Match

Kitakyushu vs Blaublitz Akita: result 0-2 and analysis

J3 LeagueRegular Season - 31Kick-off on November 11, 2018 at 05:00 AM (UTC)Mikuni World Stadium, Kitakyushu

Kitakyushu
0-2
Blaublitz Akita

Full time

What was the result of Kitakyushu vs Blaublitz Akita?

Blaublitz Akita won 0-2 on November 11, 2018.

Goalscorers

  • 8′Y. FujitaBlaublitz Akita
  • 28′N. EguchiBlaublitz Akita

What is the recent form of both teams?

Over their last 15 matches in all competitions, Kitakyushu have 4 wins, 6 draws and 5 defeats; Blaublitz Akita have 5, 4 and 6.

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

Kitakyushu
DateOpponentScoreCompetition
Nov 4, 2018Gainare Tottori(away)1-1J3 League
Oct 28, 2018Grulla Morioka(home)2-1J3 League
Oct 21, 2018Tokyo U23(home)0-0J3 League
Oct 13, 2018Sagamihara(away)0-1J3 League
Oct 6, 2018FC Ryukyu(away)0-1J3 League
Blaublitz Akita
DateOpponentScoreCompetition
Nov 4, 2018Cerezo Osaka U23(home)1-4J3 League
Oct 28, 2018YSCC(away)1-3J3 League
Oct 14, 2018Tokyo U23(away)0-1J3 League
Oct 7, 2018Thespakusatsu Gunma(home)0-1J3 League
Sep 29, 2018Kagoshima United(away)2-2J3 League

What does the head-to-head say?

Across the last 3 meetings: 0 Kitakyushu wins, 1 draw, 2 Blaublitz Akita wins.

DateScoreCompetition
May 3, 2018Blaublitz Akita 1-0 KitakyushuJ3 League
Oct 22, 2017Blaublitz Akita 1-0 KitakyushuJ3 League
Mar 12, 2017Kitakyushu 1-1 Blaublitz AkitaJ3 League

Last archived meeting: Blaublitz Akita vs Kitakyushu on May 3, 2018

How many goals should we expect?

Kitakyushu score 0.9 and concede 0.8 goals per match over their last 15; Blaublitz Akita score 1.3 and concede 1.3.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
Kitakyushu0.90.856/155/15
Blaublitz Akita1.31.339/158/15

Over the last 15 matches in all competitions.

Where do both teams sit in the table?

2026-27 standings
#ClubPWDLGFGAPts
16Kitakyushu12345162113

A question about Kitakyushu vs Blaublitz Akita?

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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