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 Oct 4, 2026 · 22:00 Finished

New York Rangers
vs
Utah Mammoth.

Quick answer

Who will win New York Rangers vs Utah Mammoth?

Final score: New York Rangers 4–2 Utah Mammoth. Before kickoff, 5 of 10 AI models pick New York Rangers to win (50%); the consensus was right. 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 New York Rangers (5 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?

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

Still not sure? Ask 10 AIs at once:
“Will New York Rangers beat Utah Mammoth 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.

New York Rangers win 50%

5 / 10 models

Utah Mammoth win 50%

5 / 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
New York Rangers win
3–2
52%
Recent meetings are consistently close, with Utah winning the last two but New York having home ice here. Limited current-season context supports a cautious, tight-scoring Rangers victory.
02
Claude Sonnet 5
New York Rangers win
4–3
55%
Recent H2H meetings have been tight and high-scoring; home-ice edge at Madison Square Garden gives Rangers a slight advantage in a close, offense-leaning matchup.
03
Gemini 3.8 Flash
New York Rangers win
4–2
61%
The Rangers hold home-ice advantage at Madison Square Garden and possess superior offensive depth to control possession against a resilient Utah side.
04
Grok 4.6
Utah Mammoth win
2–3
56%
Utah took the last two meetings, including 3-2 at MSG; thin 2026 form data, so a one-goal away edge over a typical Rangers home night.
05
DeepSeek V4 Pro
New York Rangers win
4–3
58%
Rangers' home ice and recent H2H scoring pace suggest a narrow, higher-scoring edge; Utah has won two straight but struggles to hold leads on the road.
06
Qwen 3.8 Max
Utah Mammoth win
2–3
52%
Utah won 3 of last 4 H2H meetings, including both 2025-26 matchups. Limited season context for 2026-27 keeps confidence moderate.
07
Mistral Medium 3.5
Utah Mammoth win
4–5
60%
Utah Mammoth won 3 of last 4 H2H, including recent 3-2 away; Rangers' home form less dominant.
08
Kimi K3
Utah Mammoth win
2–3
58%
Utah has won three of the last four meetings, including both 2026 clashes, and their structured defensive game matches up well against the Rangers' inconsistent attack. Expect another tight, low-scoring contest decided by one goal.
09
GLM 5.3
New York Rangers win
4–3
52%
H2H games are tight, high-event affairs with Utah winning three of four, but Madison Square Garden home edge and Rangers' deeper roster tip a narrow one-goal game.
10
MiMo V2.5 Pro
Utah Mammoth win
3–4
58%
Utah has won the last two meetings and the H2H trend shows high-scoring games. Rangers' home advantage is offset by Utah's recent edge in this matchup.
— 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
  • 2–3
    3 models
  • 3–2
    1 model
  • 4–5
    1 model
  • 3–4
    1 model
  • 4–2
    1 model

Match overview

Looking for a today prediction on New York Rangers vs Utah Mammoth 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 New York Rangers win, with vote shares roughly 50% / 50% home and away (rounded).

If you are asking who will win New York Rangers vs Utah Mammoth, 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 New York Rangers

50% 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 3.20 vs 3.10

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.