Prediction Audit: Coal India vs Measurers Prediction, Odds & AI Betting Tips

Aug 08, 2026 - 09:30
1 1.43
1 1.17
xG Accuracy: 85%

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

The model had projected Coal India at 41.4%, 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 Coal India Draw ✖ Incorrect
  • Correct Score Insights 1-1, 1-0, 2-1, 0-1, 2-0 1-1 ✔ Correct

Model vs Closing Market

Strong Disagreement

The closing market prices Coal India higher than the statistical model.

Largest probability gap: Coal India -19.7 pp

Outcome Model Closing Market Difference Signal
Coal India 41.4% 61.1% -19.7 pp Market Higher
Draw 29.4% 23.1% +6.3 pp Model Higher
Measurers 29.2% 15.8% +13.4 pp Model Edge

The closing market estimates Coal India's win probability at 61.1%, compared with the model's estimate of 41.4%, a difference of 19.7 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.

Market Assessment

The market is materially more optimistic about Coal India 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

  • 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 Coal India; match finished Draw

Market lesson

The closing market differed from the model on Coal India by 19.7 percentage points (61.1% vs model 41.4%) — 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 08, 2026 · 09:29 UTC Forecast generated
    • Model 1X2 · Coal India 41.4% · Draw 29.4% · Measurers 29.3%
    • xG · Coal India 1.43 — Measurers 1.17
  2. Aug 08, 2026 · 09:00 UTC Opening odds snapshot PRE30
    • 1X2 odds · Coal India 1.45 · Draw 3.84 · Measurers 5.61
    • Implied 1X2 · Coal India 61.1% · Draw 23.1% · Measurers 15.8%
    • Bookmaker · Pinnacle
  3. Aug 08, 2026 · 09:29 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Coal India 1.45 · Draw 3.84 · Measurers 5.61
    • Implied 1X2 · Coal India 61.1% · Draw 23.1% · Measurers 15.8%
    • Bookmaker · Pinnacle
  4. Aug 08, 2026 · 09:30 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: 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) 1/100
Betting Confidence 42/100

Validation Report

Immutable Snapshot

Prediction Time: Aug 07, 2026 · 01:40 UTC Snapshot ID: dp-3152029

Closing Odds 1.45
AI Fair Odds —
CLV Pending
Final Result Draw · Coal India 1–1 Measurers
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: Calcutta Premier Division
  • Fixture: Coal India vs Measurers
  • Kickoff: 2026-08-08 09:30:00
  • 1X2 (model): Home 41.4% · Draw 29.4% · Away 29.3%
  • xG (showing): Coal India 1.43 — Measurers 1.17 (total xG ≈ 2.6)
  • Value headline: None (actionable) — best tracked EV is about +0.7%, 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 54.1% · No 45.9%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes
  • BTTS (model): Yes 54.1% · No 45.9%
  • Correct score (top bin): 1-1 (12.4%)

The decision block shows no default Primary: Primary needs consensus EV ≥ +5.0% plus strength/reliability/calibration gates. A separate Lean/tracked gate is +2.0% (selective only). Lean labels are directional only — not bankroll-sized recommendations.

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 28, 2026 (UTC)

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Calcutta Premier Division Calcutta Premier Division — Standings
# TEAM MP W D L PTS
1 East Bengal 14 9 5 0 32
2 Bhawanipore 14 9 4 1 31
3 Mohun Bagan 14 9 3 2 30
4 Mohammedan 14 7 4 3 25
5 United 14 6 5 3 23
6 Coal India 14 6 4 4 22
7 Peerless 11 6 2 3 20
8 Aryan 11 5 4 2 19
9 Calcutta Customs 11 5 3 3 18
10 Calcutta Police 11 5 3 3 18
11 Police 11 4 5 2 17
12 United Kolkata 11 4 4 3 16
13 Measurers 11 3 6 2 15
14 Kalighat 11 4 2 5 14
15 Railway 11 4 2 5 14
16 Kidderpore 11 2 6 3 12
17 BSS Sporting 11 3 3 5 12
18 Patha Chakra 11 3 1 7 10
19 NA Suruchi Sangha 11 2 3 6 9
20 Rainbow 11 2 1 8 7
21 Wari 11 1 4 6 7
22 George Telegraph 11 2 1 8 7
23 Kalighat Club 11 0 3 8 3
24 Bidhannagar 11 0 2 9 2
# TEAM MP GS GC +/- PTS
1 East Bengal 14 35 8 +27 32
2 Mohun Bagan 14 35 10 +25 30
3 United 14 25 10 +15 23
4 Bhawanipore 14 24 7 +17 31
5 Calcutta Customs 11 24 12 +12 18
6 Mohammedan 14 23 16 +7 25
7 United Kolkata 11 22 16 +6 16
8 Measurers 11 21 17 +4 15
9 Peerless 11 20 9 +11 20
10 Railway 11 20 20 0 14
11 Coal India 14 19 22 -3 22
12 Aryan 11 18 6 +12 19
13 Kalighat 11 18 13 +5 14
14 BSS Sporting 11 17 21 -4 12
15 Kidderpore 11 15 18 -3 12
16 Calcutta Police 11 13 11 +2 18
17 Police 11 13 11 +2 17
18 Rainbow 11 13 31 -18 7
19 Patha Chakra 11 12 32 -20 10
20 NA Suruchi Sangha 11 11 20 -9 9
21 Wari 11 9 28 -19 7
22 George Telegraph 11 7 33 -26 7
23 Bidhannagar 11 5 31 -26 2
24 Kalighat Club 11 4 21 -17 3