Predictions / Football / Poland. Ekstraklasa / Wisla Krakow vs Jagiellonia

Prediction Audit: Wisla Krakow vs Jagiellonia Prediction, Odds & AI Betting Tips

Wisla Krakow Wisla Krakow
Sep 11, 2026 - 18:30
2 1.78
0 1.46
xG Accuracy: 63%
Jagiellonia Jagiellonia

AI correctly predicted the Wisla Krakow win.

The match finished 2–0, validating the model's directional assessment.

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 Over 2.5 Under 2.5 (2 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 Wisla Krakow Wisla Krakow ✔ Correct
  • Correct Score Insights 1-1, 2-1, 1-2, 1-0, 2-2 2-0 ✖ Incorrect

Model vs Closing Market

Broadly Aligned

The model and closing market are broadly aligned.

Largest probability gap: Jagiellonia -1.4 pp

Outcome Model Closing Market Difference Signal
Wisla Krakow 44.0% 43.5% +0.5 pp Aligned
Draw 25.6% 24.6% +1.0 pp Aligned
Jagiellonia 30.4% 31.8% -1.4 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 (Wisla Krakow win 2–0).

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 failed

  • Both Teams To Score: model leaned BTTS Yes; match finished BTTS No
  • Over / Under 2.5: model leaned Over 2.5; match finished Under 2.5 (2 goals)

Market lesson

The model's directional lean matched the full-time result (Wisla Krakow win 2–0).

Premium betting site stake: New users can use the promo code FHn2uDc1 to receive $100 cash.

Prediction Timeline

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

  1. Sep 11, 2026 · 18:29 UTC Forecast generated
    • Model 1X2 · Wisla Krakow 44.0% · Draw 25.6% · Jagiellonia 30.4%
    • xG · Wisla Krakow 1.78 — Jagiellonia 1.46
  2. Sep 11, 2026 · 18:02 UTC Opening odds snapshot PRE30
    • 1X2 odds · Wisla Krakow 2.21 · Draw 3.90 · Jagiellonia 3.02
    • Implied 1X2 · Wisla Krakow 43.5% · Draw 24.6% · Jagiellonia 31.8%
    • Bookmaker · Pinnacle
  3. Sep 11, 2026 · 18:29 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Wisla Krakow 2.21 · Draw 3.90 · Jagiellonia 3.02
    • Implied 1X2 · Wisla Krakow 43.5% · Draw 24.6% · Jagiellonia 31.8%
    • Bookmaker · Pinnacle
  4. Sep 11, 2026 · 18:30 UTC Kickoff
  5. FT Full-time result Wisla Krakow win · 2–0
  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 92/100
Betting Confidence 81/100

Validation Report

Immutable Snapshot

Prediction Time: Sep 05, 2026 · 02:03 UTC Snapshot ID: dp-7039705

Closing Odds 3.02
AI Fair Odds —
CLV Pending
Final Result Wisla Krakow win · Wisla Krakow 2–0 Jagiellonia
Prediction ✔ Correct
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

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

  • League: Ekstraklasa
  • Fixture: Wisla Krakow vs Jagiellonia
  • Kickoff: 2026-09-11 18:30:00
  • 1X2 (model): Home 44.0% · Draw 25.6% · Away 30.4%
  • xG (showing): Wisla Krakow 1.78 — Jagiellonia 1.46 (total xG ≈ 3.24)
  • Value headline: None (actionable) — best tracked EV is about +0.5%, 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 Over 2.5 (Under 2.5 37.2% · Over 2.5 62.8%); BTTS Yes (Yes 65.1% · No 34.8%) Value lean (pricing): O/U 2.5 Over 2.5; BTTS Yes
  • BTTS (model): Yes 65.1% · No 34.8%
  • Correct score (top bin): 1-1 (10.2%)

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

September 30, 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