Statistics / Football / Poland. Ekstraklasa / Jagiellonia vs Pogon Szczecin

Jagiellonia vs Pogon Szczecin Statistics & Analysis

Jagiellonia Jagiellonia
May 09, 2026 - 15:30
3 1.62
2 1.33
xG Accuracy: 57%
Pogon Szczecin Pogon Szczecin
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Tracked markets vs full-time result

Each row compares the model’s highlighted side (or lean) to what happened at full time.

  • Market Prediction Result Outcome
  • Over / Under 2.5 Under 2.5 Over 2.5 (5 goals) ✖ Incorrect
  • Both Teams To Score BTTS No Yes ✖ Incorrect
  • 1X2 Jagiellonia Jagiellonia ✔ Correct
  • Correct Score Insights 1-1 3-2 ✖ Incorrect

AI match briefing

AI Match Summary

Quick read on how the model reads this matchup.

  • League: Ekstraklasa
  • Fixture: Jagiellonia vs Pogon Szczecin
  • Kickoff: 2026-05-09 16:00:00
  • 1X2 (model): Home 42.8% · Draw 27.2% · Away 30.0%
  • xG (showing): Jagiellonia 1.62 — Pogon Szczecin 1.33 (total xG ≈ 2.95)
  • Primary / headline line (Betting Primary Pick when shown): Under 2.5 goals
  • Model: 43.5% · Implied: 38.5% · Probability edge: +5.0 pts · Est. EV: +10.9%
  • BTTS (model): Yes 60.5% · No 39.5%
  • Correct score (top bin): 1-1 (11.3%)

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.

Best Bet + Reason

The engine’s headline primary is: Under 2.5 goals.

Model probability is compared to implied probability from odds to highlight a probability edge; EV uses the same model probability with the best decimal price tracked.

Only one modest +EV edge is highlighted here; size cautiously and re-check if odds move.

FAQ

What changes first if odds move?

Implied probabilities and EV move immediately with price; model probabilities in this snapshot do not update until the pipeline is re-run. Refresh after material line moves.

How should I read EV versus a probability gap?

Probability edge = model probability minus implied probability (reported here in percentage points). EV ≈ model probability × best tracked decimal odds − 1, shown as return per unit stake. They are related but not interchangeable labels.

Who has the edge in the match-winner market?

Use the 1X2 model percentages in the summary and the 1X2 market card: the side with the highest model % is the model lean, but check EV — a lean can still be -EV after prices.

Is the most likely correct score a good bet?

Usually no as a standalone bet: the “most likely” scoreline is still a low absolute probability tail event (often single digits, sometimes low teens). Use it as context; keep any correct-score stake in the “fun / small” bucket.

Risk Factors

  • 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%).

Methodology

  • Inputs: Same structured facts bundle as the public prediction page (xG / Poisson snapshot, market EV where available, decision engine v2).
  • Compliance: Educational framing only; not personalised advice.

Last Updated

May 17, 2026 (UTC)

How to use this
  • Focus on the Primary line when you want one actionable idea.
  • Do not parlay many thin-edge picks together; edges do not add reliably.
  • Treat longshots as optional, high-stake-sizing plays only.

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Back to Statistics
Ekstraklasa Ekstraklasa — Standings
# TEAM MP W D L PTS
1 Lech Poznan 33 16 11 6 59
2 Gornik Zabrze 33 15 8 10 53
3 Jagiellonia 32 14 10 8 52
4 Raków Częstochowa 32 14 7 11 49
5 Zaglebie Lubin 33 13 9 11 48
6 GKS Katowice 32 14 6 12 48
7 Wisla Plock 33 12 9 12 45
8 Radomiak Radom 33 11 11 11 44
9 Pogon Szczecin 33 13 5 15 44
10 Legia Warszawa 32 10 13 9 43
11 Motor Lublin 33 10 13 10 43
12 Korona Kielce 33 11 9 13 42
13 Piast Gliwice 32 11 8 13 41
14 Cracovia Krakow 33 9 14 10 41
15 Widzew Łódź 33 11 6 16 39
16 Lechia Gdansk 32 12 7 13 38
17 Arka Gdynia 32 9 9 14 36
18 Nieciecza 32 7 7 18 28
# TEAM MP GS GC +/- PTS
1 Lech Poznan 33 60 43 +17 59
2 Lechia Gdansk 32 59 60 -1 38
3 Jagiellonia 32 53 39 +14 52
4 Radomiak Radom 33 50 47 +3 44
5 GKS Katowice 32 48 42 +6 48
6 Pogon Szczecin 33 46 48 -2 44
7 Motor Lublin 33 46 49 -3 43
8 Zaglebie Lubin 33 45 37 +8 48
9 Raków Częstochowa 32 45 39 +6 49
10 Gornik Zabrze 33 44 36 +8 53
11 Piast Gliwice 32 40 41 -1 41
12 Korona Kielce 33 39 39 0 42
13 Widzew Łódź 33 39 40 -1 39
14 Cracovia Krakow 33 38 41 -3 41
15 Nieciecza 32 37 61 -24 28
16 Legia Warszawa 32 36 36 0 43
17 Wisla Plock 33 32 36 -4 45
18 Arka Gdynia 32 32 55 -23 36
# TEAM MP xG xGC +/- PTS
1 Lech Poznan 33 58.4 34.1 +24.3 59
2 Raków Częstochowa 32 51.3 39.8 +11.5 49
3 Legia Warszawa 32 42.8 33.9 +8.9 43
4 Lechia Gdansk 32 47.2 42.3 +4.9 38
5 Pogon Szczecin 33 50.5 47.6 +2.9 44
6 Piast Gliwice 32 42.1 39.4 +2.7 41
7 Cracovia Krakow 33 36.6 34.5 +2.1 41
8 Gornik Zabrze 33 40.5 38.7 +1.8 53
9 Widzew Łódź 33 37.6 36.4 +1.2 39
10 Korona Kielce 33 48.8 49.2 -0.4 42
11 Radomiak Radom 33 41.5 42.4 -0.9 44
12 Wisla Plock 33 40.9 43.2 -2.3 45
13 GKS Katowice 32 40.0 43.4 -3.4 48
14 Jagiellonia 32 40.3 47.1 -6.8 52
15 Zaglebie Lubin 33 32.9 40.9 -8.0 48
16 Nieciecza 32 41.1 53.0 -11.9 28
17 Motor Lublin 33 37.8 50.7 -12.9 43
18 Arka Gdynia 32 34.1 47.9 -13.8 36
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