Predictions / Football / World. Africa Cup of Nations - Qualification / Libya vs Botswana

Prediction Audit: Libya vs Botswana Prediction, Odds & AI Betting Tips

Libya Libya
Sep 24, 2026 - 16:00
2 1.39
2 1.21
xG Accuracy: 68%
Botswana Botswana

The model missed the final outcome (Draw 2–2).

The model had projected Libya at 39.5%, but the full-time result went the other way.

Tracked markets vs full-time result

Prediction grade C

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

  • Market Prediction Result Outcome
  • Over / Under 2.5 Over 2.5 Over 2.5 (4 goals) ✔ Correct
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 Libya Draw ✖ Incorrect
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 2-2 ✖ Incorrect

Model vs Closing Market

Strong Disagreement

The closing market prices Libya higher than the statistical model.

Largest probability gap: Libya -20.0 pp

Outcome Model Closing Market Difference Signal
Libya 39.5% 59.4% -20.0 pp Market Higher
Draw 29.5% 26.3% +3.2 pp Aligned
Botswana 31.0% 14.2% +16.8 pp Model Edge

The closing market estimates Libya's win probability at 59.4%, compared with the model's estimate of 39.5%, a difference of 20.0 percentage points. This highlights a disagreement between the model and market consensus, without 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 Draw 2–2.

Market Assessment

The market is materially more optimistic about Libya than the current fair estimate.

  • Investors may be incorporating information not fully reflected in the baseline model.
  • Tournament-specific context can shift market pricing.

Post Match Insights

What worked

  • Expected goals projected a high-scoring match (ΣxG 2.60) — 4 goals materialised
  • Both Teams To Score (Yes) matched the full-time result
  • Over 2.5 goals aligned with the xG profile

What failed

  • 1X2: model leaned Libya; match finished Draw
  • Exact score: outside the model's top score bins

Market lesson

The closing market differed from the model on Libya by 20.0 percentage points (59.5% vs model 39.5%) — 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 24, 2026 · 15:59 UTC Forecast generated
    • Model 1X2 · Libya 39.5% · Draw 29.5% · Botswana 31.0%
    • xG · Libya 1.39 — Botswana 1.21
  2. Sep 24, 2026 · 15:29 UTC Opening odds snapshot PRE30
    • 1X2 odds · Libya 1.56 · Draw 3.52 · Botswana 6.52
    • Implied 1X2 · Libya 59.4% · Draw 26.3% · Botswana 14.2%
    • Bookmaker · Pinnacle
  3. Sep 24, 2026 · 15:59 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Libya 1.56 · Draw 3.52 · Botswana 6.52
    • Implied 1X2 · Libya 59.4% · Draw 26.3% · Botswana 14.2%
    • Bookmaker · Pinnacle
  4. Sep 24, 2026 · 16:00 UTC Kickoff
  5. FT Full-time result Draw · 2–2
  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: Monitor
Historical Decision Monitor
Outcome Missed
Pre-match metrics (historical context)
Prediction Reliability 53/100 · Moderate
  • Validation: Warning
  • Large market gap (20 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Pricing remains divergent
  • Validation warning
Pricing proximity (inverse gap) 0/100
Betting Confidence 42/100

Validation Report

Immutable Snapshot

Prediction Time: Sep 18, 2026 · 01:55 UTC Snapshot ID: dp-9339937

Closing Odds 1.56
AI Fair Odds —
CLV Pending
Final Result Draw · Libya 2–2 Botswana
Prediction ✖ Missed
Decision Grade C

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

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

  • League: Africa Cup of Nations - Qualification
  • Fixture: Libya vs Botswana
  • Kickoff: 2026-09-24 16:00:00
  • 1X2 (model): Home 39.5% · Draw 29.5% · Away 31.0%
  • xG (showing): Libya 1.39 — Botswana 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): Structural lean (model): O/U 2.5 Over 2.5 (Under 2.5 51.8% · Over 2.5 48.2%); BTTS Yes (Yes 54.3% · No 45.7%) Value lean (pricing): O/U 2.5 Over 2.5; BTTS Yes
  • BTTS (model): Yes 54.3% · No 45.7%
  • Correct score (top bin): 1-1 (12.5%)

Saying “no value” on a snapshot is a feature, not a bug: it protects readers from forcing a play when the edge is not there.

Prefer skipping to over-staking when the engine is honest about missing edge.

Historical Recommendation

Historical Decision: Monitor

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 25, 2026 (UTC)

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