Predictions / Football / Poland. I Liga / Slask Wroclaw vs Pogoń Grod. Mazowiecki

Prediction Audit: Slask Wroclaw vs Pogoń Grod. Mazowiecki Prediction, Odds & AI Betting Tips

Slask Wroclaw Slask Wroclaw
May 24, 2026 - 14:30
0 1.45
0 1.25
xG Accuracy: 48%
Pogoń Grod. Mazowiecki Pogoń Grod. Mazowiecki

The model missed the final outcome (Draw 0–0).

The model had projected Slask Wroclaw at 41.8%, but the full-time result went the other way.

Tracked markets vs full-time result

Prediction grade F

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 (0 goals) ✔ Correct
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 Slask Wroclaw Draw ✖ Incorrect
  • Correct Score Insights 1-1, 2-1, 1-2, 2-2, 1-0 0-0 ✖ Incorrect

Model vs Closing Market

Strong Disagreement

The closing market prices Slask Wroclaw higher than the statistical model.

Largest probability gap: Slask Wroclaw -18.7 pp

Outcome Model Closing Market Difference Signal
Slask Wroclaw 41.8% 60.5% -18.7 pp Market Higher
Draw 25.7% 20.1% +5.6 pp Model Higher
Pogoń Grod. Mazowiecki 32.6% 19.4% +13.1 pp Model Edge

The closing market estimates Slask Wroclaw's win probability at 60.5%, compared with the model's estimate of 41.8%, a difference of 18.7 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: PRE5.

After full time, the result was Draw 0–0.

Market Assessment

The market is materially more optimistic about Slask Wroclaw 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

  • Under 2.5 goals aligned with the xG profile

What failed

  • Both Teams To Score: model leaned BTTS Yes; match finished BTTS No
  • 1X2: model leaned Slask Wroclaw; match finished Draw

Market lesson

The closing market differed from the model on Slask Wroclaw by 18.7 percentage points (60.5% vs model 41.8%) — 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. May 23, 2026 · 19:28 UTC Forecast generated
    • Model 1X2 · Slask Wroclaw 41.8% · Draw 25.7% · Pogoń Grod. Mazowiecki 32.6%
    • xG · Slask Wroclaw 1.45 — Pogoń Grod. Mazowiecki 1.25
  2. May 23, 2026 · 14:30 UTC Opening odds snapshot PRE30
    • 1X2 odds · Slask Wroclaw 1.53 · Draw 4.61 · Pogoń Grod. Mazowiecki 4.76
    • Implied 1X2 · Slask Wroclaw 60.5% · Draw 20.1% · Pogoń Grod. Mazowiecki 19.4%
    • Bookmaker · Pinnacle
  3. May 23, 2026 · 14:56 UTC Closing snapshot recorded PRE5
    • 1X2 odds · Slask Wroclaw 1.53 · Draw 4.61 · Pogoń Grod. Mazowiecki 4.76
    • Implied 1X2 · Slask Wroclaw 60.5% · Draw 20.1% · Pogoń Grod. Mazowiecki 19.4%
    • Bookmaker · Pinnacle
  4. May 24, 2026 · 14:30 UTC Kickoff
  5. FT Full-time result Draw · 0–0
  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 54/100 · Moderate
  • Validation: Warning
  • Large market gap (19 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Pricing remains divergent
  • Validation warning
Pricing proximity (inverse gap) 6/100
Betting Confidence 43/100

Validation Report

Immutable Snapshot

Prediction Time: Aug 09, 2026 · 14:23 UTC Snapshot ID: dp-3435300

Closing Odds 1.53
AI Fair Odds —
CLV Pending
Final Result Draw · Slask Wroclaw 0–0 Pogoń Grod. Mazowiecki
Prediction ✖ Missed
Decision Grade F

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: I Liga
  • Fixture: Slask Wroclaw vs Pogoń Grod. Mazowiecki
  • Kickoff: 2026-05-23 15:00:00
  • 1X2 (model): Home 41.8% · Draw 25.7% · Away 32.6%
  • xG (showing): Slask Wroclaw 1.45 — Pogoń Grod. Mazowiecki 1.25 (total xG ≈ 2.7)
  • 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 Over 2.5 (Under 2.5 34.9% · Over 2.5 65.1%); BTTS Yes (Yes 76.3% · No 23.7%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes
  • BTTS (model): Yes 76.3% · No 23.7%
  • Correct score (top bin): 1-1 (9.7%)

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

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