Predictions / Football / Poland. I Liga / Polonia Warszawa vs Wisla Krakow

Polonia Warszawa vs Wisla Krakow Prediction, Odds & AI Betting Tips

Polonia Warszawa Polonia Warszawa
May 15, 2026 - 18:30
0 1.45
1 1.25
xG Accuracy: 63%
Wisla Krakow Wisla Krakow
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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 Under 2.5 (1 goals) ✔ Correct
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 Polonia Warszawa Wisla Krakow ✖ Incorrect
  • Correct Score Insights 1-1, 1-2, 0-1, 0-2, 2-1 0-1 ✔ Correct

Next AI Predictions Available Today

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AI match briefing

AI Match Summary

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

  • League: I Liga
  • Fixture: Polonia Warszawa vs Wisla Krakow
  • Kickoff: 2026-05-16 15:00:00
  • 1X2 (model): Home 41.8% · Draw 25.7% · Away 32.6%
  • xG (showing): Polonia Warszawa 1.45 — Wisla Krakow 1.25 (total xG ≈ 2.7)
  • Primary / headline line (Betting Primary Pick when shown): BTTS Yes
  • Model: 78.9% · Implied: 62.9% · Probability edge: +16.0 pts · Est. EV: +18.4%
  • BTTS (model): Yes 78.9% · No 21.1%
  • Correct score (top bin): 1-1 (10.4%)

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

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

Best Bet + Reason

Primary pick from the decision engine: BTTS Yes.

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

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.

Safer market than correct score?

Markets with more liquidity and smoother prices (often 1X2 or O/U 2.5 from many books) are usually easier to reason about than long-tail correct-score prices; still read EV on each leg.

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.

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.

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 25, 2026 (UTC)

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I Liga I Liga — Standings
# TEAM MP W D L PTS
1 Wisla Krakow 34 20 11 3 71
2 Slask Wroclaw 34 17 11 6 62
3 Wieczysta Kraków 34 16 9 9 57
4 Chrobry Głogów 34 16 7 11 55
5 ŁKS Łódź 34 15 9 10 54
6 Polonia Warszawa 34 15 8 11 53
7 Ruch Chorzów 34 14 11 9 53
8 Miedz Legnica 34 15 7 12 52
9 Puszcza Niepołomice 34 12 13 9 49
10 Polonia Bytom 34 13 8 13 47
11 Pogoń Grod. Mazowiecki 34 11 12 11 45
12 Odra Opole 34 11 11 12 44
13 Stal Rzeszów 34 12 7 15 43
14 Stal Mielec 34 10 6 18 36
15 Pogoń Siedlce 34 9 9 16 36
16 Znicz Pruszków 34 7 7 20 28
17 Górnik Łęczna 34 5 12 17 27
18 Tychy 71 34 5 8 21 23
# TEAM MP GS GC +/- PTS
1 Wisla Krakow 34 72 32 +40 71
2 Wieczysta Kraków 34 70 47 +23 57
3 Slask Wroclaw 34 69 47 +22 62
4 ŁKS Łódź 34 56 48 +8 54
5 Polonia Bytom 34 56 50 +6 47
6 Ruch Chorzów 34 54 46 +8 53
7 Polonia Warszawa 34 52 49 +3 53
8 Miedz Legnica 34 52 53 -1 52
9 Pogoń Grod. Mazowiecki 34 51 54 -3 45
10 Stal Mielec 34 51 62 -11 36
11 Stal Rzeszów 34 49 60 -11 43
12 Chrobry Głogów 34 48 36 +12 55
13 Puszcza Niepołomice 34 45 40 +5 49
14 Znicz Pruszków 34 40 68 -28 28
15 Tychy 71 34 40 74 -34 23
16 Górnik Łęczna 34 39 62 -23 27
17 Odra Opole 34 34 40 -6 44
18 Pogoń Siedlce 34 33 43 -10 36
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