JUV 1-1 ATA · 58% OFI 1-0 AST · 53% VIB 1-2 FCN · 52% SLA 2-1 PLZ · 59% DEP 1-1 REA · 58% VIL 2-1 LEV · 62% ALM 2-0 CEL · 59% LAS 1-0 BUR · 54% CLU 2-1 GEN · 57% KAL 0-2 PAN · 63% EST 1-1 CAS · 51% SAN 0-1 SCB · 57% AME 0-2 BEş · 61% GöZ 1-0 RIZ · 53% JUV 1-1 ATA · 58% OFI 1-0 AST · 53% VIB 1-2 FCN · 52% SLA 2-1 PLZ · 59% DEP 1-1 REA · 58% VIL 2-1 LEV · 62% ALM 2-0 CEL · 59% LAS 1-0 BUR · 54% CLU 2-1 GEN · 57% KAL 0-2 PAN · 63% EST 1-1 CAS · 51% SAN 0-1 SCB · 57% AME 0-2 BEş · 61% GöZ 1-0 RIZ · 53%
NPB Sep 20, 2026 · 05:00 Not Started

Yomiuri Giants
vs
Yakult Swallows.

Quick answer

Who will win Yomiuri Giants vs Yakult Swallows?

10 of 10 AI models pick Yomiuri Giants to win (100%). The mean predicted score is 6–3 at 68% average confidence (medium).

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 Yomiuri Giants (10 of 10 models). The mean predicted score (rounded from all models) is 6–3 at 68% 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 Yomiuri Giants beat Yakult Swallows 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.

Yomiuri Giants win 100%

10 / 10 models

Yakult Swallows 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
Yomiuri Giants win
6–3
78%
Yomiuri dominated all five listed 2026 meetings, including three recent road wins, and now returns home. That sustained matchup edge supports another Giants victory, with Yakult scoring enough to keep the total moderate.
02
Claude Sonnet 5
Yomiuri Giants win
6–3
68%
Giants swept last five head-to-head meetings with strong run production; home venue and recent dominance over Swallows support continued edge.
03
Gemini 3.8 Flash
Yomiuri Giants win
5–3
64%
Yomiuri holds clear dominance in the recent head-to-head series and possesses stronger pitching depth to secure a home victory at the Tokyo Dome.
04
Grok 4.6
Yomiuri Giants win
6–3
62%
Giants won all five recent H2H meetings, often by multiple runs. Home park plus that run of results points to another Yomiuri win at a typical NPB scoring pace.
05
DeepSeek V4 Pro
Yomiuri Giants win
6–3
68%
Yomiuri has won all five recent H2H meetings, scoring 5+ runs each time, and hosts this matchup. Yakult's offense has been limited to 2-3 runs in those games.
06
Qwen 3.8 Max
Yomiuri Giants win
6–3
72%
Giants dominated all five recent H2H meetings convincingly, including three road wins at Yakult. Home venue further strengthens their edge; expect comfortable but not blowout margin.
07
Mistral Medium 3.5
Yomiuri Giants win
6–4
68%
Giants dominate recent H2H (4-1 in last 5) and play at home; Swallows competitive but Giants' form suggests narrow win.
08
Kimi K3
Yomiuri Giants win
6–3
72%
Giants have dominated this matchup recently, winning five straight including high-scoring affairs, and hold home-field advantage at Tokyo Dome.
09
GLM 5.3
Yomiuri Giants win
6–3
62%
Yomiuri have won five straight vs Yakult, averaging 7.4 runs in that span; home venue and dominant H2H form support a clear Giants win despite roster changes.
10
MiMo V2.5 Pro
Yomiuri Giants win
7–4
68%
Giants have won all five recent H2H games, scoring 8+ runs in three, while Swallows struggle defensively; home venue supports Giants' offensive momentum.
— Scoreline frequency

How often each scoreline showed up.

7 of 10 models settled on 6–3. That convergence is a strong scoreline signal—many fixtures fan out wider across the panel.

  • 6–3
    7 models
  • 6–4
    1 model
  • 7–4
    1 model
  • 5–3
    1 model

Match overview

Looking for a today prediction on Yomiuri Giants vs Yakult Swallows in NPB? 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 (6 - 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 Yomiuri Giants win, with vote shares roughly 100% / 0% home and away (rounded).

If you are asking who will win Yomiuri Giants vs Yakult Swallows, 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 Yomiuri Giants

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

02
Medium confidence

Mean 68% across the panel with real dispersion — compare unanimous calls vs split tickets in the model table.

03
Expected runs tilt 6.00 vs 3.20

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.

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.