UNI 1-0 FCS · 57% REN 1-2 MAR · 58% VEN 1-1 FIO · 57% GEN 1-0 FRO · 57% BOR 3-1 SCP · 67% 189 1-1 VFB · 57% SCF 2-1 BOR · 59% FCA 1-2 BAY · 60% FSV 1-1 EIN · 57% CHE 2-0 HUL · 67% LIV 2-1 FUL · 65% AST 2-1 NOT · 62% BOU 1-1 BRE · 57% CRY 1-0 IPS · 60% UNI 1-0 FCS · 57% REN 1-2 MAR · 58% VEN 1-1 FIO · 57% GEN 1-0 FRO · 57% BOR 3-1 SCP · 67% 189 1-1 VFB · 57% SCF 2-1 BOR · 59% FCA 1-2 BAY · 60% FSV 1-1 EIN · 57% CHE 2-0 HUL · 67% LIV 2-1 FUL · 65% AST 2-1 NOT · 62% BOU 1-1 BRE · 57% CRY 1-0 IPS · 60%
KHL Sep 8, 2026 · 16:30 Finished

Lokomotiv Yaroslavl
vs
Shanghai.

10 AI models read this game. The plurality on the winner leans toward Lokomotiv Yaroslavl (10 of 10 models). The mean predicted score (rounded from all models) is 3–1 at 66% mean confidence (Medium band) — see the strip and table below.

Who do you think will win?

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— Consensus

Where the panel lands.

Vote share across models. Read this strip first, then the line-by-line table.

Lokomotiv Yaroslavl win 100%

10 / 10 models

Shanghai win 0%

0 / 10 models

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— Model breakdown

10 picks. Receipts attached.

Line-by-line comparison of each system’s call.

#
Model
Pick
Score
Conf.
Reasoning
01
GPT-5.6 Luna
Lokomotiv Yaroslavl win
3–1
68%
Lokomotiv’s home advantage and two recent wins over Shanghai, including a 2-0 result in February, support a controlled home victory. The limited current-form data argues for moderate rather than high confidence.
02
Claude Sonnet 5
Lokomotiv Yaroslavl win
3–1
62%
Lokomotiv won last two H2H meetings and holds home-ice advantage; Shanghai remains a weaker KHL side overall despite one prior upset.
03
Gemini 3.8 Flash
Lokomotiv Yaroslavl win
3–1
72%
Lokomotiv boasts superior defensive organization and home-ice control, having shut out Shanghai in recent 2026 meetings to consistently limit their scoring chances.
04
Grok 4.6
Lokomotiv Yaroslavl win
3–1
62%
Lokomotiv is the stronger KHL side at home; last two H2H were 2-0 shutouts. Shanghai can score in bursts but usually struggles on the road in Yaroslavl.
05
DeepSeek V4 Pro
Lokomotiv Yaroslavl win
3–1
61%
Lokomotiv's recent H2H shutouts and home venue support control, though Shanghai has shown upset ability, so a two-goal home margin is the most grounded estimate.
06
Qwen 3.8 Max
Lokomotiv Yaroslavl win
3–1
68%
Lokomotiv won both 2026 H2H meetings by shutout at home and away, showing defensive dominance over Shanghai. Home venue and recent trend support a comfortable margin.
07
Mistral Medium 3.5
Lokomotiv Yaroslavl win
2–1
70%
Lokomotiv won both 2026 meetings 2-0; home edge and recent form favor them.
08
Kimi K3
Lokomotiv Yaroslavl win
3–1
68%
Lokomotiv won the last two meetings 2-0 and is a strong home KHL side, while Shanghai/Kunlun struggles offensively; expect a controlled, low-scoring home win.
09
GLM 5.3
Lokomotiv Yaroslavl win
3–1
68%
Lokomotiv won the last two meetings 2-0 and are strong at home; Shanghai's attack has been contained before, so a moderate home win with a modest total fits.
10
MiMo V2.5 Pro
Lokomotiv Yaroslavl win
2–1
60%
Recent H2H shows Lokomotiv won last two meetings with shutouts; home advantage supports a narrow, low-scoring victory.
— Scoreline frequency

How often each scoreline showed up.

8 of 10 models settled on 3–1. That convergence is a strong scoreline signal—many fixtures fan out wider across the panel.

  • 3–1
    8 models
  • 2–1
    2 models

Match overview

Looking for a today prediction on Lokomotiv Yaroslavl vs Shanghai in KHL? TuringStats aggregates multiple AI scorelines into one readable page so you can see who the models favor, the mean predicted score shown in the hero (3 - 1; the frequency chart below lists the most common exact scorelines), and implied splits before kickoff.

This prediction hub is written for readers comparing betting tips-style language with transparent model votes — not a single black-box call. The headline read is Lokomotiv Yaroslavl win, with vote shares roughly 100% / 0% home and away (rounded).

If you are asking who will win Lokomotiv Yaroslavl vs Shanghai, start with the consensus strip and model table, then cross-check form and injuries in Match context further down — that order keeps the strongest signals first.

— Aggregated insights

What’s moving the panel.

01
Consensus favors Lokomotiv Yaroslavl

100% of models lean home — the clearest cluster on this fixture before kickoff.

02
Medium confidence

Mean 66% across the panel with real dispersion — compare unanimous calls vs split tickets in the model table.

03
xG tilt 2.80 vs 1.00

Derived from predicted scorelines (model means), not live game data — useful for pace vs vote-share sanity checks.

04
Match context

Expected-goals tilt and home-field rhythm (see xG on this page) usually explain whether the game stays open or compresses late.

Confidence trend

Cumulative average confidence in table order.

First model Last model

Explore more

Keep browsing today prediction coverage and league hubs.

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— Journal

Articles linked to these clubs or AI forecasting.

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