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 10, 2026 · 16:10 After Over Time

Dinamo Minsk
vs
Shanghai.

10 AI models read this game. The plurality on the winner leans toward Dinamo Minsk (10 of 10 models). The mean predicted score (rounded from all models) is 4–2 at 66% 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.

Dinamo Minsk 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
Dinamo Minsk win
4–2
68%
Dinamo Minsk has won the two most recent meetings, including 7-5 and 6-1, and home ice supports another advantage. Shanghai can score, but Minsk’s stronger recent head-to-head results suggest a clearer margin than the earlier close games.
02
Claude Sonnet 5
Dinamo Minsk win
4–2
67%
Dinamo Minsk has won 4 of last 5 meetings, including recent high-scoring wins, with home venue advantage supporting a comfortable margin.
03
Gemini 3.8 Flash
Dinamo Minsk win
4–2
68%
Dinamo Minsk have dominated recent home matchups against Shanghai, showing superior offensive depth and high-tempo finishing at Minsk Arena.
04
Grok 4.6
Dinamo Minsk win
4–2
62%
Minsk won all three listed home H2H games, including 7-5 in August; Shanghai’s wins were in China. Home ice and that recent pace favor a clear but not blowout Minsk win.
05
DeepSeek V4 Pro
Dinamo Minsk win
4–2
62%
Dinamo Minsk have won three of the last five H2H meetings, including a 7-5 home win in August, and hold home ice; Shanghai's defence has conceded heavily in Minsk.
06
Qwen 3.8 Max
Dinamo Minsk win
4–2
68%
Dinamo Minsk dominated recent H2H at home (7-5, 6-1, 2-1), showing clear offensive edge over Shanghai on their own ice.
07
Mistral Medium 3.5
Dinamo Minsk win
4–2
70%
Dinamo's recent scoring form against Shanghai and home advantage favor a moderate win.
08
Kimi K3
Dinamo Minsk win
5–3
68%
Dinamo Minsk has won three straight H2H meetings, including 7-5 and 6-1 blowouts, and plays at home; Shanghai's attack scores but their defence leaks against Minsk.
09
GLM 5.3
Dinamo Minsk win
4–2
63%
Minsk won all three home meetings with Shanghai, including 7-5 in August; Shanghai's wins came only on home ice. Venue and H2H edge back Minsk, but Shanghai scores, so a two-goal margin fits.
10
MiMo V2.5 Pro
Dinamo Minsk win
5–3
65%
Dinamo Minsk won the last three home H2H games, including a recent 7-5, indicating high-scoring potential and home dominance.
— Scoreline frequency

How often each scoreline showed up.

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

  • 4–2
    8 models
  • 5–3
    2 models

Match overview

Looking for a today prediction on Dinamo Minsk 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 (4 - 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 Dinamo Minsk win, with vote shares roughly 100% / 0% home and away (rounded).

If you are asking who will win Dinamo Minsk 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 Dinamo Minsk

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 4.20 vs 2.20

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.

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— Journal

Articles linked to these clubs or AI forecasting.

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