Statistik / Bola Sepak / Russia. Premier League / FC Sochi vs FC Orenburg

FC Sochi vs FC Orenburg Statistics & Analysis

May 03, 2026 - 11:30
3 0.99
1 1.02
xG Accuracy: 57%
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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
  • Lebih / Kurang 2.5 Kurang 2.5 Lebih 2.5 (4 goals) ✖ Incorrect
  • Kedua-dua Pasukan Menjaringkan Gol BTTS Tidak Ya ✖ Incorrect
  • 1X2 draw FC Sochi ✖ Incorrect
  • Cerapan skor tepat 0-1 3-1 ✖ Incorrect

Taklimat perlawanan AI

Ringkasan perlawanan AI

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

  • League: Premier League
  • Fixture: FC Sochi vs FC Orenburg
  • Kickoff: 2026-05-02 15:00:00
  • 1X2 (model): Home 32.1% · Draw 34.3% · Away 33.7%
  • xG (showing): FC Sochi 0.99 — FC Orenburg 1.02 (total xG ≈ 2.01)
  • Primary / headline line (Betting Primary Pick when shown): Under 2.5 goals
  • Model: 67.4% · Implied: 52.3% · Probability edge: +15.1 pts · Est. EV: +27.4%
  • BTTS (model): Yes 41.9% · No 58.1%
  • Correct score (top bin): 0-1 (13.7%)

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

Early match state can move realised goals away from pre-kick projections.

Taruhan terbaik dan sebab

Primary angle highlighted on the page: Under 2.5 goals.

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.

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

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.

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.

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.

Faktor risiko

  • 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%).

Metodologi

  • Inputs: Same structured facts bundle as the public prediction page (xG / Poisson snapshot, market EV where available, decision engine v2).
  • Narrative: Template sentence library with fixture-stable selection (no per-request LLM for this block).
  • Compliance: Educational framing only; not personalised advice.

Terakhir dikemas kini

May 01, 2026 (UTC)

Bagaimana untuk menggunakan ini
  • Fokus pada baris Utama apabila anda mahukan satu idea yang boleh diambil tindakan.
  • Jangan parlay banyak picks tepi nipis bersama-sama;tepi tidak menambah dengan pasti.
  • Anggap pukulan panjang sebagai permainan pilihan, bersaiz tinggi sahaja.

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Premier League Premier LeagueKedudukan
# PASUKAN MP M S K 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
# PASUKAN 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
# PASUKAN 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