Kataller Toyama vs Fujieda MYFC: result 2-0 and analysis
J3 LeagueMatchday 21Kick-off on September 11, 2016 at 08:00 AM (UTC)Toyama Athletic Recreation Park Stadium, Toyama
Full time
What was the result of Kataller Toyama vs Fujieda MYFC?
Kataller Toyama won 2-0 on September 11, 2016.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Kataller Toyama have 6 wins, 3 draws and 6 defeats; Fujieda MYFC have 7, 2 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 3, 2016 | Kashima(away) | 0-3 | Emperor Cup |
| Aug 27, 2016 | Niigata University(home) | 1-0 | Emperor Cup |
| Aug 13, 2016 | Gainare Tottori(home) | 4-1 | J3 League |
| Aug 7, 2016 | Blaublitz Akita(home) | 0-1 | J3 League |
| Jul 31, 2016 | Parceiro Nagano(away) | 0-0 | J3 League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 7, 2016 | Parceiro Nagano(home) | 3-2 | J3 League |
| Jul 31, 2016 | Blaublitz Akita(away) | 0-1 | J3 League |
| Jul 24, 2016 | FC Ryukyu(home) | 4-2 | J3 League |
| Jul 16, 2016 | Oita Trinita(away) | 3-4 | J3 League |
| Jul 10, 2016 | Tokyo U23(home) | 2-1 | J3 League |
What does the head-to-head say?
In the last meeting: 0 Kataller Toyama wins, 0 draws, 1 Fujieda MYFC win.
| Date | Score | Competition |
|---|---|---|
| Jul 3, 2016 | Fujieda MYFC 2-1 Kataller Toyama | J3 League |
Last archived meeting: Fujieda MYFC vs Kataller Toyama on Jul 3, 2016
How many goals should we expect?
Kataller Toyama score 1.0 and concede 1.1 goals per match over their last 15; Fujieda MYFC score 1.6 and concede 1.5.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Kataller Toyama | 1.0 | 1.1 | 4 | 7/15 | 6/15 |
| Fujieda MYFC | 1.6 | 1.5 | 0 | 10/15 | 8/15 |
Over the last 15 matches in all competitions.
A question about Kataller Toyama vs Fujieda MYFC?
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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