Tokyo U23 vs Kataller Toyama: result 0-2 and analysis
J3 LeagueRegular Season - 1Kick-off on March 12, 2017 at 05:00 AM (UTC)Ajinomoto Field Nishigaoka, Tokyo
Full time
What was the result of Tokyo U23 vs Kataller Toyama?
Kataller Toyama won 0-2 on March 12, 2017.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Tokyo U23 have 6 wins, 4 draws and 5 defeats; Kataller Toyama have 6, 5 and 4.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Nov 20, 2016 | Cerezo Osaka U23(home) | 2-0 | J3 League |
| Nov 13, 2016 | Fukushima United(away) | 2-0 | J3 League |
| Nov 5, 2016 | Parceiro Nagano(home) | 1-2 | J3 League |
| Oct 30, 2016 | Sagamihara(home) | 4-1 | J3 League |
| Oct 23, 2016 | Gamba Osaka U23(away) | 1-1 | J3 League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Nov 20, 2016 | Sagamihara(home) | 1-1 | J3 League |
| Nov 13, 2016 | Cerezo Osaka U23(away) | 3-2 | J3 League |
| Nov 6, 2016 | FC Ryukyu(home) | 1-1 | J3 League |
| Oct 30, 2016 | Tochigi SC(away) | 0-2 | J3 League |
| Oct 23, 2016 | Gainare Tottori(away) | 1-0 | J3 League |
What does the head-to-head say?
Across the last 2 meetings: 0 Tokyo U23 wins, 1 draw, 1 Kataller Toyama win.
| Date | Score | Competition |
|---|---|---|
| Oct 16, 2016 | Kataller Toyama 0-0 Tokyo U23 | J3 League |
| Apr 10, 2016 | Tokyo U23 0-3 Kataller Toyama | J3 League |
Last archived meeting: Kataller Toyama vs Tokyo U23 on Oct 16, 2016
How many goals should we expect?
Tokyo U23 score 1.5 and concede 0.9 goals per match over their last 15; Kataller Toyama score 1.1 and concede 1.1.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Tokyo U23 | 1.5 | 0.9 | 5 | 8/15 | 5/15 |
| Kataller Toyama | 1.1 | 1.1 | 6 | 5/15 | 5/15 |
Over the last 15 matches in all competitions.
A question about Tokyo U23 vs Kataller Toyama?
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