Səbail vs Şəmkir: result 1-0 and analysis
Birinci DastaRegular Season - 25Kick-off on April 21, 2017 at 12:00 PM (UTC)ASCO Arena, Baku
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What was the result of Səbail vs Şəmkir?
Səbail won 1-0 on April 21, 2017.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Səbail have 9 wins, 2 draws and 4 defeats; Şəmkir have 10, 1 and 4.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 14, 2017 | Zaqatala(away) | 1-1 | Birinci Dasta |
| Apr 8, 2017 | Rəvan(home) | 3-0 | Birinci Dasta |
| Mar 27, 2017 | Şahdağ(away) | 4-0 | Birinci Dasta |
| Mar 23, 2017 | Şərurspor(home) | 3-0 | Birinci Dasta |
| Mar 16, 2017 | Ağsu(away) | 2-3 | Birinci Dasta |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 14, 2017 | Mingəçevir(home) | 5-1 | Birinci Dasta |
| Apr 9, 2017 | Göyəzən(away) | 2-0 | Birinci Dasta |
| Mar 27, 2017 | Qaradağ Lökbatan(home) | 2-0 | Birinci Dasta |
| Mar 22, 2017 | MOIK(away) | 0-0 | Birinci Dasta |
| Mar 16, 2017 | Imisli FK(home) | 0-2 | Birinci Dasta |
What does the head-to-head say?
In the last meeting: 0 Səbail wins, 0 draws, 1 Şəmkir win.
| Date | Score | Competition |
|---|---|---|
| Nov 17, 2016 | Şəmkir 2-0 Səbail | Birinci Dasta |
How many goals should we expect?
Səbail score 2.7 and concede 1.1 goals per match over their last 15; Şəmkir score 1.9 and concede 0.7.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Səbail | 2.7 | 1.1 | 8 | 5/15 | 10/15 |
| Şəmkir | 1.9 | 0.7 | 9 | 4/15 | 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 |
|---|---|---|---|---|---|---|---|---|
| 3 | Səbail | 4 | 2 | 2 | 0 | 5 | 3 | 8 |
A question about Səbail vs Şəmkir?
Ask Footlab AI: lineups, absences, player form, stats, how the match could unfold.
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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