Match

Gamba Osaka vs Tokyo Verdy: result 0-0 and analysis

J2 LeagueRegular Season - 7Kick-off on April 7, 2013 at 05:00 AM (UTC)Saitama Stadium 2002, Saitama

Gamba Osaka
0-0
Tokyo Verdy

Full time

What was the result of Gamba Osaka vs Tokyo Verdy?

Gamba Osaka and Tokyo Verdy drew 0-0 on April 7, 2013.

Official lineup for Gamba Osaka vs Tokyo Verdy

The starting elevens fielded at kick-off.

Gamba Osaka

  1. 9Leandro Montera da Silva
  2. 41A. Ienaga
  1. 6S. Kurata
  2. 7Y. Endō
  3. 10T. Futagawa
  1. 4H. Fujiharu
  2. 8K. Iwashita
  3. 15Y. Konno
  4. 21Akira Kaji
  5. 26Takaharu Nishino
  1. 1Yosuke Fujigaya

Tokyo Verdy

  1. 16K. Iio
  2. 17S. Tokiwa
  3. 44N. Takahara
  1. 5Kim Jong-Pil
  2. 11Norihiro Nishi
  3. 14J. Suzuki
  4. 15J. Koike
  5. 19Yusuke Mori
  1. 3R. Tone
  2. 6Ryoji Fukui
  1. 1Y. Sato
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What is the recent form of both teams?

Over their last 15 matches in all competitions, Gamba Osaka have 6 wins, 7 draws and 2 defeats; Tokyo Verdy have 3, 7 and 5.

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

Gamba Osaka
DateOpponentScoreCompetition
Mar 31, 2013Consadole Sapporo(away)3-1J2 League
Mar 24, 2013JEF United Chiba(home)1-1J2 League
Mar 20, 2013Roasso Kumamoto(away)2-2J2 League
Mar 17, 2013Yokohama FC(home)0-0J2 League
Mar 10, 2013V-varen Nagasaki(away)3-1J2 League
Tokyo Verdy
DateOpponentScoreCompetition
Mar 31, 2013FC Gifu(home)3-0J2 League
Mar 24, 2013Roasso Kumamoto(home)1-1J2 League
Mar 20, 2013Kitakyushu(away)1-1J2 League
Mar 17, 2013Fagiano Okayama(home)1-1J2 League
Mar 10, 2013Kyoto Sanga(away)0-0J2 League

How many goals should we expect?

Gamba Osaka score 1.8 and concede 1.3 goals per match over their last 15; Tokyo Verdy score 1.1 and concede 1.0.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
Gamba Osaka1.81.3212/1510/15
Tokyo Verdy1.11.038/154/15

Over the last 15 matches in all competitions.

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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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