Match

Tokyo Verdy vs Nagoya Grampus: result 2-1 and analysis

J2 LeagueMatchday 18Kick-off on June 10, 2017 at 06:00 AM (UTC)Ajinomoto Stadium, Chōfu

Tokyo Verdy
2-1
Nagoya Grampus

Full time

What was the result of Tokyo Verdy vs Nagoya Grampus?

Tokyo Verdy won 2-1 on June 10, 2017.

Goalscorers

  • 15′K. SugimoriNagoya Grampus
  • 65′Douglas VieiraTokyo Verdy
  • 67′Douglas VieiraTokyo Verdy

Official lineup for Tokyo Verdy vs Nagoya Grampus

The starting elevens fielded at kick-off.

Tokyo Verdy

  1. 7Alan Pinheiro
  2. 18D. Takagi
  1. 33K. Watanabe
  2. 38R. Kajikawa
  1. 2K. Anzai
  2. 3A. Ibayashi
  3. 4S. Hatanaka
  4. 5T. Taira
  5. 6K. Anzai
  6. 17T. Uchida
  1. 1T. Shibasaki

Nagoya Grampus

  1. 9R. Simović
  1. 7T. Taguchi
  2. 17Yuki Kobayashi
  3. 21Kohei Hattanda
  4. 23R. Aoki
  5. 27K. Sugimori
  6. 29R. Izumi
  1. 3K. Kushibiki
  2. 8Cezar Washington Alves Portela
  3. 15K. Miyahara
  1. 18T. Shibuya
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What is the recent form of both teams?

Over their last 15 matches in all competitions, Tokyo Verdy have 7 wins, 3 draws and 5 defeats; Nagoya Grampus have 8, 3 and 4.

The competition is shown for every match: in pre-season, several of these games are friendlies.

Tokyo Verdy
DateOpponentScoreCompetition
Jun 4, 2017Matsumoto Yamaga(away)1-1J2 League
May 27, 2017V-varen Nagasaki(away)0-1J2 League
May 21, 2017Kyoto Sanga(home)1-2J2 League
May 17, 2017JEF United Chiba(home)3-0J2 League
May 13, 2017Kamatamare Sanuki(away)0-0J2 League
Nagoya Grampus
DateOpponentScoreCompetition
Jun 3, 2017Kanazawa(home)2-3J2 League
May 27, 2017Yokohama FC(away)2-1J2 League
May 21, 2017Ehime FC(away)2-1J2 League
May 17, 2017Machida Zelvia(home)2-1J2 League
May 13, 2017Oita Trinita(away)1-4J2 League

How many goals should we expect?

Tokyo Verdy score 1.4 and concede 0.8 goals per match over their last 15; Nagoya Grampus score 1.8 and concede 1.5.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
Tokyo Verdy1.40.866/156/15
Nagoya Grampus1.81.5112/1511/15

Over the last 15 matches in all competitions.

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Ask Footlab AI: lineups, absences, player form, stats, how the match could unfold.

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Sign-in required. No odds displayed, no affiliation: the method is published and the accuracy is measured.

How does Footlab AI compute this prediction?

The model combines both teams' Elo ratings (anchored by competition pool), their recent form weighted by opponent strength, home advantage and a Poisson matrix for scorelines. When bookmakers publish odds for the match, their consensus is built into the calculation: that is what proved most accurate on past matches. Its accuracy is measured continuously on the predictions actually published. Methodology and measured accuracy

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Next match: Tokyo Verdy and Nagoya Grampus