consensus closing 1X2 odds after margin removal. Values represent implied probabilities rather than betting recommendations. Closing snapshot: PRE1.

After full time, the result was Guinea-Bissau win 0–2.

Market Assessment

The fair estimate shows a modest edge over current market pricing on Guinea-Bissau.

  • Monitor line movement before kickoff — not a betting recommendation.

Post Match Insights

What failed

  • Both Teams To Score: model leaned BTTS Yes; match finished BTTS No
  • Over / Under 2.5: model leaned Over 2.5; match finished Under 2.5 (2 goals)

Market lesson

The closing market differed from the model on Tanzania by 7.4 percentage points (31.1% vs model 38.5%) — in this case the market view proved closer.

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Prediction Timeline

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

  1. Sep 25, 2026 · 12:59 UTC Forecast generated
    • Model 1X2 · Tanzania 38.5% · Draw 29.6% · Guinea-Bissau 31.9%
    • xG · Tanzania 1.37 — Guinea-Bissau 1.23
  2. Sep 25, 2026 · 12:29 UTC Opening odds snapshot PRE30
    • 1X2 odds · Tanzania 2.22 · Draw 2.84 · Guinea-Bissau 3.83
    • Implied 1X2 · Tanzania 42.4% · Draw 33.1% · Guinea-Bissau 24.6%
    • Bookmaker · Pinnacle
  3. Sep 25, 2026 · 12:59 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Tanzania 2.22 · Draw 2.84 · Guinea-Bissau 3.83
    • Implied 1X2 · Tanzania 42.4% · Draw 33.1% · Guinea-Bissau 24.6%
    • Bookmaker · Pinnacle
  4. Sep 25, 2026 · 13:00 UTC Kickoff
  5. FT Full-time result Guinea-Bissau win · 0–2
  6. FT Prediction missed 1X2 lean did not match full-time result
  7. 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 Missed
Pre-match metrics (historical context)
Prediction Reliability 75/100 · High
  • Validation: Pass
Evidence ★★★★★
  • No strong statistical edge
  • Direction agrees with model lean
  • Validation passed
Pricing proximity (inverse gap) 63/100
Betting Confidence 78/100

Validation Report

Immutable Snapshot

Prediction Time: Sep 19, 2026 · 00:47 UTC Snapshot ID: dp-9561476

Closing Odds 3.83
AI Fair Odds —
CLV Pending
Final Result Guinea-Bissau win · Tanzania 0–2 Guinea-Bissau
Prediction ✖ Missed
Decision Grade F

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: Africa Cup of Nations - Qualification
  • Fixture: Tanzania vs Guinea-Bissau
  • Kickoff: 2026-09-25 13:00:00
  • 1X2 (model): Home 38.5% · Draw 29.6% · Away 31.9%
  • xG (showing): Tanzania 1.37 — Guinea-Bissau 1.23 (total xG ≈ 2.6)
  • Primary / headline line (Betting Primary Pick when shown): BTTS Yes
  • Model: 54.4% · Implied: 44.2% · Probability edge: +10.2 pts · Est. EV: +19.7%
  • BTTS (model): Yes 54.4% · No 45.6%
  • Correct score (top bin): 1-1 (12.5%)

Use the cards for tiering; this text only restates the same inputs in narrative form.

1X2 can look balanced even when side markets show clearer structure.

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 30, 2026 (UTC)

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