Obod vs Nasaf: result 0-6 and analysis
Super LeagueRegular Season - 22Kick-off on September 22, 2017 at 11:00 AM (UTC)Stadion Majmuasi (SOK Jar), Tashkent
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What was the result of Obod vs Nasaf?
Nasaf won 0-6 on September 22, 2017.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Obod have 1 win, 1 draw and 13 defeats; Nasaf have 8, 2 and 5.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 17, 2017 | Olmaliq(away) | 0-1 | Super League |
| Sep 7, 2017 | Sogdiana(home) | 2-4 | Super League |
| Aug 26, 2017 | Bunyodkor(away) | 0-2 | Super League |
| Aug 19, 2017 | Buxoro(home) | 2-3 | Super League |
| Aug 12, 2017 | Kokand-1912(away) | 0-1 | Super League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 16, 2017 | Lokomotiv(home) | 2-0 | Super League |
| Sep 8, 2017 | Olmaliq(home) | 1-0 | Super League |
| Aug 18, 2017 | Bunyodkor(home) | 0-1 | Super League |
| Aug 12, 2017 | Buxoro(away) | 0-1 | Super League |
| Aug 6, 2017 | Kokand-1912(home) | 3-0 | Super League |
What does the head-to-head say?
Across the last 3 meetings: 0 Obod wins, 0 draws, 3 Nasaf wins.
| Date | Score | Competition |
|---|---|---|
| Apr 22, 2017 | Nasaf 1-0 Obod | Super League |
| Aug 12, 2016 | Obod 0-3 Nasaf | Super League |
| Apr 1, 2016 | Nasaf 1-0 Obod | Super League |
How many goals should we expect?
Obod score 0.7 and concede 2.5 goals per match over their last 15; Nasaf score 1.4 and concede 0.7.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Obod | 0.7 | 2.5 | 0 | 6/15 | 7/15 |
| Nasaf | 1.4 | 0.7 | 7 | 5/15 | 5/15 |
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 | Nasaf | 23 | 10 | 7 | 6 | 35 | 22 | 37 |
A question about Obod vs Nasaf?
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