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%
NHL Sep 29, 2026 · 23:00 Finished

Toronto Maple Leafs
vs
Montreal Canadiens.

Quick answer

Who will win Toronto Maple Leafs vs Montreal Canadiens?

Final score: Toronto Maple Leafs 2–3 Montreal Canadiens. Before kickoff, 6 of 10 AI models pick Toronto Maple Leafs to win (60%); the consensus was wrong. The AI predicted score was 4–3.

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

10 AI models read this game. The plurality on the winner leans toward Toronto Maple Leafs (6 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

10 AI models · council in session Live match data · Pro

Still not sure? Ask 10 AIs at once:
“Will Toronto Maple Leafs beat Montreal Canadiens 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.

Toronto Maple Leafs win 60%

6 / 10 models

Montreal Canadiens win 40%

4 / 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
Toronto Maple Leafs win
4–3
52%
Toronto gets the home-ice edge, but Montreal has won four of the last five listed meetings. The recent rivalry pattern supports a competitive, offense-led game with a narrow Maple Leafs victory.
02
Claude Sonnet 5
Toronto Maple Leafs win
4–3
52%
Recent H2H favors Montreal, but Toronto's home venue edge and history of high-scoring meetings suggest a close, back-and-forth game.
03
Gemini 3.8 Flash
Toronto Maple Leafs win
4–2
62%
Toronto's offensive firepower on home ice gives them the advantage against Montreal in an energetic, typical rivalry matchup.
04
Grok 4.6
Toronto Maple Leafs win
3–2
52%
Montreal took four of the last five H2H, but Toronto at home in an early-season NHL date should edge a typical one-goal game rather than another road blowout.
05
DeepSeek V4 Pro
Toronto Maple Leafs win
4–2
58%
Toronto's home edge and need to answer Montreal's recent H2H dominance point to a Leafs win, but Canadiens' strong recent form keeps the margin modest.
06
Qwen 3.8 Max
Montreal Canadiens win
2–3
58%
Montreal won 4 of last 5 H2H meetings including a road win in September 2025; their recent dominance over Toronto in this rivalry is notable despite roster changes.
07
Mistral Medium 3.5
Montreal Canadiens win
4–5
62%
Montreal has won 4 of last 5 H2H, including recent 3-1 and 5-2; Toronto’s home form inconsistent.
08
Kimi K3
Toronto Maple Leafs win
4–3
58%
Montreal won three of the last four H2H meetings, but Toronto's home ice and offensive depth give them a slight edge in what should be a tight, high-scoring rivalry game.
09
GLM 5.3
Montreal Canadiens win
3–4
55%
Montreal has won four of the last five meetings, including three straight over Toronto, and their defence has held the Leafs to 1-2 goals repeatedly; narrow road win fits the rivalry's tight scoring.
10
MiMo V2.5 Pro
Montreal Canadiens win
2–3
58%
Montreal has won the last three head-to-head meetings, showing a recent psychological edge. Toronto's home advantage is offset by Montreal's consistent scoring against them.
— Scoreline frequency

How often each scoreline showed up.

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

  • 4–3
    3 models
  • 4–2
    2 models
  • 2–3
    2 models
  • 4–5
    1 model
  • 3–2
    1 model
  • 3–4
    1 model

Match overview

Looking for a today prediction on Toronto Maple Leafs vs Montreal Canadiens 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 Toronto Maple Leafs win, with vote shares roughly 60% / 40% home and away (rounded).

If you are asking who will win Toronto Maple Leafs vs Montreal Canadiens, 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 Toronto Maple Leafs

60% 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 3.40 vs 3.00

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.

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.