Match

Kyoto Sanga vs Imabari: result 3-1 and analysis

Emperor Cup2nd RoundKick-off on June 9, 2021 at 09:00 AM (UTC)Sanga Stadium by Kyocera, Kameoka

Kyoto Sanga
3-1
Imabari

Full time

What was the result of Kyoto Sanga vs Imabari?

Kyoto Sanga won 3-1 on June 9, 2021.

Goalscorers

  • 10′T. LeeKyoto Sanga
  • 62′S. KozukiKyoto Sanga
  • 69′T. LeeKyoto Sanga
  • 82′S. TakeiImabari

Official lineup for Kyoto Sanga vs Imabari

The starting elevens fielded at kick-off.

Kyoto Sanga

  1. 20T. Lee
  1. 10Y. Shoji
  2. 11Y. Soneda
  3. 25K. Nakano
  4. 29K. Nakano
  5. 33N. Misawa
  1. 5Kyohei Kuroki
  2. 15K. Nagai
  3. 28K. Tomita
  4. 41K. Shirai
  1. 21K. Shimizu

Imabari

  1. 10Jun Arima
  2. 15S. Fukuda
  3. 26T. Takase
  1. 6Koichi Miyao
  2. 8Shungo Tamashiro
  3. 20Kazuki Okayama
  1. 5T. Ando
  2. 13R. Ichihara
  3. 17Ó. Linton
  4. 24T. Kondo
  1. 31S. Okada
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What is the recent form of both teams?

Over their last 15 matches in all competitions, Kyoto Sanga have 10 wins, 3 draws and 2 defeats; Imabari have 5, 3 and 7.

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

Kyoto Sanga
DateOpponentScoreCompetition
Jun 6, 2021Tochigi SC(away)0-0J2 League
May 30, 2021Ventforet Kofu(home)0-0J2 League
May 23, 2021Albirex Niigata(away)1-0J2 League
May 16, 2021Mito Hollyhock(home)1-0J2 League
May 9, 2021Montedio Yamagata(home)1-0J2 League
Imabari
DateOpponentScoreCompetition
Jun 5, 2021Parceiro Nagano(home)0-0J3 League
May 30, 2021Vanraure Hachinohe(away)1-2J3 League
May 22, 2021Ehime FC(away)2-1Emperor Cup
May 16, 2021Kamatamare Sanuki(home)1-1J3 League
May 2, 2021Tegevajaro Miyazaki(away)1-2J3 League

How many goals should we expect?

Kyoto Sanga score 1.6 and concede 0.7 goals per match over their last 15; Imabari score 1.3 and concede 1.1.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
Kyoto Sanga1.60.795/155/15
Imabari1.31.139/157/15

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: Kyoto Sanga and Imabari

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