Match

Kyoto Sanga vs Kitakyushu: result 1-0 and analysis

J2 LeagueRegular Season - 16Kick-off on May 26, 2012 at 04:00 AM (UTC)Kyōto Nishikyogoku Stadium, Kyoto

Kyoto Sanga
1-0
Kitakyushu

Full time

What was the result of Kyoto Sanga vs Kitakyushu?

Kyoto Sanga won 1-0 on May 26, 2012.

Goalscorers

  • 37′A. NakamuraKyoto Sanga

Official lineup for Kyoto Sanga vs Kitakyushu

The starting elevens fielded at kick-off.

Kyoto Sanga

  1. 13T. Miyayoshi
  2. 23A. Nakamura
  3. 32W. Sanou
  1. 7Jung Woo-Young
  2. 8J. Ando
  3. 10K. Kudo
  4. 15H. Nakayama
  1. 4Michitaka Akimoto
  2. 16T. Fukumura
  3. 20M. Bajalica
  1. 1Yuichi Mizutani

Kitakyushu

  1. 11Tomoki Ikemoto
  2. 24D. Watari
  1. 3T. Komorida
  2. 5Kim Jong-Pil
  3. 7Y. Kimura
  4. 10K. Yasuda
  5. 13Mitsuhiro Seki
  6. 16T. Tada
  1. 2T. Miyamoto
  2. 4S. Nagano
  1. 1Y. Sato
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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, 1 draw and 4 defeats; Kitakyushu have 6, 2 and 7.

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

Kyoto Sanga
DateOpponentScoreCompetition
May 20, 2012Fagiano Okayama(away)2-1J2 League
May 13, 2012Tokushima Vortis(home)2-1J2 League
May 6, 2012Ventforet Kofu(away)3-0J2 League
May 3, 2012Tochigi SC(home)1-0J2 League
Apr 30, 2012Matsumoto Yamaga(away)0-0J2 League
Kitakyushu
DateOpponentScoreCompetition
May 20, 2012Tokyo Verdy(home)1-5J2 League
May 12, 2012Ehime FC(away)2-2J2 League
May 6, 2012Yokohama FC(home)1-2J2 League
May 3, 2012Machida Zelvia(away)1-0J2 League
Apr 30, 2012JEF United Chiba(home)1-2J2 League

How many goals should we expect?

Kyoto Sanga score 1.5 and concede 0.9 goals per match over their last 15; Kitakyushu score 1.1 and concede 1.3.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
Kyoto Sanga1.50.978/159/15
Kitakyushu1.11.357/157/15

Over the last 15 matches in all competitions.

Where do both teams sit in the table?

2026-27 standings
#ClubPWDLGFGAPts
10Kitakyushu184311173215

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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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