Osaka vs Fagiano Okayama II: result 1-2 and analysis
Japan Football League1st Phase - 14Kick-off on May 29, 2016 at 04:00 AM (UTC)Hanazono Rugby Stadium, Higashiosaka
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What was the result of Osaka vs Fagiano Okayama II?
Fagiano Okayama II won 1-2 on May 29, 2016.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Osaka have 10 wins, 3 draws and 2 defeats; Fagiano Okayama II have 2, 0 and 13.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 22, 2016 | Urayasu(away) | 2-1 | Japan Football League |
| May 15, 2016 | Honda(home) | 2-1 | Japan Football League |
| May 8, 2016 | Azul Claro Numazu(away) | 0-1 | Japan Football League |
| May 3, 2016 | Sony Sendai(home) | 4-3 | Japan Football League |
| Apr 29, 2016 | Vanraure Hachinohe(away) | 2-1 | Japan Football League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 22, 2016 | Honda Lock(home) | 1-2 | Japan Football League |
| May 14, 2016 | Verspah Oita(away) | 2-0 | Japan Football League |
| May 8, 2016 | Biwako Shiga(home) | 1-2 | Japan Football League |
| May 3, 2016 | Nara Club(away) | 0-3 | Japan Football League |
| Apr 29, 2016 | Tokyo Musashino City(home) | 0-1 | Japan Football League |
What does the head-to-head say?
Across the last 2 meetings: 2 Osaka win(s), 0 draw(s), 0 Fagiano Okayama II win(s).
| Date | Score | Competition |
|---|---|---|
| Jun 21, 2015 | Osaka 3-1 Fagiano Okayama II | J3 League |
| Apr 26, 2015 | Fagiano Okayama II 1-5 Osaka | J3 League |
Last archived meeting: Osaka vs Fagiano Okayama II on Jun 21, 2015
How many goals should we expect?
Osaka score 1.9 and concede 0.9 goals per match over their last 15; Fagiano Okayama II score 0.6 and concede 1.9.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Osaka | 1.9 | 0.9 | 5 | 8/15 | 7/15 |
| Fagiano Okayama II | 0.6 | 1.9 | 2 | 5/15 | 8/15 |
Over the last 15 matches in all competitions.
How does Footlab 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. Its accuracy is measured continuously on the predictions actually published. Methodology and measured accuracy