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 Uber Arena Game Finished

USA W
vs
Czech Republic W.

10 AI models read this game. The plurality on the winner leans toward USA W (10 of 10 models). The mean predicted score (rounded from all models) is 92–64 at 78% mean confidence (High 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.

USA W win 100%

10 / 10 models

Czech Republic W win 0%

0 / 10 models

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— 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
USA W win
86–64
78%
USA W's sustained international depth and defensive pressure make them clear favorites at Uber Arena. Historical meetings also show a sizable USA advantage, though their age and changing rosters warrant a moderate rather than extreme margin.
02
Claude Sonnet 5
USA W win
95–63
82%
USA W has historically dominated this matchup with elite roster depth and pace; Czech Republic W competitive but overmatched at this level.
03
Gemini 3.8 Flash
USA W win
92–64
92%
USA Women dominate international competition with unmatched athletic depth and elite two-way talent, creating a decisive mismatch against Czech Republic.
04
Grok 4.6
USA W win
89–63
72%
USA W have dominated this matchup historically and remain the World Cup standard; Czech Republic W lack the depth to keep pace at Uber Arena.
05
DeepSeek V4 Pro
USA W win
85–60
62%
USA W's historical dominance and depth suggest a clear win, with a margin consistent with past meetings despite limited 2026 form data.
06
Qwen 3.8 Max
USA W win
92–64
82%
USA W historically dominates Czech Republic W by 20+ points; superior depth and talent gap persists across eras in women's basketball.
07
Mistral Medium 3.5
USA W win
89–67
85%
USA's historical dominance and recent H2H margins support a comfortable win.
08
Kimi K3
USA W win
91–66
84%
USA W's depth and talent far exceed a mid-tier Czech side; H2H meetings (88-61, 89-69) show consistent 20+ point margins, and that athleticism and scoring gap still applies at this neutral-venue World Cup.
09
GLM 5.3
USA W win
92–61
78%
USA W dominated both prior H2H meetings by 20+ points and boast far superior depth and athleticism; Czech Republic W's slower pace limits scoring, supporting a comfortable USA margin.
10
MiMo V2.5 Pro
USA W win
85–65
60%
USA W dominated both prior H2H matchups by 20+ points; home venue advantage in a World Cup setting supports a similar outcome.
— Scoreline frequency

How often each scoreline showed up.

2 of 7 models settled on 92–64. The rest of the list shows where dissent still lives before kickoff.

  • 92–64
    2 models
  • 86–64
    1 model
  • 95–63
    1 model
  • 89–67
    1 model
  • 85–60
    1 model
  • 85–65
    1 model

Match overview

Looking for a today prediction on USA W vs Czech Republic 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 (92 - 64; 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 USA W win, with vote shares roughly 100% / 0% home and away (rounded).

If you are asking who will win USA W vs Czech Republic 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 USA W

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

02
High confidence

Mean 78% across the panel with real dispersion — compare unanimous calls vs split tickets in the model table.

03
Expected points tilt 89.60 vs 63.70

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.

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— Journal

Articles linked to these clubs or AI forecasting.

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