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 · 00:00 After Over Time

St. Louis Blues
vs
San Jose Sharks.

Quick answer

Who will win St. Louis Blues vs San Jose Sharks?

10 of 10 AI models pick St. Louis Blues to win (100%). The mean predicted score is 3–2 at 57% 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 St. Louis Blues (10 of 10 models). The mean predicted score (rounded from all models) is 3–2 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

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“Will St. Louis Blues beat San Jose Sharks 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.

St. Louis Blues win 100%

10 / 10 models

San Jose Sharks 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
St. Louis Blues win
3–2
56%
St. Louis has won three of the last five meetings and gets home ice, while the recent series has been tight. San Jose’s scoring threat keeps this a modest-confidence, close game rather than a clear mismatch.
02
Claude Sonnet 5
St. Louis Blues win
4–3
55%
Recent meetings were tight and high-scoring; home ice gives Blues a slight edge in a closely matched, offense-leaning series.
03
Gemini 3.8 Flash
St. Louis Blues win
4–2
61%
St. Louis holds superior structural depth and home-ice advantage against a rebuilding San Jose squad that often concedes heavily on the road.
04
Grok 4.6
St. Louis Blues win
3–2
56%
H2H is split and low-margin; early-season context is thin. Home ice and NHL base rates slightly favor St. Louis in a typical one-goal game.
05
DeepSeek V4 Pro
St. Louis Blues win
3–2
55%
Blues have won two of the last three meetings, including a 2-1 home win over San Jose. Home venue and tight H2H scoring support a narrow St. Louis edge.
06
Qwen 3.8 Max
St. Louis Blues win
3–2
55%
Blues won 3 of last 5 H2H meetings and have home ice; Sharks remain competitive but slightly weaker overall this season.
07
Mistral Medium 3.5
St. Louis Blues win
3–2
58%
Recent H2H split but Blues edge at home; Sharks' road form slightly weaker.
08
Kimi K3
St. Louis Blues win
3–2
58%
Blues won two of three recent H2H meetings including a 2-1 home victory, suggesting they match up well at Enterprise Center despite the Sharks' latest 5-4 win.
09
GLM 5.3
St. Louis Blues win
3–2
55%
H2H games are tight one-goal contests with both teams scoring; Blues won two of the last three meetings and get the home edge, but Sharks remain competitive.
10
MiMo V2.5 Pro
St. Louis Blues win
3–2
58%
Recent H2H shows close, high-scoring games; Blues have home advantage and split the last two, suggesting a tight contest with a slight edge.
— Scoreline frequency

How often each scoreline showed up.

8 of 10 models settled on 3–2. That convergence is a strong scoreline signal—many fixtures fan out wider across the panel.

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

Match overview

Looking for a today prediction on St. Louis Blues vs San Jose Sharks 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 (3 - 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 St. Louis Blues win, with vote shares roughly 100% / 0% home and away (rounded).

If you are asking who will win St. Louis Blues vs San Jose Sharks, 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 St. Louis Blues

100% 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 2.10

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.