Amkar vs Zenit 2 Statistics & Analysis

May 20, 2026 - 14:00
4 1.45
2 1.25
xG Accuracy: 40%
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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 (6 goals) ✔ Correct
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 Amkar Amkar ✔ Correct
  • Correct Score Insights 1-1, 2-1, 1-2, 2-2, 3-1 4-2 ✖ Incorrect

AI match briefing

AI Match Summary

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

  • League: Second League A - Division A Silver
  • Fixture: Amkar vs Zenit 2
  • Kickoff: 2026-05-20 10:00:00
  • 1X2 (model): Home 41.8% · Draw 25.7% · Away 32.6%
  • xG (showing): Amkar 1.45 — Zenit 2 1.25 (total xG ≈ 2.7)
  • Primary / headline line (Betting Primary Pick when shown): Over 2.5 goals
  • Model: 69.7% · Implied: 57.0% · Probability edge: +12.6 pts · Est. EV: +12.9%
  • BTTS (model): Yes 65.1% · No 34.9%
  • Correct score (top bin): 1-1 (8.8%)

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

Primary angle highlighted on the page: 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).

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

FAQ

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.

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.

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.

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 22, 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
Second League A - Division A Silver Second League A - Division A SilverStandings
# TEAM MP W D L PTS
1 Rodina Moskva II 14 7 4 3 25
2 Kaluga 14 7 3 4 24
3 Torpedo Miass 14 4 8 2 20
4 Irtysh Omsk 14 4 7 3 19
5 Urozhay 14 4 6 4 18
6 Dinamo Vladivostok 14 5 2 7 17
7 Avangard Kursk 14 3 4 7 13
8 Murom 14 2 6 6 12
# TEAM MP GS GC +/- PTS
1 Kaluga 14 20 14 +6 24
2 Rodina Moskva II 14 18 12 +6 25
3 Irtysh Omsk 14 15 13 +2 19
4 Torpedo Miass 14 14 12 +2 20
5 Urozhay 14 14 14 0 18
6 Avangard Kursk 14 14 23 -9 13
7 Dinamo Vladivostok 14 13 16 -3 17
8 Murom 14 13 17 -4 12