Statistics / Football / Russia. Second League A - Division A Gold / Novosibirsk vs Kaluga

Novosibirsk vs Kaluga Statistics & Analysis

Novosibirsk Novosibirsk
Sep 20, 2026 - 10:00
3 1.35
0 1.25
xG Accuracy: 45%
Kaluga Kaluga
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Tracked markets vs full-time result

Each row compares the pre-match model lean to the full-time result.

  • Market Prediction Result Outcome
  • Over / Under 2.5 Over 2.5 Over 2.5 (3 goals) ✔ Correct
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 Novosibirsk Novosibirsk ✔ Correct
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 3-0 ✖ Incorrect

Validation Report

Immutable Snapshot

Prediction Time: Sep 14, 2026 · 01:04 UTC Snapshot ID: dp-8660735

Closing Odds 1.7
AI Fair Odds —
CLV +0.0%
Final Result Novosibirsk win · Novosibirsk 3–0 Kaluga
Prediction ✔ Correct
Decision Grade B-

Model Performance

This prediction contributes to:

  • Primary Bets ROI (180d): -100.0%

Market intelligence

Supporting read on how the prioritized closing feed moved versus the model — use after the Primary pick above.

Market briefing

Market remained largely stable before kickoff. No meaningful late implied-price shift was detected between PRE30 and PRE1 on the prioritized bookmaker snapshot.

Despite limited late movement, the model still prices Draw (1X2), Kaluga (1X2), Over 2.5 goals, BTTS Yes meaningfully above what those closing snapshots implied — that gap is a static “model vs. price” read, not a late steam or chase story.

The model still exceeds closing implied on Kaluga (1X2) by about 11.4 percentage points — the clearest mispricing signal summarized on this page.

Model vs. closing implied

Market Model % Closing impl. % Gap (pp)
Novosibirsk (1X2) 37.6 52.5 -14.9
Draw (1X2) 29.6 26.1 +3.5
Kaluga (1X2) 32.9 21.5 +11.4
Over 2.5 goals 48.2 47.0 +1.2
Under 2.5 goals 51.8 53.0 -1.2
BTTS Yes 54.5 49.2 +5.3
BTTS No 45.5 50.8 -5.3
What this means

In plain terms: the model lands near 32.9% on Kaluga (1X2), while the closing snapshot implied about 21.5%. The difference — about 11.4 percentage points — is the largest model-vs.-market gap highlighted on this page.

Quick definitions: “closing implied” is the probability for that outcome implied by the final captured odds (after a simple de-vig). “Gap (pp)” is the model percentage minus that implied value, in percentage points (pp).

Closing-window line move

Single prioritized bookmaker per snapshot (not all books). Capture path: PRE30 → PRE1 · Book: Marathonbet

Column tags in parentheses: Closing uses the first available snapshot in PRE1→PRE5→PRE10→PRE30; Early uses the first available in PRE30→PRE10→PRE5 that is not the same capture as Closing.

Detailed capture odds are folded below — movement was negligible on de-vig implied prices.

View full line-by-line capture table
Market Early (PRE30) Closing (PRE1) Implied Δ (pp)
Novosibirsk (1X2) 1.7 1.7 0.0
Draw (1X2) 3.42 3.42 0.0
Kaluga (1X2) 4.15 4.15 0.0
Over 2.5 goals 1.95 1.95 0.0
Under 2.5 goals 1.73 1.73 0.0
BTTS Yes 1.85 1.85 0.0
BTTS No 1.79 1.79 0.0

AI match briefing

AI Match Summary

Quick read on how the model reads this matchup.

  • League: Second League A - Division A Gold
  • Fixture: Novosibirsk vs Kaluga
  • Kickoff: 2026-09-20 10:00:00
  • 1X2 (model): Home 37.6% · Draw 29.6% · Away 32.9%
  • xG (showing): Novosibirsk 1.35 — Kaluga 1.25 (total xG ≈ 2.6)
  • Value headline: None (actionable) — best tracked EV is about +0.8%, still below the +2.0% minimum for a headline / default stake (no default bet).
  • Structural leans (not bets): Structural lean (model): O/U 2.5 Under 2.5 (Under 2.5 51.8% · Over 2.5 48.2%); BTTS Yes (Yes 54.5% · No 45.5%) Value lean (pricing): O/U 2.5 Over 2.5; BTTS Yes
  • BTTS (model): Yes 54.5% · No 45.5%
  • Correct score (top bin): 1-1 (12.5%)

When book depth is thin or odds are missing, EV may be unavailable even though the model still prefers one side on totals or BTTS — wait for cleaner prices or skip.

Prefer skipping to over-staking when the engine is honest about missing edge.

Historical Recommendation

Historical Decision: No Primary Bet

Outcome: Validated — Pre-match lean validated against the full-time result.

Risk Factors Considered Before Kickoff

  • 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%).

Last Updated

September 29, 2026 (UTC)

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Second League A - Division A Gold Second League A - Division A Gold — Standings
# TEAM MP W D L PTS
1 Dinamo Kirov 11 7 2 2 23
2 Rodina Moskva II 11 7 2 2 23
3 Dinamo Bryansk 11 4 4 3 16
4 Novosibirsk 11 4 3 4 15
5 Dinamo Vladivostok 11 3 4 4 13
6 Mashuk-KMV 11 2 7 2 13
7 Alaniya Vladikavkaz 11 2 6 3 12
8 Volgar Astrakhan 11 1 8 2 11
9 FK Sokol Saratov 11 1 6 4 9
10 Kaluga 11 0 6 5 6
# TEAM MP GS GC +/- PTS
1 Rodina Moskva II 11 20 10 +10 23
2 Novosibirsk 11 15 14 +1 15
3 Alaniya Vladikavkaz 11 14 12 +2 12
4 Dinamo Kirov 11 13 8 +5 23
5 Volgar Astrakhan 11 12 13 -1 11
6 Dinamo Bryansk 11 11 13 -2 16
7 FK Sokol Saratov 11 10 17 -7 9
8 Mashuk-KMV 11 8 8 0 13
9 Dinamo Vladivostok 11 8 9 -1 13
10 Kaluga 11 6 13 -7 6
Second League A - Division A Gold Russia. Second League A - Division A Gold Predictions