Match

Nagoya Grampus vs Doshisha University: result 2-0 and analysis

Emperor Cup2nd RoundKick-off on June 1, 2022 at 10:00 AM (UTC)Toyota Stadium, Toyota

Nagoya Grampus
2-0
Doshisha University

Full time

What was the result of Nagoya Grampus vs Doshisha University?

Nagoya Grampus won 2-0 on June 1, 2022.

Goalscorers

  • 46′H. AbeNagoya Grampus
  • 89′MateusNagoya Grampus

Official lineup for Nagoya Grampus vs Doshisha University

The starting elevens fielded at kick-off.

Nagoya Grampus

  1. 19M. Saitō
  1. 7H. Abe
  2. 14K. Sento
  3. 31H. Yoshida
  4. 34T. Uchida
  5. 44M. Kanazaki
  6. 46R. Ishida
  1. 2Tiago Pagnussat
  2. 3Y. Maruyama
  3. 28A. Yoshida
  1. 21Y. Takeda

Doshisha University

  1. 10S. Iwagishi
  1. 6Yusuke Sento
  2. 7Takashi Koda
  3. 8Keisuke Nakasato
  4. 33Yuto Katori
  5. 11R. Nagasaka
  1. 2Haruto Koike
  2. 3Keito Nakata
  3. 5K. Yamawaki
  4. 20Ryo Koyama
  1. 21Tomohito Koyama
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What is the recent form of both teams?

Over their last 15 matches in all competitions, Nagoya Grampus have 6 wins, 3 draws and 6 defeats; Doshisha University have 1, 0 and 0.

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

Nagoya Grampus
DateOpponentScoreCompetition
May 28, 2022Sanfrecce Hiroshima(away)0-1J1 League
May 25, 2022Avispa Fukuoka(home)1-0J1 League
May 21, 2022Shimizu S-pulse(away)2-1J1 League
May 18, 2022Tokushima Vortis(away)2-0J-League Cup
May 14, 2022Cerezo Osaka(home)1-0J1 League
Doshisha University
DateOpponentScoreCompetition
May 22, 2022Fukui United(away)1-0Emperor Cup

How many goals should we expect?

Nagoya Grampus score 0.9 and concede 1.0 goals per match over their last 15; Doshisha University score 1.0 and concede 0.0.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
Nagoya Grampus0.91.067/156/15
Doshisha University1.00.010/10/1

Over the last 15 matches in all competitions.

A question about Nagoya Grampus vs Doshisha University?

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

Other matches in the same round

Next match: Nagoya Grampus and Doshisha University