Predictions / Football / Poland. I Liga / Odra Opole vs Pogoń Grod. Mazowiecki

Prediction Audit: Odra Opole vs Pogoń Grod. Mazowiecki Prediction, Odds & AI Betting Tips

Odra Opole Odra Opole
May 11, 2026 - 16:30
3 1.45
1 1.25
xG Accuracy: 61%
Pogoń Grod. Mazowiecki Pogoń Grod. Mazowiecki

AI correctly predicted the Odra Opole 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 Over 2.5 Over 2.5 (4 goals) ✔ Correct
  • Both Teams To Score BTTS No Yes ✖ Incorrect
  • 1X2 Odra Opole Odra Opole ✔ Correct
  • Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 3-1 ✖ Incorrect

Model vs Closing Market

Broadly Aligned

The model and closing market are broadly aligned.

Largest probability gap: Draw -2.8 pp

Outcome Model Closing Market Difference Signal
Odra Opole 41.8% 41.1% +0.7 pp Aligned
Draw 25.7% 28.5% -2.8 pp Aligned
Pogoń Grod. Mazowiecki 32.6% 30.5% +2.1 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 model's directional lean matched the result (Odra Opole win 3–1).

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 2.70) — 4 goals materialised
  • Over 2.5 goals aligned with the xG profile

What failed

  • Both Teams To Score: model leaned BTTS No; match finished BTTS Yes
  • Exact score: outside the model's top score bins

Market lesson

The model's directional lean matched the full-time result (Odra Opole win 3–1).

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Prediction Timeline

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

  1. May 11, 2026 · 16:29 UTC Forecast generated
    • Model 1X2 · Odra Opole 41.8% · Draw 25.7% · Pogoń Grod. Mazowiecki 32.6%
    • xG · Odra Opole 1.45 — Pogoń Grod. Mazowiecki 1.25
  2. May 09, 2026 · 14:31 UTC Opening odds snapshot PRE30
    • 1X2 odds · Odra Opole 2.13 · Draw 3.49 · Pogoń Grod. Mazowiecki 3.21
    • Implied 1X2 · Odra Opole 44.0% · Draw 26.8% · Pogoń Grod. Mazowiecki 29.2%
    • Bookmaker · Pinnacle
  3. May 11, 2026 · 16:29 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Odra Opole 2.32 · Draw 3.35 · Pogoń Grod. Mazowiecki 3.13
    • Implied 1X2 · Odra Opole 41.1% · Draw 28.5% · Pogoń Grod. Mazowiecki 30.5%
    • Bookmaker · Pinnacle
  4. May 11, 2026 · 16:30 UTC Kickoff
  5. FT Full-time result Odra Opole 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: Observe
Historical Decision No Primary Bet
Outcome Validated
Pre-match metrics (historical context)
Prediction Reliability 78/100 · High
  • Validation: Pass
Evidence ★★★★★
  • No strong statistical edge
  • Direction agrees with model lean
  • Validation passed
Market Compatibility 86/100
Betting Confidence 81/100

Validation Report

Immutable Snapshot

Prediction Time: Aug 04, 2026 · 08:44 UTC Snapshot ID: dp-2982542

Closing Odds 3.35
AI Fair Odds —
CLV Pending
Final Result Odra Opole win · Odra Opole 3–1 Pogoń Grod. Mazowiecki
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

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

  • League: I Liga
  • Fixture: Odra Opole vs Pogoń Grod. Mazowiecki
  • Kickoff: 2026-05-11 16:30:00
  • 1X2 (model): Home 41.8% · Draw 25.7% · Away 32.6%
  • xG (showing): Odra Opole 1.45 — Pogoń Grod. Mazowiecki 1.25 (total xG ≈ 2.7)
  • Value headline: None (actionable) — best tracked EV is about +1.8%, 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 50.6% · Over 2.5 49.4%); BTTS Yes (Yes 52.0% · No 48.0%) Value lean (pricing): O/U 2.5 Over 2.5; BTTS No
  • BTTS (model): Yes 52.0% · No 48.0%
  • Correct score (top bin): 1-1 (12.4%)

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: 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

October 02, 2026 (UTC)

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I Liga I Liga — Standings
# TEAM MP W D L PTS
1 Wisla Krakow 34 20 11 3 71
2 Slask Wroclaw 34 17 11 6 62
3 Wieczysta Kraków 34 16 9 9 57
4 Chrobry Głogów 34 16 7 11 55
5 ŁKS Łódź 34 15 9 10 54
6 Polonia Warszawa 34 15 8 11 53
7 Ruch Chorzów 34 14 11 9 53
8 Miedz Legnica 34 15 7 12 52
9 Puszcza Niepołomice 34 12 13 9 49
10 Polonia Bytom 34 13 8 13 47
11 Pogoń Grod. Mazowiecki 34 11 12 11 45
12 Odra Opole 34 11 11 12 44
13 Stal Rzeszów 34 12 7 15 43
14 Stal Mielec 34 10 6 18 36
15 Pogoń Siedlce 34 9 9 16 36
16 Znicz Pruszków 34 7 7 20 28
17 Górnik Łęczna 34 5 12 17 27
18 Tychy 71 34 5 8 21 23
# TEAM MP GS GC +/- PTS
1 Wisla Krakow 34 72 32 +40 71
2 Wieczysta Kraków 34 70 47 +23 57
3 Slask Wroclaw 34 69 47 +22 62
4 ŁKS Łódź 34 56 48 +8 54
5 Polonia Bytom 34 56 50 +6 47
6 Ruch Chorzów 34 54 46 +8 53
7 Polonia Warszawa 34 52 49 +3 53
8 Miedz Legnica 34 52 53 -1 52
9 Pogoń Grod. Mazowiecki 34 51 54 -3 45
10 Stal Mielec 34 51 62 -11 36
11 Stal Rzeszów 34 49 60 -11 43
12 Chrobry Głogów 34 48 36 +12 55
13 Puszcza Niepołomice 34 45 40 +5 49
14 Znicz Pruszków 34 40 68 -28 28
15 Tychy 71 34 40 74 -34 23
16 Górnik Łęczna 34 39 62 -23 27
17 Odra Opole 34 34 40 -6 44
18 Pogoń Siedlce 34 33 43 -10 36