Statistics / Football / Poland. Ekstraklasa / Slask Wroclaw vs Korona Kielce

Slask Wroclaw vs Korona Kielce Statistics & Analysis

Sep 12, 2026 - 12:45
1 1.57
2 1.22
xG Accuracy: 69%
Premium betting site stake: New users can use the promo code FHn2uDc1 to receive $100 cash.

Tracked markets vs full-time result

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 No Yes ✖ Incorrect
  • 1X2 Slask Wroclaw Korona Kielce ✖ Incorrect
  • Correct Score Insights 1-1, 1-0, 2-1, 2-0, 0-1 1-2 ✖ Incorrect

Validation Report

Immutable Snapshot

Prediction Time: Sep 07, 2026 · 01:17 UTC Snapshot ID: dp-7430578

Closing Odds 2.83
AI Fair Odds —
CLV +0.0%
Final Result Korona Kielce win · Slask Wroclaw 1–2 Korona Kielce
Prediction ✖ Missed
Decision Grade F

Model Performance

This prediction contributes to:

  • Primary Bets ROI (180d): -100.0%

Market intelligence

Supporting read on how the prioritized closing feed moved versus the model — use after the Primary pick above.

Market briefing

Market remained largely stable before kickoff. No meaningful late implied-price shift was detected between PRE30 and PRE1 on the prioritized bookmaker snapshot.

Despite limited late movement, the model still prices Slask Wroclaw (1X2) meaningfully above what those closing snapshots implied — that gap is a static “model vs. price” read, not a late steam or chase story.

The model still exceeds closing implied on Slask Wroclaw (1X2) by about 9.9 percentage points — the clearest mispricing signal summarized on this page.

Model vs. closing implied

Market Model % Closing impl. % Gap (pp)
Slask Wroclaw (1X2) 43.9 34.0 +9.9
Draw (1X2) 28.0 28.1 -0.1
Korona Kielce (1X2) 28.1 37.9 -9.8
Over 2.5 goals 52.8 51.9 +0.9
Under 2.5 goals 47.2 48.1 -0.9
What this means

In plain terms: the model lands near 43.9% on Slask Wroclaw (1X2), while the closing snapshot implied about 34.0%. The difference — about 9.9 percentage points — is the largest model-vs.-market gap highlighted on this page.

Quick definitions: “closing implied” is the probability for that outcome implied by the final captured odds (after a simple de-vig). “Gap (pp)” is the model percentage minus that implied value, in percentage points (pp).

Closing-window line move

Single prioritized bookmaker per snapshot (not all books). Capture path: PRE30 → PRE1 · Book: Pinnacle

Column tags in parentheses: Closing uses the first available snapshot in PRE1→PRE5→PRE10→PRE30; Early uses the first available in PRE30→PRE10→PRE5 that is not the same capture as Closing.

Detailed capture odds are folded below — movement was negligible on de-vig implied prices.

View full line-by-line capture table
Market Early (PRE30) Closing (PRE1) Implied Δ (pp)
Slask Wroclaw (1X2) 2.83 2.83 0.0
Draw (1X2) 3.43 3.43 0.0
Korona Kielce (1X2) 2.54 2.54 0.0
Over 2.5 goals 1.86 1.86 0.0
Under 2.5 goals 2.01 2.01 0.0

AI match briefing

AI Match Summary

Quick read on how the model reads this matchup.

  • League: Ekstraklasa
  • Fixture: Slask Wroclaw vs Korona Kielce
  • Kickoff: 2026-09-12 12:45:00
  • 1X2 (model): Home 43.9% · Draw 28.0% · Away 28.1%
  • xG (showing): Slask Wroclaw 1.57 — Korona Kielce 1.22 (total xG ≈ 2.79)
  • Best +EV line (same label as hero card when Primary thresholds are not met): Slask Wroclaw
  • Model: 43.9% · Implied: 34.0% · Probability edge: +9.9 pts · Est. EV: +7.0%
  • BTTS (model): Yes 57.3% · No 42.7%
  • Correct score (top bin): 1-1 (11.8%)

Totals and BTTS are evaluated against current market prices where available.

1X2 can look balanced even when side markets show clearer structure.

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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Back to Statistics
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