Sagamihara vs Azul Claro Numazu: result 2-2 and analysis
J3 LeagueRegular Season - 7Kick-off on May 7, 2017 at 04:00 AM (UTC)Sagamihara Gion Stadium, Sagamihara
Full time
What was the result of Sagamihara vs Azul Claro Numazu?
Sagamihara and Azul Claro Numazu drew 2-2 on May 7, 2017.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Sagamihara have 3 wins, 3 draws and 9 defeats; Azul Claro Numazu have 10, 0 and 5.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 16, 2017 | Fukushima United(away) | 1-1 | J3 League |
| Apr 1, 2017 | Kitakyushu(home) | 1-0 | J3 League |
| Mar 25, 2017 | Tokyo U23(away) | 0-1 | J3 League |
| Mar 20, 2017 | Gamba Osaka U23(away) | 1-0 | J3 League |
| Mar 12, 2017 | Parceiro Nagano(home) | 0-1 | J3 League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 30, 2017 | Kagoshima United(home) | 2-0 | J3 League |
| Apr 22, 2017 | Saurcos Fukui(home) | 1-0 | Emperor Cup |
| Apr 16, 2017 | Tochigi SC(away) | 1-2 | J3 League |
| Apr 2, 2017 | Kataller Toyama(away) | 3-0 | J3 League |
| Mar 25, 2017 | Fujieda MYFC(home) | 4-1 | J3 League |
How many goals should we expect?
Sagamihara score 0.8 and concede 1.9 goals per match over their last 15; Azul Claro Numazu score 1.5 and concede 0.8.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Sagamihara | 0.8 | 1.9 | 2 | 8/15 | 8/15 |
| Azul Claro Numazu | 1.5 | 0.8 | 7 | 5/15 | 7/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 6 | Sagamihara | 12 | 6 | 3 | 3 | 21 | 14 | 21 |
A question about Sagamihara vs Azul Claro Numazu?
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