Statistics / Football / Ukraine. Premier League / Polessya vs Oleksandria

Polessya vs Oleksandria Statistics & Analysis

May 08, 2026 - 15:00
2 2.82
1 0.64
xG Accuracy: 72%
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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 Over 2.5 Over 2.5 (3 goals) ✔ Correct
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 Polessya Polessya ✔ Correct
  • Correct Score Insights 2-0 2-1 ✖ Incorrect

AI match briefing

AI Match Summary

Pre-match snapshot for this fixture.

  • League: Premier League
  • Fixture: Polessya vs Oleksandria
  • Kickoff: 2026-05-09 15:00:00
  • 1X2 (model): Home 81.4% · Draw 13.5% · Away 5.1%
  • xG (showing): Polessya 2.82 — Oleksandria 0.64 (total xG ≈ 3.46)
  • Primary / headline line (Betting Primary Pick when shown): BTTS Yes
  • Model: 45.2% · Implied: 33.4% · Probability edge: +11.8 pts · Est. EV: +35.6%
  • BTTS (model): Yes 45.2% · No 54.8%
  • Correct score (top bin): 2-0 (12.5%)

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

Correct score remains high-variance even when a line is most likely on paper.

Best Bet + Reason

The engine’s headline primary is: 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.

No pick is a guarantee; variance is especially large in scoreline markets.

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.

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.

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
Premier League Premier LeagueStandings
# TEAM MP W D L PTS
1 Shakhtar Donetsk 28 21 6 1 69
2 LNZ Cherkasy 28 17 6 5 57
3 Polessya 28 17 4 7 55
4 Dynamo Kyiv 29 16 6 7 54
5 Metalist 1925 Kharkiv 29 12 12 5 48
6 Kryvbas KR 28 13 8 7 47
7 Kolos Kovalivka 28 12 10 6 46
8 Zorya Luhansk 28 11 9 8 42
9 Karpaty 28 9 11 8 38
10 Veres Rivne 28 7 10 11 31
11 Epitsentr Dunayivtsi 29 8 7 14 31
12 Obolon'-Brovar 28 6 10 12 28
13 Kudrivka 28 6 7 15 25
14 Ruh Lviv 28 6 3 19 21
15 Oleksandria 28 2 7 19 13
16 SK Poltava 29 2 6 21 12
# TEAM MP GS GC +/- PTS
1 Shakhtar Donetsk 28 68 18 +50 69
2 Dynamo Kyiv 29 63 34 +29 54
3 Kryvbas KR 28 50 42 +8 47
4 Polessya 28 49 21 +28 55
5 Zorya Luhansk 28 40 35 +5 42
6 LNZ Cherkasy 28 38 16 +22 57
7 Karpaty 28 37 29 +8 38
8 Epitsentr Dunayivtsi 29 36 45 -9 31
9 Metalist 1925 Kharkiv 29 35 19 +16 48
10 Kolos Kovalivka 28 29 23 +6 46
11 Kudrivka 28 29 45 -16 25
12 Veres Rivne 28 26 37 -11 31
13 Obolon'-Brovar 28 26 48 -22 28
14 SK Poltava 29 23 74 -51 12
15 Oleksandria 28 20 56 -36 13
16 Ruh Lviv 28 19 46 -27 21
# TEAM MP xG xGC +/- PTS
1 Dynamo Kyiv 29 30.7 10.1 +20.6 54
2 Shakhtar Donetsk 28 29.2 9.0 +20.2 69
3 Polessya 28 30.3 14.6 +15.7 55
4 LNZ Cherkasy 28 25.3 11.7 +13.6 57
5 Metalist 1925 Kharkiv 29 20.8 11.0 +9.8 48
6 Karpaty 28 22.7 18.8 +3.9 38
7 Kolos Kovalivka 28 22.6 22.2 +0.4 46
8 Zorya Luhansk 28 18.7 20.3 -1.6 42
9 Veres Rivne 28 10.0 15.0 -5.0 31
10 Kryvbas KR 28 19.9 25.2 -5.3 47
11 Ruh Lviv 28 16.1 21.5 -5.4 21
12 Obolon'-Brovar 28 16.4 22.6 -6.2 28
13 Epitsentr Dunayivtsi 29 16.5 27.2 -10.7 31
14 Kudrivka 28 14.9 27.4 -12.5 25
15 Oleksandria 28 9.6 22.6 -13.0 13
16 SK Poltava 29 9.6 34.1 -24.5 12