Statistics / Football / Russia. Premier League / Lokomotiv vs Baltika

Lokomotiv vs Baltika Statistics & Analysis

May 10, 2026 - 16:30
1 1.28
0 0.96
xG Accuracy: 71%
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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 Lokomotiv Lokomotiv ✔ Correct
  • Correct Score Insights 1-0 1-0 ✔ Correct

AI match briefing

AI Match Summary

Pre-match snapshot for this fixture.

  • League: Premier League
  • Fixture: Lokomotiv vs Baltika
  • Kickoff: 2026-05-09 15:00:00
  • 1X2 (model): Home 42.0% · Draw 31.8% · Away 26.2%
  • xG (showing): Lokomotiv 1.28 — Baltika 0.96 (total xG ≈ 2.24)
  • Primary / headline line (Betting Primary Pick when shown): Under 2.5 goals
  • Model: 61.2% · Implied: 55.9% · Probability edge: +5.3 pts · Est. EV: +7.7%
  • BTTS (model): Yes 46.2% · No 53.8%
  • Correct score (top bin): 1-0 (13.6%)

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

1X2 can look balanced even when side markets show clearer structure.

Best Bet + Reason

The engine’s headline primary is: 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

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.

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 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.

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.

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