BOR 2-1 WER · 52% RBL 2-1 EIN · 51% 189 2-1 HAM · 48% SCF 2-0 FCS · 54% FCA 1-3 BAY · 56% FSV 1-2 BAY · 47% UNI 2-0 SVE · 51% 1.F 2-2 BOR · 43% SCP 1-2 VFB · 45% LIV 1-1 MAN · 44% ARS 3-0 LEE · 60% CHE 2-1 BOU · 47% MAN 2-1 TOT · 45% AST 2-1 BRE · 45% BOR 2-1 WER · 52% RBL 2-1 EIN · 51% 189 2-1 HAM · 48% SCF 2-0 FCS · 54% FCA 1-3 BAY · 56% FSV 1-2 BAY · 47% UNI 2-0 SVE · 51% 1.F 2-2 BOR · 43% SCP 1-2 VFB · 45% LIV 1-1 MAN · 44% ARS 3-0 LEE · 60% CHE 2-1 BOU · 47% MAN 2-1 TOT · 45% AST 2-1 BRE · 45%
KHL Sep 30, 2026 · 16:30 Finished

Shanghai
vs
Magnitogorsk.

Quick answer

Who will win Shanghai vs Magnitogorsk?

Final score: Shanghai 4–1 Magnitogorsk. Before kickoff, 10 of 10 AI models pick Magnitogorsk to win (100%); the consensus was wrong. The AI predicted score was 2–4.

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

All 10 AIs agree. When the whole council agrees, it has been right 62% of the time (269 games).

10 AI models read this game. The plurality on the winner leans toward Magnitogorsk (10 of 10 models). The mean predicted score (rounded from all models) is 2–4 at 67% mean confidence (High 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 Shanghai beat Magnitogorsk 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.

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— Consensus

Where the panel lands.

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

Shanghai win 0%

0 / 10 models

Magnitogorsk win 100%

10 / 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
Magnitogorsk win
4–5
78%
Magnitogorsk won the three most recent completed meetings, including a 3-2 result in August and two larger victories. Shanghai’s home venue may narrow the margin, but the visitors remain the stronger projected side.
02
Claude Sonnet 5
Magnitogorsk win
2–4
68%
Magnitogorsk has dominated recent H2H meetings, winning all three by clear margins including a lopsided 6-1 result, showing consistent superiority over Shanghai.
03
Gemini 3.8 Flash
Magnitogorsk win
2–4
72%
Magnitogorsk consistently dominates this matchup with superior offensive depth, as evidenced by consecutive multi-goal victories over Shanghai.
04
Grok 4.6
Magnitogorsk win
2–4
62%
H2H is one-sided for Magnitogorsk including a 3-2 win in August; Shanghai home helps but KHL quality gap still favors the visitors by a couple of goals.
05
DeepSeek V4 Pro
Magnitogorsk win
2–4
68%
Magnitogorsk has dominated recent meetings, winning four of five with multi-goal margins; Shanghai's home edge is unlikely to close that gap.
06
Qwen 3.8 Max
Magnitogorsk win
2–4
72%
Magnitogorsk dominated all recent H2H meetings convincingly, including a 3-2 win just weeks ago and multiple blowouts. Their superior depth and consistent dominance over Shanghai support a comfortable away victory.
07
Mistral Medium 3.5
Magnitogorsk win
4–5
78%
Magnitogorsk dominates H2H, including recent 3-2 and 7-1 over Shanghai/Kunlun. Strong away form.
08
Kimi K3
Magnitogorsk win
2–4
68%
Magnitogorsk dominate H2H, winning last three meetings including 7-3 and 6-1 blowouts. Shanghai's defensive frailty persists despite home ice.
09
GLM 5.3
Magnitogorsk win
4–5
68%
Magnitogorsk has dominated recent H2H, winning all four meetings including 3-2 and 7-3 in Shanghai; their deeper roster still outweighs home venue.
10
MiMo V2.5 Pro
Magnitogorsk win
2–4
68%
Magnitogorsk dominated recent H2H with high-scoring wins, showing superior offense; Shanghai's home venue unlikely to overcome this historical gap.
— Scoreline frequency

How often each scoreline showed up.

7 of 10 models settled on 2–4. That convergence is a strong scoreline signal—many fixtures fan out wider across the panel.

  • 2–4
    7 models
  • 4–5
    3 models

Match overview

Looking for a today prediction on Shanghai vs Magnitogorsk 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 (2 - 4; 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 Magnitogorsk win, with vote shares roughly 0% / 100% home and away (rounded).

If you are asking who will win Shanghai vs Magnitogorsk, 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 Magnitogorsk

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

02
High confidence

Mean 67% across the panel with real dispersion — compare unanimous calls vs split tickets in the model table.

03
xG tilt 2.60 vs 4.30

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

Explore more

Keep browsing today prediction coverage and league hubs.

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— Journal

Articles linked to these clubs or AI forecasting.

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.