J1 League (Japan), round 11 · Wednesday, 21 October, MSK

Nagoya Grampus — Cerezo Osaka

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Model prediction for 21 October

Nagoya Grampus42%
Draw27%
Cerezo Osaka32%
Model estimate at MSK

Preliminary forecast: the match is more than a week away. Closer to it the model takes in fresh form, injuries and line-ups, and the numbers may move.

In short

Nagoya Grampus are slightly stronger: 42% against 32%, draw 27%.

The model expects plenty of goals: 3.0 in total, against a competition average of 2.6.

Over 2.5 goals — 58%, both teams to score — 63%.

Why

  • By the strength ratings the teams are almost level.

Probabilities

Expected goals: Nagoya Grampus — Cerezo Osaka What is xG?1.6–1.4
Nagoya Grampus not to lose68%
Cerezo Osaka not to lose58%
No draw73%
Both teams to score: yes63%
Both teams to score: no37%
Total over 2.558%
Total under 2.542%

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All totals and handicaps, team totals, corners and cards, the score grid, every factor and how the estimate moved before kick-off.

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Form

Nagoya Grampus

  • 11.10away · Kawasaki Frontale2:1
  • 19.09away · FC Tokyo0:1
  • 12.09away · V-Varen Nagasaki0:2
  • 06.09Machida Zelvia1:3
  • 02.09away · Sanfrecce Hiroshima0:3

Cerezo Osaka

  • 10.10Yokohama F.Marinos0:0
  • 19.09away · V-Varen Nagasaki1:1
  • 12.09away · Sanfrecce Hiroshima1:6
  • 06.09Tokyo Verdy0:0
  • 02.09Kashiwa Reysol2:0

Head to head

  • 17.05.2026Cerezo Osaka — Nagoya Grampus6:1
  • 04.04.2026Nagoya Grampus — Cerezo Osaka3:0
  • 04.10.2025Nagoya Grampus — Cerezo Osaka2:1
  • 08.03.2025Cerezo Osaka — Nagoya Grampus1:1
  • 30.06.2024Cerezo Osaka — Nagoya Grampus2:1

Full record: 8 meetings →

Table

Table «Overall», season 2026/27
#TeamPWDLGoals+/−Pts
11Urawa Red Diamonds940516–21-512
12Cerezo Osaka93337–12-512
13Mito Hollyhock923412–13-19
14V-Varen Nagasaki923411–16-59
15Nagoya Grampus93069–15-69
16Kyoto Sanga FC922511–16-58

Season 2026/27

Full table

J1 League on the same day

This is the model’s statistical estimate, not a recommendation. An outcome at 42% will not happen in roughly 58 matches out of 100. How to read probabilities →