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 9, 2026 · 16:30 Finished

CSKA Moscow
vs
Nizhny Novgorod.

10 AI models read this game. The plurality on the winner leans toward CSKA Moscow (10 of 10 models). The mean predicted score (rounded from all models) is 3–2 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.

CSKA Moscow win 100%

10 / 10 models

Nizhny Novgorod 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
CSKA Moscow win
3–2
58%
CSKA Moscow's home advantage and three wins in the last five meetings give them a narrow edge, while Nizhny Novgorod's recent head-to-head competitiveness supports a close, moderate-scoring game.
02
Claude Sonnet 5
CSKA Moscow win
3–2
55%
Recent H2H is split with both sides trading wins; CSKA's home venue and typically strong defensive structure give a slight edge in a close matchup.
03
Gemini 3.8 Flash
CSKA Moscow win
3–2
60%
Recent meetings show closely contested games between the two. CSKA's defensive structure at home should give them a slight edge to edge out Torpedo in a tight battle.
04
Grok 4.6
CSKA Moscow win
3–2
56%
H2H is split and Nizhny won two of the last three in Moscow, so the series is close; CSKA still get a slight home-ice edge in a one-goal KHL game.
05
DeepSeek V4 Pro
CSKA Moscow win
3–2
58%
CSKA's home ice and narrow 3-2 win in the last meeting give a slight edge, but Nizhny Novgorod has won two of the last three in Moscow, so the margin stays tight.
06
Qwen 3.8 Max
CSKA Moscow win
3–2
62%
CSKA won 3 of last 5 H2H including a road win in December; home venue and historical edge support a narrow home victory.
07
Mistral Medium 3.5
CSKA Moscow win
3–2
55%
Close rivalry; home edge and recent 3-2 win favor CSKA.
08
Kimi K3
CSKA Moscow win
3–2
54%
CSKA took the latest meeting 3-2 and has home ice plus stronger pedigree, but Nizhny won twice in Moscow last season, so expect another tight, moderate-scoring contest.
09
GLM 5.3
CSKA Moscow win
3–2
58%
CSKA won three of the last five H2H meetings, including tight low-scoring road wins, and home ice adds an edge; Nizhny keeps games close, so a narrow margin fits.
10
MiMo V2.5 Pro
CSKA Moscow win
3–2
55%
CSKA Moscow's home venue and recent H2H win suggest a slight edge; score based on typical close KHL games with limited current form data.
— Scoreline frequency

How often each scoreline showed up.

10 of 10 models settled on 3–2. That convergence is a strong scoreline signal—many fixtures fan out wider across the panel.

  • 3–2
    10 models

Match overview

Looking for a today prediction on CSKA Moscow vs Nizhny Novgorod 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 CSKA Moscow win, with vote shares roughly 100% / 0% home and away (rounded).

If you are asking who will win CSKA Moscow vs Nizhny Novgorod, 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 CSKA Moscow

100% 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 3.00 vs 2.00

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

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— Journal

Articles linked to these clubs or AI forecasting.

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