Predictions / Football / Poland. Ekstraklasa / Slask Wroclaw vs Raków Częstochowa

Prediction Audit: Slask Wroclaw vs Raków Częstochowa Prediction, Odds & AI Betting Tips

Aug 02, 2026 - 15:30
2 1.40
1 1.70
xG Accuracy: 70%

The model missed the final outcome (Slask Wroclaw win 2–1).

The model had projected Raków Częstochowa at 41.8%, 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 Over 2.5 Over 2.5 (3 goals) ✔ Correct
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 Raków Częstochowa Slask Wroclaw ✖ Incorrect
  • Correct Score Insights 1-1, 1-2, 0-1, 2-1, 0-2 2-1 ✔ Correct

Model vs Closing Market

Broadly Aligned

The model and closing market are broadly aligned.

Largest probability gap: Raków Częstochowa +1.5 pp

Outcome Model Closing Market Difference Signal
Slask Wroclaw 31.3% 31.9% -0.6 pp Aligned
Draw 26.9% 27.8% -0.9 pp Aligned
Raków Częstochowa 41.8% 40.3% +1.5 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 result was Slask Wroclaw win 2–1.

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 3.10) — 3 goals materialised
  • Both Teams To Score (Yes) matched the full-time result
  • Over 2.5 goals aligned with the xG profile

What failed

  • 1X2: model leaned Raków Częstochowa; match finished Slask Wroclaw

Market lesson

The full-time result was Slask Wroclaw win 2–1, which did not match the model's pre-match lean on 1X2.

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Prediction Timeline

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

  1. Aug 02, 2026 · 19:18 UTC Forecast generated
    • Model 1X2 · Slask Wroclaw 31.3% · Draw 26.9% · Raków Częstochowa 41.8%
    • xG · Slask Wroclaw 1.40 — Raków Częstochowa 1.70
  2. Aug 02, 2026 · 15:03 UTC Opening odds snapshot PRE30
    • 1X2 odds · Slask Wroclaw 3.02 · Draw 3.47 · Raków Częstochowa 2.39
    • Implied 1X2 · Slask Wroclaw 31.9% · Draw 27.8% · Raków Częstochowa 40.3%
    • Bookmaker · Pinnacle
  3. Aug 02, 2026 · 15:29 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Slask Wroclaw 3.02 · Draw 3.47 · Raków Częstochowa 2.39
    • Implied 1X2 · Slask Wroclaw 31.9% · Draw 27.8% · Raków Częstochowa 40.3%
    • Bookmaker · Pinnacle
  4. Aug 02, 2026 · 15:30 UTC Kickoff
  5. FT Full-time result Slask Wroclaw win · 2–1
  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: Observe
Historical Decision No Primary Bet
Outcome Missed
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 92/100
Betting Confidence 81/100

Validation Report

Immutable Snapshot

Prediction Time: Jul 27, 2026 · 01:36 UTC Snapshot ID: dp-1951251

Closing Odds 2.39
AI Fair Odds —
CLV Pending
Final Result Slask Wroclaw win · Slask Wroclaw 2–1 Raków Częstochowa
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: Ekstraklasa
  • Fixture: Slask Wroclaw vs Raków Częstochowa
  • Kickoff: 2026-08-02 15:30:00
  • 1X2 (model): Home 10.0% · Draw 45.0% · Away 45.0%
  • xG (showing): Slask Wroclaw 1.4 — Raków Częstochowa 1.7 (total xG ≈ 3.1)
  • 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

Saying “no value” on a snapshot is a feature, not a bug: it protects readers from forcing a play when the edge is not there.

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

Historical Recommendation

Historical Decision: No Primary Bet

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 29, 2026 (UTC)

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Ekstraklasa Ekstraklasa — Standings
# TEAM MP W D L PTS
1 Gornik Zabrze 9 7 1 1 22
2 Legia Warszawa 9 5 4 0 19
3 Lech Poznan 8 6 1 1 19
4 Wisla Krakow 9 5 2 2 17
5 Pogon Szczecin 8 4 3 1 15
6 Korona Kielce 9 4 3 2 15
7 Zaglebie Lubin 9 4 3 2 15
8 Piast Gliwice 9 4 1 4 13
9 GKS Katowice 8 4 0 4 12
10 Jagiellonia 8 4 0 4 12
11 Wisla Plock 8 3 2 3 11
12 Widzew Łódź 9 1 6 2 9
13 Cracovia Krakow 9 2 2 5 8
14 Radomiak Radom 9 2 2 5 8
15 Slask Wroclaw 9 1 3 5 6
16 Motor Lublin 9 1 3 5 6
17 Wieczysta Kraków 8 1 2 5 5
18 Raków Częstochowa 9 1 0 8 3
# TEAM MP GS GC +/- PTS
1 Legia Warszawa 9 19 8 +11 19
2 Lech Poznan 8 17 7 +10 19
3 Wisla Krakow 9 17 12 +5 17
4 Gornik Zabrze 9 16 8 +8 22
5 GKS Katowice 8 16 13 +3 12
6 Piast Gliwice 9 16 15 +1 13
7 Widzew Łódź 9 13 13 0 9
8 Pogon Szczecin 8 12 6 +6 15
9 Korona Kielce 9 12 10 +2 15
10 Jagiellonia 8 12 13 -1 12
11 Raków Częstochowa 9 12 21 -9 3
12 Zaglebie Lubin 9 11 10 +1 15
13 Slask Wroclaw 9 11 15 -4 6
14 Wieczysta Kraków 8 11 17 -6 5
15 Wisla Plock 8 9 12 -3 11
16 Cracovia Krakow 9 9 14 -5 8
17 Motor Lublin 9 9 15 -6 6
18 Radomiak Radom 9 7 20 -13 8
# TEAM MP xG xGC +/- PTS
1 Lech Poznan 8 10.4 4.1 +6.3 19
2 Wisla Krakow 9 12.0 7.9 +4.1 17
3 Legia Warszawa 9 9.9 6.0 +3.9 19
4 Cracovia Krakow 9 10.4 7.1 +3.3 8
5 Gornik Zabrze 9 10.0 7.7 +2.3 22
6 Jagiellonia 8 8.9 6.9 +2.0 12
7 Zaglebie Lubin 9 8.4 8.2 +0.2 15
8 Widzew Łódź 9 9.8 9.7 +0.1 9
9 Slask Wroclaw 9 10.5 10.6 -0.1 6
10 Wieczysta Kraków 8 9.1 9.6 -0.5 5
11 Motor Lublin 9 8.7 9.2 -0.5 6
12 Pogon Szczecin 8 8.1 8.9 -0.8 15
13 Wisla Plock 8 9.6 10.8 -1.2 11
14 GKS Katowice 8 8.8 10.6 -1.8 12
15 Korona Kielce 9 5.4 8.7 -3.3 15
16 Piast Gliwice 9 7.3 10.8 -3.5 13
17 Radomiak Radom 9 7.4 11.2 -3.8 8
18 Raków Częstochowa 9 9.9 16.5 -6.6 3