Fukushima United vs Kitakyushu: result 0-3 and analysis
J3 LeagueRegular Season - 13Kick-off on June 18, 2017 at 06:00 AM (UTC)TOHO Stadium, Fukushima
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What was the result of Fukushima United vs Kitakyushu?
Kitakyushu won 0-3 on June 18, 2017.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Fukushima United have 5 wins, 1 draw and 9 defeats; Kitakyushu have 6, 3 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 10, 2017 | Kagoshima United(away) | 1-2 | J3 League |
| Jun 4, 2017 | Fujieda MYFC(home) | 1-2 | J3 League |
| May 28, 2017 | Gainare Tottori(away) | 2-1 | J3 League |
| May 21, 2017 | Tochigi SC(away) | 1-2 | J3 League |
| May 14, 2017 | Blaublitz Akita(home) | 0-2 | J3 League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 10, 2017 | Gamba Osaka U23(home) | 2-1 | J3 League |
| Jun 4, 2017 | Azul Claro Numazu(away) | 0-1 | J3 League |
| May 28, 2017 | Tokyo U23(home) | 1-0 | J3 League |
| May 21, 2017 | Fujieda MYFC(away) | 0-2 | J3 League |
| May 14, 2017 | Gainare Tottori(home) | 2-0 | J3 League |
How many goals should we expect?
Fukushima United score 0.9 and concede 1.5 goals per match over their last 15; Kitakyushu score 1.6 and concede 1.2.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Fukushima United | 0.9 | 1.5 | 3 | 7/15 | 6/15 |
| Kitakyushu | 1.6 | 1.2 | 5 | 6/15 | 7/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
Fukushima United sit 18th in J3 League (8 points from 11 matches) and Kitakyushu sit 14th (13 points from 11 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 14 | Kitakyushu | 11 | 3 | 4 | 4 | 15 | 19 | 13 |
| 18 | Fukushima United | 11 | 2 | 2 | 7 | 20 | 26 | 8 |
A question about Fukushima United vs Kitakyushu?
Ask Footlab AI: lineups, absences, player form, stats, how the match could unfold.
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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