Predictions / Football / World. Leagues Cup / Monterrey vs Chicago Fire

Prediction Audit: Monterrey vs Chicago Fire Prediction, Odds & AI Betting Tips

Monterrey Monterrey
Aug 26, 2026 - 00:30
2 1.28
1 1.32
xG Accuracy: 75%
Chicago Fire Chicago Fire

The model missed the final outcome (Monterrey win 2–1).

The model had projected Chicago Fire at 36.1%, 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 Over 2.5 (3 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 Chicago Fire Monterrey ✖ Incorrect
  • Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 2-1 ✔ Correct

Model vs Closing Market

Broadly Aligned

The model and closing market are broadly aligned.

Largest probability gap: Draw +4.8 pp

Outcome Model Closing Market Difference Signal
Monterrey 34.2% 34.2% -0.0 pp Aligned
Draw 29.6% 24.8% +4.8 pp Aligned
Chicago Fire 36.1% 41.0% -4.8 pp Aligned

The model and closing market are broadly aligned, with probability differences below 5 percentage points.

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 Monterrey win 2–1.

Market Assessment

The market and model are broadly aligned. Any small pricing gap likely reflects rounding or bookmaker margin, not a structural disagreement.

  • Current pricing remains close to the model baseline.

Post Match Insights

What worked

  • Expected goals projected a high-scoring match (ΣxG 2.60) — 3 goals materialised
  • Both Teams To Score (Yes) matched the full-time result
  • Exact score 2–1 fell within the model's highlighted bins

What failed

  • Over / Under 2.5: model leaned Under 2.5; match finished Over 2.5 (3 goals)
  • 1X2: model leaned Chicago Fire; match finished Monterrey

Market lesson

The full-time result was Monterrey win 2–1, which did not match the model's pre-match lean on 1X2.

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Prediction Timeline

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

  1. Aug 26, 2026 · 00:29 UTC Forecast generated
    • Model 1X2 · Monterrey 34.2% · Draw 29.7% · Chicago Fire 36.1%
    • xG · Monterrey 1.28 — Chicago Fire 1.32
  2. Aug 25, 2026 · 23:59 UTC Opening odds snapshot PRE30
    • 1X2 odds · Monterrey 2.81 · Draw 3.88 · Chicago Fire 2.35
    • Implied 1X2 · Monterrey 34.2% · Draw 24.8% · Chicago Fire 41.0%
    • Bookmaker · Pinnacle
  3. Aug 26, 2026 · 00:29 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Monterrey 2.81 · Draw 3.88 · Chicago Fire 2.35
    • Implied 1X2 · Monterrey 34.2% · Draw 24.8% · Chicago Fire 41.0%
    • Bookmaker · Pinnacle
  4. Aug 26, 2026 · 00:30 UTC Kickoff
  5. FT Full-time result Monterrey win · 2–1
  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 77/100 · High
  • Validation: Pass
Evidence ★★★★★
  • No strong statistical edge
  • Direction agrees with model lean
  • Validation passed
Market Compatibility 75/100
Betting Confidence 80/100

Validation Report

Immutable Snapshot

Prediction Time: Aug 20, 2026 · 01:46 UTC Snapshot ID: dp-4671874

Closing Odds 3.88
AI Fair Odds —
CLV Pending
Final Result Monterrey win · Monterrey 2–1 Chicago Fire
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

Pre-match snapshot for this fixture.

  • League: Leagues Cup
  • Fixture: Monterrey vs Chicago Fire
  • Kickoff: 2026-08-26 00:30:00
  • 1X2 (model): Home 34.2% · Draw 29.7% · Away 36.1%
  • xG (showing): Monterrey 1.28 — Chicago Fire 1.32 (total xG ≈ 2.6)
  • Value headline: None (actionable) — best tracked EV is about +1.5%, still below the +2.0% minimum for a headline / default stake (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 54.5% · No 45.5%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes
  • BTTS (model): Yes 54.5% · No 45.5%
  • 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 27, 2026 (UTC)

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