Sagamihara vs Gainare Tottori: result 1-0 and analysis
J3 LeagueRegular Season - 11Kick-off on May 29, 2016 at 04:00 AM (UTC)Sagamihara Gion Stadium, Sagamihara
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What was the result of Sagamihara vs Gainare Tottori?
Sagamihara won 1-0 on May 29, 2016.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Sagamihara have 8 wins, 4 draws and 3 defeats; Gainare Tottori have 4, 4 and 7.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 22, 2016 | Gamba Osaka U23(away) | 1-0 | J3 League |
| May 15, 2016 | Fujieda MYFC(away) | 1-0 | J3 League |
| May 8, 2016 | Blaublitz Akita(home) | 2-2 | J3 League |
| May 1, 2016 | FC Ryukyu(away) | 2-2 | J3 League |
| Apr 24, 2016 | Cerezo Osaka U23(home) | 3-1 | J3 League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 22, 2016 | Fujieda MYFC(home) | 1-3 | J3 League |
| May 15, 2016 | YSCC(away) | 1-0 | J3 League |
| May 8, 2016 | FC Ryukyu(home) | 1-0 | J3 League |
| May 1, 2016 | Parceiro Nagano(away) | 0-0 | J3 League |
| Apr 24, 2016 | Tokyo U23(home) | 0-1 | J3 League |
How many goals should we expect?
Sagamihara score 1.1 and concede 0.9 goals per match over their last 15; Gainare Tottori score 1.1 and concede 1.1.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Sagamihara | 1.1 | 0.9 | 6 | 6/15 | 6/15 |
| Gainare Tottori | 1.1 | 1.1 | 5 | 7/15 | 7/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
Sagamihara sit 4th in J3 League (28 points from 15 matches) and Gainare Tottori sit 17th (15 points from 15 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 4 | Sagamihara | 15 | 8 | 4 | 3 | 25 | 15 | 28 |
| 17 | Gainare Tottori | 15 | 4 | 3 | 8 | 15 | 29 | 15 |
A question about Sagamihara vs Gainare Tottori?
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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