Predictions / Football / World. Friendlies Clubs / Montrose vs Civil Service Strollers

Prediction Audit: Montrose vs Civil Service Strollers Prediction, Odds & AI Betting Tips

Jul 01, 2026 - 18:30
1 1.38
1 1.22
xG Accuracy: 85%

The model missed the final outcome (Draw 1–1).

The model had projected Montrose at 51.2%, 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 Under 2.5 Under 2.5 (2 goals) ✔ Correct
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 Montrose Draw ✖ Incorrect
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 1-1 ✔ Correct

Model vs Closing Market

Strong Disagreement

The closing market prices Montrose higher than the statistical model.

Largest probability gap: Montrose -24.6 pp

Outcome Model Closing Market Difference Signal
Montrose 51.2% 75.8% -24.6 pp Market Higher
Draw 25.5% 14.3% +11.2 pp Model Edge
Civil Service Strollers 23.3% 10.0% +13.3 pp Model Edge

The closing market estimates Montrose's win probability at 75.8%, compared with the model's estimate of 51.2%, a difference of 24.6 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 1–1.

Post Match Insights

What worked

  • Both Teams To Score (Yes) matched the full-time result
  • Under 2.5 goals aligned with the xG profile
  • Exact score 1–1 fell within the model's highlighted bins

What failed

  • 1X2: model leaned Montrose; match finished Draw

Market lesson

The closing market differed from the model on Montrose by 24.6 percentage points (75.8% vs model 51.2%) — 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. Jul 01, 2026 · 19:57 UTC Forecast generated
    • Model 1X2 · Montrose 51.2% · Draw 25.5% · Civil Service Strollers 23.3%
    • xG · Montrose 1.38 — Civil Service Strollers 1.22
  2. Jul 01, 2026 · 17:59 UTC Opening odds snapshot PRE30
    • 1X2 odds · Montrose 1.17 · Draw 6.21 · Civil Service Strollers 8.90
    • Implied 1X2 · Montrose 75.8% · Draw 14.3% · Civil Service Strollers 10.0%
    • Bookmaker · Pinnacle
  3. Jul 01, 2026 · 18:29 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Montrose 1.17 · Draw 6.21 · Civil Service Strollers 8.90
    • Implied 1X2 · Montrose 75.8% · Draw 14.3% · Civil Service Strollers 10.0%
    • Bookmaker · Pinnacle
  4. Jul 01, 2026 · 18:30 UTC Kickoff
  5. FT Full-time result Draw · 1–1
  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: Cautious / Wait

Historical label: Originally displayed as "Wait for validation".

Historical Decision Wait
Outcome Missed
Pre-match metrics (historical context)
Prediction Reliability 51/100 · Moderate
  • Validation: Warning
  • Large market gap (25 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Pricing remains divergent
  • Validation warning
Pricing proximity (inverse gap) 0/100
Betting Confidence 33/100

Validation Report

Immutable Snapshot

Prediction Time: Jul 24, 2026 · 19:30 UTC Snapshot ID: dp-1630616

Closing Odds 1.17
AI Fair Odds —
CLV Pending
Final Result Draw · Montrose 1–1 Civil Service Strollers
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

Quick read on how the model reads this matchup.

  • League: Friendlies Clubs
  • Fixture: Montrose vs Civil Service Strollers
  • Kickoff: 2026-07-01 18:30:00
  • 1X2 (model): Home 51.2% · Draw 25.5% · Away 23.3%
  • xG (showing): Montrose 1.38 — Civil Service Strollers 1.22 (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 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%)

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.

Most likely correct score stays a low-probability tail: use it for context, not as a must-bet story.

Historical Recommendation

Historical Decision: Wait

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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