Predictions / Football / Poland. I Liga / Polonia Bytom vs Polonia Warszawa

Polonia Bytom vs Polonia Warszawa Prediction, Odds & AI Betting Tips

May 04, 2026 - 16:00
3 1.45
2 1.25
xG Accuracy: 53%
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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 Yes Yes ✔ Correct
  • 1X2 draw Polonia Bytom ✖ Incorrect
  • Correct Score Insights 1-1, 2-1, 1-0, 1-2, 0-1 3-2 ✖ Incorrect

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 Bytom vs Polonia Warszawa
  • Kickoff: 2026-05-04 16:00:00
  • 1X2 (model): Home 10.0% · Draw 45.0% · Away 45.0%
  • xG (showing): Polonia Bytom 1.45 — Polonia Warszawa 1.25 (total xG ≈ 2.7)
  • Primary / headline line (Betting Primary Pick when shown): draw
  • Model: 45.0% · Implied: 26.5% · Probability edge: +18.5 pts · Est. EV: +9.6%
  • BTTS (model): Yes 66.7% · No 33.3%
  • Correct score (top bin): 1-1 (11.6%)

Where EV is shown, it is estimated return per unit stake at the best tracked decimal price — not the same thing as a raw probability gap.

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

Best Bet + Reason

Primary pick from the decision engine: draw.

If 1X2 looks tight, the engine may still find clearer structure in totals or BTTS — that is intentional.

Edges shrink quickly if prices move; always re-check the number on your book.

FAQ

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.

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.

Why might 1X2 look unattractive while totals do not?

Tight 1X2 prices often embed a fair three-way split, so EV on match-winner can sit negative even when Over/Under or BTTS still diverges from the model — compare the 1X2 row on the market cards to O/U and BTTS.

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 LigaStandings
# 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