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 11, 2026 · 16:00 Not Started

Niznekamsk
vs
Yekaterinburg.

10 AI models read this game. The plurality on the winner leans toward Niznekamsk (5 of 10 models). The mean predicted score (rounded from all models) is 4–3 at 57% mean confidence (Medium band) — see the strip and table below.

Who do you think will win?

Vote before kick-off and compare with AI

— Consensus

Where the panel lands.

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

Niznekamsk win 50%

5 / 10 models

Yekaterinburg win 50%

5 / 10 models

Advertisement
— 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
3–4
61%
Yekaterinburg won the two most recent meetings, including a 6-3 road result, suggesting a modest matchup edge despite Niznekamsk's home advantage. A competitive, medium-scoring game is more likely than a runaway.
02
Claude Sonnet 5
Niznekamsk win
4–3
52%
Mixed recent H2H with high-scoring trend; home venue edge tips a close, offense-heavy contest toward Niznekamsk.
03
Gemini 3.8 Flash
Yekaterinburg win
2–4
61%
Yekaterinburg showed offensive dominance in their recent encounters late in 2025, possessing deeper finishing talent to outscore Niznekamsk on the road.
04
Grok 4.6
Yekaterinburg win
2–3
56%
Yekaterinburg won the last two H2H meetings, including 5-2 on the road in Niznekamsk. Early-season 2026 form is unknown, so the edge is modest.
05
DeepSeek V4 Pro
Yekaterinburg win
3–4
52%
Yekaterinburg have won the last two H2H meetings, including 5-2 at Niznekamsk, and both sides tend to produce high-scoring games, supporting a road edge despite thin current form data.
06
Qwen 3.8 Max
Yekaterinburg win
2–3
58%
Yekaterinburg won the last two H2H meetings convincingly (6-3 and 5-2), showing offensive dominance over Niznekamsk. Away form and recent head-to-head momentum favor Yekaterinburg despite venue disadvantage.
07
Mistral Medium 3.5
Niznekamsk win
4–3
62%
Home edge and 3-2 H2H record favor Niznekamsk; recent meetings high-scoring.
08
Kimi K3
Niznekamsk win
4–3
55%
H2H is split: Niznekamsk won three of five but lost the two most recent. Home ice and historically high-scoring, open meetings between these sides tilt a tight game to Niznekamsk.
09
GLM 5.3
Niznekamsk win
3–2
54%
Niznekamsk won three of the last five H2H meetings, including twice at home; home ice edge in a tight KHL matchup gives a narrow win.
10
MiMo V2.5 Pro
Niznekamsk win
4–3
55%
H2H shows frequent high-scoring games; with home venue, Niznekamsk edges a close match against Yekaterinburg.
— Scoreline frequency

How often each scoreline showed up.

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

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

Match overview

Looking for a today prediction on Niznekamsk vs Yekaterinburg 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 (4 - 3; 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 Niznekamsk win, with vote shares roughly 50% / 50% home and away (rounded).

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

50% of models lean home — the clearest cluster on this fixture before kickoff.

02
Medium confidence

Mean 57% across the panel with real dispersion — compare unanimous calls vs split tickets in the model table.

03
xG tilt 3.10 vs 3.20

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.

Related matches

— Journal

Articles linked to these clubs or AI forecasting.

Advertisement

Ask multiple AIs about this match.

Compare their answers, read the reasoning, and see where they disagree. Try one question free each day.