Tokyo U23 vs Sagamihara: result 4-1 and analysis
J3 LeagueRegular Season - 27Kick-off on October 30, 2016 at 05:00 AM (UTC)Ajinomoto Field Nishigaoka, Tokyo
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What was the result of Tokyo U23 vs Sagamihara?
Tokyo U23 won 4-1 on October 30, 2016.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Tokyo U23 have 4 wins, 6 draws and 5 defeats; Sagamihara have 2, 4 and 9.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 23, 2016 | Gamba Osaka U23(away) | 1-1 | J3 League |
| Oct 16, 2016 | Kataller Toyama(away) | 0-0 | J3 League |
| Oct 2, 2016 | YSCC(home) | 2-0 | J3 League |
| Sep 25, 2016 | Kagoshima United(away) | 0-1 | J3 League |
| Sep 19, 2016 | Blaublitz Akita(home) | 1-0 | J3 League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 23, 2016 | Kagoshima United(home) | 0-4 | J3 League |
| Oct 16, 2016 | Grulla Morioka(away) | 0-5 | J3 League |
| Oct 2, 2016 | Parceiro Nagano(home) | 1-2 | J3 League |
| Sep 25, 2016 | FC Ryukyu(home) | 1-3 | J3 League |
| Sep 18, 2016 | Tochigi SC(away) | 1-1 | J3 League |
What does the head-to-head say?
In the last meeting: 0 Tokyo U23 wins, 0 draws, 1 Sagamihara win.
| Date | Score | Competition |
|---|---|---|
| Mar 13, 2016 | Sagamihara 1-0 Tokyo U23 | J3 League |
Last archived meeting: Sagamihara vs Tokyo U23 on Mar 13, 2016
How many goals should we expect?
Tokyo U23 score 1.1 and concede 0.9 goals per match over their last 15; Sagamihara score 0.7 and concede 1.9.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Tokyo U23 | 1.1 | 0.9 | 4 | 9/15 | 4/15 |
| Sagamihara | 0.7 | 1.9 | 2 | 8/15 | 8/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 5 | Sagamihara | 10 | 5 | 3 | 2 | 18 | 12 | 18 |
A question about Tokyo U23 vs Sagamihara?
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