COM 1-2 ASR · 47% ELC 1-1 CEL · 45% CRY 1-1 NOT · 45% HUL 1-2 EVE · 45% NIC 2-1 STR · 46% LAZ 2-0 MON · 51% LEC 0-1 BOL · 43% 1.F 2-2 BOR · 42% REA 2-0 DEP · 51% REN 2-1 AUX · 47% LIV 1-1 MAN · 43% SCF 2-0 FCS · 54% SAS 1-2 ACM · 47% REA 2-1 OSA · 45% COM 1-2 ASR · 47% ELC 1-1 CEL · 45% CRY 1-1 NOT · 45% HUL 1-2 EVE · 45% NIC 2-1 STR · 46% LAZ 2-0 MON · 51% LEC 0-1 BOL · 43% 1.F 2-2 BOR · 42% REA 2-0 DEP · 51% REN 2-1 AUX · 47% LIV 1-1 MAN · 43% SCF 2-0 FCS · 54% SAS 1-2 ACM · 47% REA 2-1 OSA · 45%
KHL Oct 2, 2026 · 14:00 Finished

Yekaterinburg
vs
Khabarovsk.

Quick answer

Who will win Yekaterinburg vs Khabarovsk?

Final score: Yekaterinburg 3–0 Khabarovsk. Before kickoff, 9 of 10 AI models pick Yekaterinburg to win (90%); the consensus was right. The AI predicted score was 3–2.

Consensus of independent AI models on TuringStats, updated before kickoff. Not betting advice.

10 AI models read this game. The plurality on the winner leans toward Yekaterinburg (9 of 10 models). The mean predicted score (rounded from all models) is 3–2 at 59% mean confidence (Medium band) — see the strip and table below.

Who do you think will win?

Vote before kick-off and compare with AI

10 AI models · council in session Live match data · Pro

Still not sure? Ask 10 AIs at once:
“Will Yekaterinburg beat Khabarovsk in their upcoming match?”

Every model votes yes or no and defends it in a sentence or two. Attach this match's last-5 form, head-to-head and the picks above so they argue from real data — then keep asking the same council follow-ups.

Ask the Council Free today · sign in with Google to convene the council
— Consensus

Where the panel lands.

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

Yekaterinburg win 90%

9 / 10 models

Khabarovsk win 10%

1 / 10 models

— 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
Yekaterinburg win
3–2
56%
Yekaterinburg has the home advantage and won two of the last three meetings there, though Khabarovsk’s recent 5-2 victory signals a competitive matchup. A close, moderately paced game is most likely.
02
Claude Sonnet 5
Yekaterinburg win
4–3
53%
Split recent H2H with both sides scoring heavily; home ice and a slight edge from recent home win over Khabarovsk tilt a close, high-paced matchup.
03
Gemini 3.8 Flash
Yekaterinburg win
4–2
68%
Yekaterinburg typically controls this matchup at home, capitalizing on Khabarovsk's defensive lapses on road trips to secure a multi-goal victory.
04
Grok 4.6
Yekaterinburg win
4–2
58%
Yekaterinburg won all listed home H2H meetings (4-2, 3-1, 5-3); Khabarovsk travels far. Home ice edge, similar open scoring, not a blowout.
05
DeepSeek V4 Pro
Yekaterinburg win
3–2
58%
Yekaterinburg has won three of the last five H2H meetings, including both home games, and holds a venue edge. Khabarovsk is competitive but has been inconsistent on the road.
06
Qwen 3.8 Max
Yekaterinburg win
3–2
62%
Yekaterinburg won both home H2H meetings convincingly; home ice advantage and historical dominance at their venue support a narrow home win despite Khabarovsk's recent away victory.
07
Mistral Medium 3.5
Khabarovsk win
3–4
60%
Khabarovsk won 3 of last 5, including recent 5-2; Yekaterinburg strong at home but Khabarovsk's road form edges it.
08
Kimi K3
Yekaterinburg win
4–2
62%
Yekaterinburg has won three of the last five meetings, including two home victories this season, and typically plays higher-scoring games at home against Khabarovsk.
09
GLM 5.3
Yekaterinburg win
4–2
58%
Yekaterinburg won both recent home H2H meetings with Khabarovsk (4-2, 3-1); home venue edge outweighs Khabarovsk's road win in January.
10
MiMo V2.5 Pro
Yekaterinburg win
3–2
58%
H2H shows split results with high-scoring games; Yekaterinburg's home venue and recent 4-2 win provide a slight edge in a close, offensive matchup.
— Scoreline frequency

How often each scoreline showed up.

4 of 10 models settled on 3–2. The rest of the list shows where dissent still lives before kickoff.

  • 3–2
    4 models
  • 4–2
    4 models
  • 4–3
    1 model
  • 3–4
    1 model

Match overview

Looking for a today prediction on Yekaterinburg vs Khabarovsk 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 - 2; 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 Yekaterinburg win, with vote shares roughly 90% / 10% home and away (rounded).

If you are asking who will win Yekaterinburg vs Khabarovsk, 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 Yekaterinburg

90% of models lean home — the clearest cluster on this fixture before kickoff.

02
Medium confidence

Mean 59% across the panel with real dispersion — compare unanimous calls vs split tickets in the model table.

03
xG tilt 3.50 vs 2.30

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.

Ask the Council about this match

Pro

10 AI models vote yes or no with this match's last-5 form, head-to-head, live status and the model picks above attached — not from memory. Then keep asking the same council follow-ups.

Confidence trend

Cumulative average confidence in table order.

First model Last model

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Ask multiple AIs about this match.

10 models vote yes or no with this match's last-5 form, head-to-head, live status and our model picks attached — not from memory. Then ask follow-ups to the same council.