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%
National League · Week 9 Sep 25, 2026 · 17:45 Finished

Ambri-Piotta
vs
Zurich.

Quick answer

Who will win Ambri-Piotta vs Zurich?

Final score: Ambri-Piotta 3–6 Zurich. Before kickoff, 10 of 10 AI models pick Zurich to win (100%); the consensus was right. The AI predicted score was 2–4.

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 (269 games).

10 AI models read this game. The plurality on the winner leans toward Zurich (10 of 10 models). The mean predicted score (rounded from all models) is 2–4 at 60% 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 Ambri-Piotta beat Zurich 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.

Ask the Council Free today · sign in with Google to convene the council
— Consensus

Where the panel lands.

Vote share across models. Read this strip first, then the line-by-line table.

Ambri-Piotta win 0%

0 / 10 models

Zurich win 100%

10 / 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
Zurich win
3–4
62%
Zurich won four of the last five meetings, including the most recent, while Ambri-Piotta retains home-ice advantage. The matchup looks competitive, but Zurich’s recent head-to-head edge supports a narrow away victory.
02
Claude Sonnet 5
Zurich win
2–3
56%
Zurich have won recent H2H meetings and enter as the stronger squad; expect a close, competitive game decided by margin of one.
03
Gemini 3.8 Flash
Zurich win
2–4
68%
Zurich historically controls this matchup with superior offensive depth, consistently putting up multiple goals in Ambri.
04
Grok 4.6
Zurich win
2–3
58%
Zurich took four of the last five H2H meetings, often by a goal or two. Early Week 4 form is thin, so a modest away edge at Ambri fits recent scores.
05
DeepSeek V4 Pro
Zurich win
3–4
62%
Zurich have won four of the last five H2H meetings, including two wins in Ambri, and look the stronger side despite Ambri's home ice.
06
Qwen 3.8 Max
Zurich win
2–4
62%
Zurich won 4 of last 5 H2H meetings, including two convincing away victories at Ambri-Piotta. Their offensive depth consistently overwhelms Ambri's defence in this fixture.
07
Mistral Medium 3.5
Zurich win
4–5
62%
Zurich holds 4-1-1 H2H edge, including recent 4-2 away win; Ambri-Piotta struggles to contain their pace.
08
Kimi K3
Zurich win
2–4
68%
Zurich has won four of the last five head-to-head meetings, including the most recent two, and typically scores 3-4 goals against Ambri-Piotta's defense.
09
GLM 5.3
Zurich win
2–4
60%
Zurich won four of the last five meetings, including 4-2 at Ambri in January, and look the stronger side despite the road venue; moderate edge in a fairly open game.
10
MiMo V2.5 Pro
Zurich win
2–4
62%
Zurich has won 4 of the last 5 meetings, including the most recent, and historically scores well at Ambri. The venue provides some edge, but the pattern favors Zurich.
— Scoreline frequency

How often each scoreline showed up.

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

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

Match overview

Looking for a today prediction on Ambri-Piotta vs Zurich in National League? 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 (2 - 4; 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 Zurich win, with vote shares roughly 0% / 100% home and away (rounded).

If you are asking who will win Ambri-Piotta vs Zurich, 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 Zurich

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

02
Medium confidence

Mean 60% across the panel with real dispersion — compare unanimous calls vs split tickets in the model table.

03
xG tilt 2.40 vs 3.90

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.

Related matches

— 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.