CHI 1-1 NEW · 38% STA 1-0 ANG · 45% LOR 2-1 PAR · 44% MON 2-1 TOU · 47% PAR 3-0 LEM · 69% NAP 2-0 FRO · 58% REA 2-1 VIL · 52% BRO 1-1 DAL · 36% POR 1-0 BOI · 41% UNI 1-0 FOR · 44% CHA 1-1 LOU · 39% TAM 1-1 CAR · 37% DET 1-0 RHO · 39% IND 1-1 TAM · 37% CHI 1-1 NEW · 38% STA 1-0 ANG · 45% LOR 2-1 PAR · 44% MON 2-1 TOU · 47% PAR 3-0 LEM · 69% NAP 2-0 FRO · 58% REA 2-1 VIL · 52% BRO 1-1 DAL · 36% POR 1-0 BOI · 41% UNI 1-0 FOR · 44% CHA 1-1 LOU · 39% TAM 1-1 CAR · 37% DET 1-0 RHO · 39% IND 1-1 TAM · 37%
NHL Oct 9, 2026 · 02:00 After Penalties

Vegas Golden Knights
vs
Toronto Maple Leafs.

Quick answer

Who will win Vegas Golden Knights vs Toronto Maple Leafs?

10 of 10 AI models pick Vegas Golden Knights to win (100%). The mean predicted score is 4–3 at 58% average confidence (medium).

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 (292 games).

10 AI models read this game. The plurality on the winner leans toward Vegas Golden Knights (10 of 10 models). The mean predicted score (rounded from all models) is 4–3 at 58% 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 Vegas Golden Knights beat Toronto Maple Leafs 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.

Vegas Golden Knights win 100%

10 / 10 models

Toronto Maple Leafs win 0%

0 / 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
Vegas Golden Knights win
4–3
57%
Vegas has won four of the last five meetings, including both 2026 encounters, and home ice supports a narrow edge. Toronto’s high-end attack makes a close, high-scoring game more likely than a comfortable result.
02
Claude Sonnet 5
Vegas Golden Knights win
4–3
57%
Vegas has won the last three meetings including both 2026 games, high-scoring trend continues, home ice adds slight edge.
03
Gemini 3.8 Flash
Vegas Golden Knights win
4–3
56%
Vegas holds a dominant recent head-to-head record against Toronto, often exploiting the Leafs' transition defense in high-scoring home matchups.
04
Grok 4.6
Vegas Golden Knights win
4–3
58%
Vegas won four of five recent H2H, including both listed home games in high-scoring affairs; home ice plus that pattern favors a one-goal Knights win.
05
DeepSeek V4 Pro
Vegas Golden Knights win
4–2
58%
Vegas has won four of the last five head-to-head meetings, including both 2026 games with high scoring. Home venue and recent H2H dominance support a Golden Knights edge.
06
Qwen 3.8 Max
Vegas Golden Knights win
4–2
58%
Vegas dominated recent H2H (4 of last 5 wins, often by multiple goals) and holds home ice. Early-season context limits certainty, but historical edge supports a comfortable home win.
07
Mistral Medium 3.5
Vegas Golden Knights win
4–3
60%
Vegas outscored Toronto in 4 of last 5 meetings; home ice and recent high-scoring form favor Knights.
08
Kimi K3
Vegas Golden Knights win
4–3
62%
Vegas has won three of the last four meetings, all high-scoring, and Toronto's defense has leaked goals in this matchup; home ice tilts a tight, fast game.
09
GLM 5.3
Vegas Golden Knights win
4–3
55%
Vegas won four of the last five meetings, including high-scoring home wins over Toronto; both teams play fast, so expect goals with a narrow home edge.
10
MiMo V2.5 Pro
Vegas Golden Knights win
4–3
58%
Recent H2H shows high-scoring, Vegas-dominated games; home venue and offensive firepower give them a slight edge in a likely close, high-tempo matchup.
— Scoreline frequency

How often each scoreline showed up.

8 of 10 models settled on 4–3. That convergence is a strong scoreline signal—many fixtures fan out wider across the panel.

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

Match overview

Looking for a today prediction on Vegas Golden Knights vs Toronto Maple Leafs in NHL? 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 Vegas Golden Knights win, with vote shares roughly 100% / 0% home and away (rounded).

If you are asking who will win Vegas Golden Knights vs Toronto Maple Leafs, 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 Vegas Golden Knights

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

02
Medium confidence

Mean 58% across the panel with real dispersion — compare unanimous calls vs split tickets in the model table.

03
xG tilt 4.00 vs 2.80

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.