Predictions / Football / India. Calcutta Premier Division / Coal India vs Police

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

⚽
Coal India
Aug 21, 2026 - 09:30
1 1.24
1 1.36
xG Accuracy: 85%
Police Police

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

The model had projected Police at 38.0%, 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 Police Draw ✖ Incorrect
  • Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 1-1 ✔ Correct

Model vs Closing Market

Moderate Disagreement

The model rates Police considerably stronger than the closing betting market.

Largest probability gap: Police +5.7 pp

Outcome Model Closing Market Difference Signal
Coal India 32.4% 36.9% -4.5 pp Aligned
Draw 29.6% 30.8% -1.2 pp Aligned
Police 38.0% 32.3% +5.7 pp Model Higher

The statistical model estimates Police's win probability at 38.0%, compared with the closing market's implied probability of 32.3%, a difference of 5.7 percentage points. This highlights a substantial disagreement between the model's assessment and the market consensus, rather than 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 fair estimate shows a modest edge over current market pricing on Police.

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

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 Police; match finished Draw

Market lesson

The closing market differed from the model on Police by 5.7 percentage points (32.3% vs model 38.0%) — 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 · 09:29 UTC Forecast generated
    • Model 1X2 · Coal India 32.4% · Draw 29.6% · Police 38.0%
    • xG · Coal India 1.24 — Police 1.36
  2. Aug 21, 2026 · 08:59 UTC Opening odds snapshot PRE30
    • 1X2 odds · Coal India 2.41 · Draw 2.89 · Police 2.75
    • Implied 1X2 · Coal India 36.9% · Draw 30.8% · Police 32.3%
    • Bookmaker · Pinnacle
  3. Aug 21, 2026 · 09:29 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Coal India 2.41 · Draw 2.89 · Police 2.75
    • Implied 1X2 · Coal India 36.9% · Draw 30.8% · Police 32.3%
    • Bookmaker · Pinnacle
  4. Aug 21, 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 76/100 · High
  • Validation: Pass
Evidence ★★★★★
  • No strong statistical edge
  • Direction agrees with model lean
  • Validation passed
Market Compatibility 24/100
Monitoring Confidence 34/100

Validation Report

Immutable Snapshot

Prediction Time: Aug 16, 2026 · 00:33 UTC Snapshot ID: dp-4207455

Closing Odds 2.75
AI Fair Odds —
CLV Pending
Final Result Draw · Coal India 1–1 Police
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

Below is a compact, numbers-first snapshot aligned with the same engine as the cards above.

  • League: Calcutta Premier Division
  • Fixture: Coal India vs Police
  • Kickoff: 2026-08-21 09:30:00
  • 1X2 (model): Home 32.4% · Draw 29.6% · Away 38.0%
  • xG (showing): Coal India 1.24 — Police 1.36 (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%)

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.

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

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 30, 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