Match

Kashima vs Matsumoto Yamaga: result 3-1 and analysis

J1 League1st Stage - 14Kick-off on May 30, 2015 at 10:00 AM (UTC)Kashima Soccer Stadium, Kashima

Kashima
3-1
Matsumoto Yamaga

Full time

What was the result of Kashima vs Matsumoto Yamaga?

Kashima won 3-1 on May 30, 2015.

Goalscorers

  • 5′Ryusuke SakaiMatsumoto Yamaga
  • 7′Shuhei AkasakiKashima
  • 45′Shuhei AkasakiKashima
  • 90′Caio LucasKashima

Official lineup for Kashima vs Matsumoto Yamaga

The starting elevens fielded at kick-off.

Kashima

  1. 7Caio Lucas
  2. 18Shuhei Akasaki
  1. 8S. Doi
  2. 20G. Shibasaki
  3. 25Y. Endo
  4. 40M. Ogasawara
  1. 3G. Shōji
  2. 14Hwang Seok-Ho
  3. 22D. Nishi
  4. 23N. Ueda
  1. 1A. Sato

Matsumoto Yamaga

  1. 9Manuel de Brito Filho
  2. 11K. Kiyama
  3. 22N. Maeda
  1. 5Yudai Iwama
  2. 8Y. Iwakami
  1. 2Y. Okubo
  2. 3Hayuma Tanaka
  3. 4M. Iida
  4. 6S. Iwanuma
  5. 30Ryusuke Sakai
  1. 1T. Murayama
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What is the recent form of both teams?

Over their last 15 matches in all competitions, Kashima have 6 wins, 3 draws and 6 defeats; Matsumoto Yamaga have 5, 3 and 7.

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

Kashima
DateOpponentScoreCompetition
May 23, 2015Urawa(away)1-2J1 League
May 16, 2015Sanfrecce Hiroshima(home)2-2J1 League
May 10, 2015FC Tokyo(away)1-0J1 League
May 2, 2015Ventforet Kofu(home)0-1J1 League
Apr 29, 2015Vegalta Sendai(away)2-1J1 League
Matsumoto Yamaga
DateOpponentScoreCompetition
May 23, 2015Yokohama F. Marinos(home)0-3J1 League
May 20, 2015Shonan Bellmare(away)1-2J-League Cup
May 16, 2015Vissel Kobe(home)2-0J1 League
May 10, 2015Sagan Tosu(away)1-1J1 League
May 6, 2015Ventforet Kofu(home)2-0J1 League

How many goals should we expect?

Kashima score 1.5 and concede 1.3 goals per match over their last 15; Matsumoto Yamaga score 1.1 and concede 1.3.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
Kashima1.51.3112/1510/15
Matsumoto Yamaga1.11.357/156/15

Over the last 15 matches in all competitions.

Where do both teams sit in the table?

2026-27 standings
#ClubPWDLGFGAPts
6Kashima14725292423

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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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