UNI 1-0 FCS · 57% REN 1-2 MAR · 58% VEN 1-1 FIO · 57% GEN 1-0 FRO · 57% BOR 3-1 SCP · 67% 189 1-1 VFB · 57% SCF 2-1 BOR · 59% FCA 1-2 BAY · 60% FSV 1-1 EIN · 57% CHE 2-0 HUL · 67% LIV 2-1 FUL · 65% AST 2-1 NOT · 62% BOU 1-1 BRE · 57% CRY 1-0 IPS · 60% UNI 1-0 FCS · 57% REN 1-2 MAR · 58% VEN 1-1 FIO · 57% GEN 1-0 FRO · 57% BOR 3-1 SCP · 67% 189 1-1 VFB · 57% SCF 2-1 BOR · 59% FCA 1-2 BAY · 60% FSV 1-1 EIN · 57% CHE 2-0 HUL · 67% LIV 2-1 FUL · 65% AST 2-1 NOT · 62% BOU 1-1 BRE · 57% CRY 1-0 IPS · 60%
World Cup Women · World Cup Women - Quarter-finals Sep 7, 2026 · 18:45 Max-Schmeling-Halle Game Finished

Italy W
vs
China W.

10 AI models read this game. The plurality on the winner leans toward Italy W (9 of 10 models). The mean predicted score (rounded from all models) is 79–74 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

— Consensus

Where the panel lands.

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

Italy W win 90%

9 / 10 models

China W win 10%

1 / 10 models

Advertisement
— 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
Italy W win
79–74
58%
Italy W recently defeated China W 88-76, providing the clearest matchup signal, though the Berlin venue offers limited true home advantage. Expect a competitive, moderately paced game with Italy slightly more efficient late.
02
Claude Sonnet 5
Italy W win
82–75
62%
Italy won the most recent meeting decisively and holds home court; China competitive but Italy's recent form and h2h edge favor a moderate win.
03
Gemini 3.8 Flash
China W win
71–76
58%
China Women possess strong interior size and tactical discipline, giving them a slight edge over Italy in a neutral tournament setting despite Italy's recent warm-up win.
04
Grok 4.6
Italy W win
81–73
61%
Italy beat China 88-76 two weeks earlier in this World Cup cycle; similar matchup at Max-Schmeling-Halle favors Italy again by a single-digit margin.
05
DeepSeek V4 Pro
Italy W win
80–72
60%
Recent H2H (Italy 88-76 in August) and home designation point to Italy; expect a controlled win with China staying within single digits.
06
Qwen 3.8 Max
Italy W win
79–71
62%
Italy W won the most recent H2H convincingly (88-76) and play at a neutral venue with momentum; China W's lower scoring output suggests a moderate Italian win.
07
Mistral Medium 3.5
Italy W win
84–72
65%
Recent H2H shows Italy's 12-point edge; World Cup form favors Italy.
08
Kimi K3
Italy W win
82–74
60%
Italy W won the most recent H2H 88-76 and play at home in Berlin; China W keep games competitive, so expect a solid but not blowout home win.
09
GLM 5.3
Italy W win
78–71
58%
Italy won the recent H2H 88-76 and have home-crowd support at Max-Schmeling-Halle; China's 2023 one-point win is dated, so a modest Italy edge fits.
10
MiMo V2.5 Pro
Italy W win
80–74
60%
Italy won the recent H2H 88-76 and has home venue; scores suggest a moderate margin in the 70s-80s range.
— Scoreline frequency

How often each scoreline showed up.

1 of 6 models settled on 79–74. The rest of the list shows where dissent still lives before kickoff.

  • 79–74
    1 model
  • 82–75
    1 model
  • 84–72
    1 model
  • 80–72
    1 model
  • 79–71
    1 model
  • 80–74
    1 model

Match overview

Looking for a today prediction on Italy W vs China W in World Cup Women? 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 (79 - 74; 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 Italy W win, with vote shares roughly 90% / 10% home and away (rounded).

If you are asking who will win Italy W vs China W, 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 Italy W

90% of models lean home — 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
Expected points tilt 79.60 vs 73.20

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.

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.

Advertisement

Ask multiple AIs about this match.

Compare their answers, read the reasoning, and see where they disagree. Try one question free each day.