Mash'al vs Obod: result 3-0 and analysis
Super LeagueRegular Season - 12Kick-off on May 26, 2017 at 01:30 PM (UTC)Stadion im. Bahrom Vafoyev, Mubarek
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What was the result of Mash'al vs Obod?
Mash'al won 3-0 on May 26, 2017.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Mash'al have 5 wins, 5 draws and 5 defeats; Obod have 3, 5 and 7.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 18, 2017 | Nasaf(away) | 0-1 | Super League |
| May 13, 2017 | Olmaliq(home) | 0-0 | Super League |
| May 6, 2017 | Sogdiana(away) | 0-3 | Super League |
| Apr 28, 2017 | Bunyodkor(home) | 1-0 | Super League |
| Apr 22, 2017 | Buxoro(away) | 2-2 | Super League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 18, 2017 | Dinamo Samarqand(home) | 3-1 | Super League |
| May 12, 2017 | Neftchi(away) | 0-1 | Super League |
| May 6, 2017 | Qizilqum(home) | 1-1 | Super League |
| Apr 29, 2017 | Lokomotiv(away) | 0-7 | Super League |
| Apr 22, 2017 | Nasaf(away) | 0-1 | Super League |
What does the head-to-head say?
Across the last 2 meetings: 2 Mash'al win(s), 0 draw(s), 0 Obod win(s).
| Date | Score | Competition |
|---|---|---|
| Oct 24, 2016 | Obod 0-1 Mash'al | Super League |
| Jun 10, 2016 | Mash'al 5-0 Obod | Super League |
How many goals should we expect?
Mash'al score 0.9 and concede 0.8 goals per match over their last 15; Obod score 0.7 and concede 1.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Mash'al | 0.9 | 0.8 | 7 | 3/15 | 3/15 |
| Obod | 0.7 | 1.3 | 3 | 6/15 | 3/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 16 | Mash'al | 11 | 0 | 0 | 11 | 4 | 21 | 0 |
| 16 | Mash'al | 18 | 1 | 1 | 16 | 8 | 32 | 4 |
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