Statistics / Football / Russia. Premier League / FC Orenburg vs Krylia Sovetov

FC Orenburg vs Krylia Sovetov Statistics & Analysis

May 10, 2026 - 09:30
1 1.36
0 0.62
xG Accuracy: 76%
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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 No No ✔ Correct
  • 1X2 FC Orenburg FC Orenburg ✔ Correct
  • Correct Score Insights 1-0 1-0 ✔ 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: FC Orenburg vs Krylia Sovetov
  • Kickoff: 2026-05-09 15:00:00
  • 1X2 (model): Home 53.4% · Draw 31.1% · Away 15.5%
  • xG (showing): FC Orenburg 1.36 — Krylia Sovetov 0.62 (total xG ≈ 1.98)
  • Primary / headline line (Betting Primary Pick when shown): Under 2.5 goals
  • Model: 68.2% · Implied: 49.6% · Probability edge: +18.6 pts · Est. EV: +35.7%
  • BTTS (model): Yes 35.9% · No 64.1%
  • Correct score (top bin): 1-0 (18.8%)

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.

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

Best Bet + Reason

Primary angle highlighted on the page: Under 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.

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.

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.

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 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 Zenit 29 19 8 2 65
2 FC Krasnodar 29 19 6 4 63
3 Lokomotiv 29 14 11 4 53
4 Spartak Moscow 29 15 6 8 51
5 CSKA Moscow 29 14 6 9 48
6 Baltika 29 11 13 5 46
7 Dynamo 29 11 9 9 42
8 Rubin 29 11 9 9 42
9 Akhmat 29 9 9 11 36
10 FC Rostov 29 8 9 12 33
11 FC Orenburg 29 7 8 14 29
12 Krylia Sovetov 29 7 8 14 29
13 Akron 29 6 9 14 27
14 Dinamo Makhachkala 29 5 10 14 25
15 Nizhny Novgorod 29 6 4 19 22
16 FC Sochi 29 6 3 20 21
# TEAM MP GS GC +/- PTS
1 FC Krasnodar 29 57 23 +34 63
2 Lokomotiv 29 53 36 +17 53
3 Zenit 29 52 19 +33 65
4 Dynamo 29 49 39 +10 42
5 Spartak Moscow 29 47 39 +8 51
6 CSKA Moscow 29 41 32 +9 48
7 Baltika 29 37 19 +18 46
8 Akhmat 29 34 38 -4 36
9 Akron 29 34 49 -15 27
10 Krylia Sovetov 29 31 49 -18 29
11 FC Orenburg 29 29 41 -12 29
12 FC Sochi 29 28 59 -31 21
13 Rubin 29 27 28 -1 42
14 FC Rostov 29 25 31 -6 33
15 Nizhny Novgorod 29 24 48 -24 22
16 Dinamo Makhachkala 29 19 37 -18 25
# TEAM MP xG xGC +/- PTS
1 FC Krasnodar 29 27.6 15.2 +12.4 63
2 Zenit 29 25.0 14.1 +10.9 65
3 Lokomotiv 29 26.7 20.4 +6.3 53
4 Dynamo 29 23.7 18.5 +5.2 42
5 Spartak Moscow 29 22.8 19.0 +3.8 51
6 Baltika 29 22.2 18.6 +3.6 46
7 Rubin 29 19.1 16.8 +2.3 42
8 FC Rostov 29 19.1 17.2 +1.9 33
9 Akhmat 29 20.2 19.3 +0.9 36
10 CSKA Moscow 29 23.4 24.7 -1.3 48
11 Dinamo Makhachkala 29 15.7 17.1 -1.4 25
12 Akron 29 21.8 24.9 -3.1 27
13 FC Orenburg 29 18.4 23.8 -5.4 29
14 Nizhny Novgorod 29 16.7 25.0 -8.3 22
15 Krylia Sovetov 29 12.9 26.0 -13.1 29
16 FC Sochi 29 12.1 27.1 -15.0 21