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

FC Orenburg vs Krylia Sovetov Prediction, Odds & AI Betting Tips

May 10, 2026 - 09:30
1 1.36
0 0.62
xG Accuracy: 76%
Premium betting site 1xbet: New users can use the promo code 1x_3342271 to receive $100 cash.

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, 0-0, 2-0, 1-1, 0-1 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 22, 2026 (UTC)

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Premier League Premier LeagueStandings
# TEAM MP W D L PTS
1 Zenit 30 20 8 2 68
2 FC Krasnodar 30 20 6 4 66
3 Lokomotiv 30 14 11 5 53
4 Spartak Moscow 30 15 7 8 52
5 CSKA Moscow 30 15 6 9 51
6 Baltika 30 11 13 6 46
7 Dynamo 30 12 9 9 45
8 Rubin 30 11 10 9 43
9 Akhmat 30 9 10 11 37
10 FC Rostov 30 8 9 13 33
11 Krylia Sovetov 30 8 8 14 32
12 FC Orenburg 30 7 8 15 29
13 Akron 30 6 9 15 27
14 Dinamo Makhachkala 30 5 11 14 26
15 Nizhny Novgorod 30 6 5 19 23
16 FC Sochi 30 6 4 20 22
# TEAM MP GS GC +/- PTS
1 FC Krasnodar 30 60 23 +37 66
2 Lokomotiv 30 54 39 +15 53
3 Zenit 30 53 19 +34 68
4 Dynamo 30 51 40 +11 45
5 Spartak Moscow 30 47 39 +8 52
6 CSKA Moscow 30 44 33 +11 51
7 Baltika 30 38 21 +17 46
8 Akhmat 30 35 39 -4 37
9 Krylia Sovetov 30 35 50 -15 32
10 Akron 30 35 53 -18 27
11 Rubin 30 29 30 -1 43
12 FC Orenburg 30 29 44 -15 29
13 FC Sochi 30 29 60 -31 22
14 Nizhny Novgorod 30 26 50 -24 23
15 FC Rostov 30 25 32 -7 33
16 Dinamo Makhachkala 30 19 37 -18 26
# TEAM MP xG xGC +/- PTS
1 FC Krasnodar 30 27.6 15.2 +12.4 66
2 Zenit 30 25.0 14.1 +10.9 68
3 Lokomotiv 30 26.7 20.4 +6.3 53
4 Dynamo 30 23.7 18.5 +5.2 45
5 Spartak Moscow 30 22.8 19.0 +3.8 52
6 Baltika 30 22.2 18.6 +3.6 46
7 Rubin 30 19.1 16.8 +2.3 43
8 FC Rostov 30 19.1 17.2 +1.9 33
9 Akhmat 30 20.2 19.3 +0.9 37
10 CSKA Moscow 30 23.4 24.7 -1.3 51
11 Dinamo Makhachkala 30 15.7 17.1 -1.4 26
12 Akron 30 21.8 24.9 -3.1 27
13 FC Orenburg 30 18.4 23.8 -5.4 29
14 Nizhny Novgorod 30 16.7 25.0 -8.3 23
15 Krylia Sovetov 30 12.9 26.0 -13.1 32
16 FC Sochi 30 12.1 27.1 -15.0 22