Prediction Audit: Firpo vs LD Alajuelense Prediction, Odds & AI Betting Tips

Aug 21, 2026 - 03:00
1 1.23
0 1.37
xG Accuracy: 64%

The model missed the final outcome (Firpo win 1–0).

The model had projected LD Alajuelense 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 Under 2.5 Under 2.5 (1 goals) ✔ Correct
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 LD Alajuelense Firpo ✖ Incorrect
  • Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 1-0 ✔ Correct

Model vs Closing Market

Moderate Disagreement

The closing market prices LD Alajuelense higher than the statistical model.

Largest probability gap: LD Alajuelense -5.2 pp

Outcome Model Closing Market Difference Signal
Firpo 31.9% 28.2% +3.8 pp Aligned
Draw 29.6% 28.1% +1.5 pp Aligned
LD Alajuelense 38.5% 43.7% -5.2 pp Market Higher

The closing market estimates LD Alajuelense's win probability at 43.7%, compared with the model's estimate of 38.5%, a difference of 5.2 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 Firpo win 1–0.

Market Assessment

The market and model broadly agree on LD Alajuelense. The remaining divergence may reflect differences in team-strength assumptions rather than a directional disagreement.

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

Post Match Insights

What worked

  • Under 2.5 goals aligned with the xG profile
  • Exact score 1–0 fell within the model's highlighted bins

What failed

  • Both Teams To Score: model leaned BTTS Yes; match finished BTTS No
  • 1X2: model leaned LD Alajuelense; match finished Firpo

Market lesson

The closing market differed from the model on LD Alajuelense by 5.2 percentage points (43.7% 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. Aug 21, 2026 · 02:59 UTC Forecast generated
    • Model 1X2 · Firpo 31.9% · Draw 29.6% · LD Alajuelense 38.5%
    • xG · Firpo 1.23 — LD Alajuelense 1.37
  2. Aug 21, 2026 · 02:29 UTC Opening odds snapshot PRE30
    • 1X2 odds · Firpo 3.21 · Draw 3.22 · LD Alajuelense 2.07
    • Implied 1X2 · Firpo 28.2% · Draw 28.1% · LD Alajuelense 43.7%
    • Bookmaker · Pinnacle
  3. Aug 21, 2026 · 02:59 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Firpo 3.21 · Draw 3.22 · LD Alajuelense 2.07
    • Implied 1X2 · Firpo 28.2% · Draw 28.1% · LD Alajuelense 43.7%
    • Bookmaker · Pinnacle
  4. Aug 21, 2026 · 03:00 UTC Kickoff
  5. FT Full-time result Firpo win · 1–0
  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 76/100 · High
  • Validation: Pass
Evidence ★★★★★
  • No strong statistical edge
  • Direction agrees with model lean
  • Validation passed
Market Compatibility 73/100
Betting Confidence 79/100

Validation Report

Immutable Snapshot

Prediction Time: Aug 15, 2026 · 00:54 UTC Snapshot ID: dp-4018335

Closing Odds 2.07
AI Fair Odds —
CLV Pending
Final Result Firpo win · Firpo 1–0 LD Alajuelense
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: CONCACAF Central American Cup
  • Fixture: Firpo vs LD Alajuelense
  • Kickoff: 2026-08-21 03:00:00
  • 1X2 (model): Home 31.9% · Draw 29.6% · Away 38.5%
  • xG (showing): Firpo 1.23 — LD Alajuelense 1.37 (total xG ≈ 2.6)
  • Value headline: None — no positive EV on tracked lines at current best prices (same as the decision block: no default bet).
  • 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 54.4% · No 45.6%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes
  • BTTS (model): Yes 54.4% · No 45.6%
  • Correct score (top bin): 1-1 (12.5%)

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: 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 29, 2026 (UTC)

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