Statistics / Football / Ukraine. Premier League / Oleksandria vs Zorya Luhansk

Oleksandria vs Zorya Luhansk Statistics & Analysis

May 12, 2026 - 10:00
1 1.22
2 2.01
xG Accuracy: 94%
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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 Zorya Luhansk Zorya Luhansk ✔ Correct
  • Correct Score Insights 1-2 1-2 ✔ Correct

AI match briefing

AI Match Summary

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

  • League: Premier League
  • Fixture: Oleksandria vs Zorya Luhansk
  • Kickoff: 2026-05-16 15:00:00
  • 1X2 (model): Home 21.6% · Draw 24.1% · Away 54.4%
  • xG (showing): Oleksandria 1.22 — Zorya Luhansk 2.01 (total xG ≈ 3.23)
  • Primary / headline line (Betting Primary Pick when shown): Over 2.5 goals
  • Model: 62.6% · Implied: 46.3% · Probability edge: +16.3 pts · Est. EV: +29.6%
  • BTTS (model): Yes 62.3% · No 37.7%
  • Correct score (top bin): 1-2 (9.7%)

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: Over 2.5 goals.

We separate probability edge (model minus implied, in points of probability) from estimated EV (economic edge at the best price shown on the page).

When several markets sit near +EV, keep stakes small — correlation means edges do not add cleanly.

FAQ

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.

What is the best-supported line in this snapshot?

Match the hero card above: if it says “Betting Primary Pick”, that leg cleared primary rules; if it says “Best +EV (tracked markets)”, it is the strongest +EV line that did not meet stricter Primary thresholds. The bullets below repeat the same model %, implied %, edge (pts), and EV % as that card.

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.

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 18, 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 29.8 9.8 +20.0 69
3 Polessya 28 35.3 17.0 +18.3 55
4 LNZ Cherkasy 28 27.3 12.2 +15.1 57
5 Metalist 1925 Kharkiv 29 22.0 12.7 +9.3 48
6 Karpaty 28 24.4 20.0 +4.4 38
7 Kolos Kovalivka 28 22.6 22.2 +0.4 46
8 Zorya Luhansk 28 21.1 21.2 -0.1 42
9 Veres Rivne 28 12.6 16.5 -3.9 31
10 Ruh Lviv 28 16.1 21.5 -5.4 21
11 Obolon'-Brovar 28 17.2 23.2 -6.0 28
12 Kryvbas KR 28 21.4 27.8 -6.4 47
13 Kudrivka 28 14.9 27.4 -12.5 25
14 Epitsentr Dunayivtsi 29 18.9 32.2 -13.3 31
15 Oleksandria 28 10.5 25.0 -14.5 13
16 SK Poltava 29 10.1 36.0 -25.9 12