Predictions / Football / Scotland. League Cup / Ross County vs Clyde

Prediction Audit: Ross County vs Clyde Prediction, Odds & AI Betting Tips

Jul 18, 2026 - 14:00
3 1.36
1 1.24
xG Accuracy: 60%

AI correctly predicted the Ross County win.

The match finished 3–1, validating the model's directional assessment.

Tracked markets vs full-time result

Prediction grade B-

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 (4 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 Ross County Ross County ✔ Correct
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 3-1 ✖ Incorrect

Model vs Closing Market

Strong Disagreement

The closing market prices Ross County higher than the statistical model.

Largest probability gap: Ross County -21.5 pp

Outcome Model Closing Market Difference Signal
Ross County 46.4% 67.9% -21.5 pp Market Higher
Draw 27.4% 18.7% +8.7 pp Model Higher
Clyde 26.2% 13.4% +12.8 pp Model Edge

The closing market estimates Ross County's win probability at 67.9%, compared with the model's estimate of 46.4%, a difference of 21.5 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: PRE10.

After full time, the model's directional lean matched the result (Ross County win 3–1).

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

What failed

  • Over / Under 2.5: model leaned Under 2.5; match finished Over 2.5 (4 goals)
  • Exact score: outside the model's top score bins

Market lesson

Large model–market gaps do not automatically mean the market is right. Here the closing market priced Ross County higher (67.9% vs model 46.4%, 21.5 pp), but the model's lean was validated (Ross County win 3–1).

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Prediction Timeline

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

  1. Jul 18, 2026 · 20:28 UTC Forecast generated
    • Model 1X2 · Ross County 46.5% · Draw 27.4% · Clyde 26.2%
    • xG · Ross County 1.36 — Clyde 1.24
  2. Jul 18, 2026 · 13:42 UTC Opening odds snapshot PRE30
    • 1X2 odds · Ross County 1.35 · Draw 4.91 · Clyde 6.85
    • Implied 1X2 · Ross County 67.9% · Draw 18.7% · Clyde 13.4%
    • Bookmaker · Pinnacle
  3. Jul 18, 2026 · 13:59 UTC Closing snapshot recorded PRE10
    • 1X2 odds · Ross County 1.35 · Draw 4.91 · Clyde 6.85
    • Implied 1X2 · Ross County 67.9% · Draw 18.7% · Clyde 13.4%
    • Bookmaker · Pinnacle
  4. Jul 18, 2026 · 14:00 UTC Kickoff
  5. FT Full-time result Ross County win · 3–1
  6. FT Prediction validated Directional lean matched 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 Validated
Pre-match metrics (historical context)
Prediction Reliability 52/100 · Moderate
  • Validation: Warning
  • Large market gap (22 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 25, 2026 · 22:50 UTC Snapshot ID: dp-1771639

Closing Odds 1.35
AI Fair Odds —
CLV Pending
Final Result Ross County win · Ross County 3–1 Clyde
Prediction ✔ Correct
Decision Grade B-

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: Scottish League Cup
  • Fixture: Ross County vs Clyde
  • Kickoff: 2026-07-18 14:00:00
  • 1X2 (model): Home 35.0% · Draw 35.0% · Away 30.0%
  • xG (showing): Ross County 1.36 — Clyde 1.24 (total xG ≈ 2.6)
  • Value headline: None — no positive EV could be estimated on tracked lines at current best prices (missing odds or thin book depth).
  • Structural leans (not bets): See the Over/Under and BTTS cards for any directional lean text.
  • BTTS (model): Yes N/A · No N/A
  • Correct score (top bin): N/A

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.

If lines move materially, re-run generation or refresh — implied probabilities and any future EV readouts will change first.

Historical Recommendation

Historical Decision: Wait

Outcome: Validated — Pre-match lean validated against 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 28, 2026 (UTC)

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