COM 1-0 PAR · 57% TOR 0-1 ASR · 57% INT 2-1 UDI · 63% LEE 1-1 NEW · 57% VIL 1-1 REA · 57% RAY 1-1 ESP · 57% ALA 1-1 VAL · 56% ELC 0-2 REA · 68% ATL 1-0 OSA · 63% BAR 2-0 RAC · 70% REA 2-1 GET · 59% DEP 0-1 SEV · 58% LEV 1-2 ATH · 61% MAL 1-2 VIL · 57% COM 1-0 PAR · 57% TOR 0-1 ASR · 57% INT 2-1 UDI · 63% LEE 1-1 NEW · 57% VIL 1-1 REA · 57% RAY 1-1 ESP · 57% ALA 1-1 VAL · 56% ELC 0-2 REA · 68% ATL 1-0 OSA · 63% BAR 2-0 RAC · 70% REA 2-1 GET · 59% DEP 0-1 SEV · 58% LEV 1-2 ATH · 61% MAL 1-2 VIL · 57%
NPB Sep 13, 2026 · 09:00 Not Started

Yokohama BayStars
vs
Yomiuri Giants.

10 AI models read this game. The plurality on the winner leans toward Yokohama BayStars (10 of 10 models). The mean predicted score (rounded from all models) is 4–3 at 57% 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 Yokohama BayStars beat Yomiuri Giants 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.

Yokohama BayStars win 100%

10 / 10 models

Yomiuri Giants 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
Yokohama BayStars win
3–2
54%
Yokohama has won two of the three most recent meetings, including a 2-1 result, and home venue supports a narrow edge. The recent series suggests a relatively low-scoring, closely contested game.
02
Claude Sonnet 5
Yokohama BayStars win
4–3
56%
BayStars won 3 of last 5 head-to-head meetings including the most recent, with home advantage tipping a close, low-scoring contest.
03
Gemini 3.8 Flash
Yokohama BayStars win
4–3
56%
Recent head-to-head meetings have consistently been tight, low-scoring one-run games, giving the BayStars a slight edge at home.
04
Grok 4.6
Yokohama BayStars win
4–3
56%
BayStars won 3 of last 5 H2H and host at Yokohama; those meetings were mostly one-run, low-to-mid scoring, so a tight 4-3 home edge fits.
05
DeepSeek V4 Pro
Yokohama BayStars win
4–3
58%
Yokohama won three of the last five meetings and host this one; recent head-to-head games have been tight, supporting a narrow one-run home result.
06
Qwen 3.8 Max
Yokohama BayStars win
3–2
58%
BayStars won 3 of last 5 H2H including the most recent meeting; home venue and low-scoring trend in this matchup support a narrow home edge.
07
Mistral Medium 3.5
Yokohama BayStars win
4–3
60%
Close H2H; home edge and recent BayStars form suggest narrow win.
08
Kimi K3
Yokohama BayStars win
4–3
58%
BayStars took the latest meeting 2-1 and three of the last five, all tight one-run games; home edge in a low-scoring rivalry favors Yokohama narrowly.
09
GLM 5.3
Yokohama BayStars win
4–3
55%
BayStars lead recent H2H 3-2 and host at Yokohama; games between these sides are consistently tight, low-scoring one-run affairs, so a narrow home edge fits.
10
MiMo V2.5 Pro
Yokohama BayStars win
3–2
58%
Home advantage and recent H2H win for BayStars support a narrow victory; games between these teams are consistently low-scoring and tight.
— Scoreline frequency

How often each scoreline showed up.

7 of 10 models settled on 4–3. That convergence is a strong scoreline signal—many fixtures fan out wider across the panel.

  • 4–3
    7 models
  • 3–2
    3 models

Match overview

Looking for a today prediction on Yokohama BayStars vs Yomiuri Giants 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 (4 - 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 Yokohama BayStars win, with vote shares roughly 100% / 0% home and away (rounded).

If you are asking who will win Yokohama BayStars vs Yomiuri Giants, 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 Yokohama BayStars

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
Expected runs tilt 3.70 vs 2.70

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.

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.

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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.