Match

Japan vs Kyrgyzstan: result 4-0 and analysis

FriendliesFriendlies 1Kick-off on November 20, 2018 at 10:20 AM (UTC)Saitama Stadium 2002, Saitama

Japan
4-0
Kyrgyzstan

Full time

What was the result of Japan vs Kyrgyzstan?

Japan won 4-0 on November 20, 2018.

Goalscorers

  • 2′R. YamanakaJapan
  • 19′G. HaraguchiJapan
  • 72′Y. OsakoJapan
  • 73′S. NakajimaJapan

Official lineup for Japan vs Kyrgyzstan

The starting elevens fielded at kick-off.

Japan

  1. 11K. Sugimoto
  2. 13K. Kitagawa
  3. 14J. Ito
  1. 8G. Haraguchi
  2. 17H. Morita
  3. 18K. Misao
  1. 2G. Miura
  2. 3S. Muroya
  3. 5R. Yamanaka
  4. 20T. Makino
  1. 12S. Gonda

Kyrgyzstan

  1. 19V. Lux
  1. 9E. Bernhardt
  2. 15Murolimzhon Akhmedov
  3. 17Daniel Nii Armah Tagoe
  4. 20Bakhtiyar Duyshobekov
  5. 21Farkhat Musabekov
  1. 2M. Yusupov
  2. 3T. Kozubaev
  3. 5Sherzot Shakirov
  4. 18K. Zhyrgalbek
  1. 1Pavel Matiash
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What is the recent form of both teams?

Over their last 15 matches in all competitions, Japan have 6 wins, 3 draws and 6 defeats; Kyrgyzstan have 9, 2 and 4.

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

Japan
DateOpponentScoreCompetition
Nov 16, 2018Venezuela(home)1-1Friendlies
Oct 16, 2018Uruguay(home)4-3Friendlies
Oct 12, 2018Panama(home)3-0Friendlies
Sep 11, 2018Costa Rica(home)3-0Friendlies
Jul 2, 2018Belgium(away)2-3World Cup
Kyrgyzstan
DateOpponentScoreCompetition
Oct 16, 2018Malaysia(away)1-0Friendlies
Sep 10, 2018Syria(home)2-1Friendlies
Sep 6, 2018Palestine(home)1-1Friendlies
May 29, 2018Azerbaijan(away)0-3Friendlies
Mar 27, 2018India(home)2-1Asian Cup - Qualification

How many goals should we expect?

Japan score 1.7 and concede 1.7 goals per match over their last 15; Kyrgyzstan score 1.5 and concede 1.5.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
Japan1.71.7210/1510/15
Kyrgyzstan1.51.556/159/15

Over the last 15 matches in all competitions.

A question about Japan vs Kyrgyzstan?

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

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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