Statistics / Football / Poland. Ekstraklasa / Wisla Plock vs Korona Kielce

Wisla Plock vs Korona Kielce Statistics & Analysis

Wisla Plock Wisla Plock
Aug 28, 2026 - 16:00
0 1.35
2 1.37
xG Accuracy: 58%
Korona Kielce Korona Kielce
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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 Under 2.5 (2 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 Korona Kielce Korona Kielce ✔ Correct
  • Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 0-2 ✖ Incorrect

Validation Report

Immutable Snapshot

Prediction Time: Aug 22, 2026 · 02:37 UTC Snapshot ID: dp-4928503

Closing Odds 2.91
AI Fair Odds —
CLV +0.0%
Final Result Korona Kielce win · Wisla Plock 0–2 Korona Kielce
Prediction ✔ Correct
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 Wisla Plock (1X2), Over 2.5 goals 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 Over 2.5 goals by about 4.6 percentage points — the clearest mispricing signal summarized on this page.

Model vs. closing implied

Market Model % Closing impl. % Gap (pp)
Wisla Plock (1X2) 35.1 33.1 +2.0
Draw (1X2) 28.9 30.1 -1.2
Korona Kielce (1X2) 36.0 36.8 -0.8
Over 2.5 goals 51.1 46.5 +4.6
Under 2.5 goals 48.9 53.5 -4.6
What this means

In plain terms: the model lands near 51.1% on Over 2.5 goals, while the closing snapshot implied about 46.5%. The difference — about 4.6 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)
Wisla Plock (1X2) 2.91 2.91 0.0
Draw (1X2) 3.2 3.2 0.0
Korona Kielce (1X2) 2.62 2.62 0.0
Over 2.5 goals 2.07 2.07 0.0
Under 2.5 goals 1.8 1.8 0.0

AI match briefing

AI Match Summary

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

  • League: Ekstraklasa
  • Fixture: Wisla Plock vs Korona Kielce
  • Kickoff: 2026-08-28 16:00:00
  • 1X2 (model): Home 35.1% · Draw 28.9% · Away 36.0%
  • xG (showing): Wisla Plock 1.35 — Korona Kielce 1.37 (total xG ≈ 2.72)
  • Primary / headline line (Betting Primary Pick when shown): BTTS Yes
  • Model: 56.8% · Implied: 51.3% · Probability edge: +5.5 pts · Est. EV: +8.5%
  • BTTS (model): Yes N/A · No N/A
  • Correct score (top bin): N/A

Use the cards for tiering; this text only restates the same inputs in narrative form.

Early match state can move realised goals away from pre-kick projections.

Historical Recommendation

Historical Decision: 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

September 30, 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