Rəvan vs Şahdağ: result 0-3 and analysis
Birinci DastaRegular Season - 26Kick-off on April 26, 2017 at 10:00 PM (UTC)Bayıl Arena, Baku
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What was the result of Rəvan vs Şahdağ?
Şahdağ won 0-3 on April 26, 2017.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Rəvan have 3 wins, 2 draws and 10 defeats; Şahdağ have 4, 3 and 8.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 12, 2017 | Ağsu(home) | 0-3 | Birinci Dasta |
| Apr 8, 2017 | Səbail(away) | 0-3 | Birinci Dasta |
| Mar 25, 2017 | Mingəçevir(home) | 0-3 | Birinci Dasta |
| Mar 22, 2017 | Göyəzən(away) | 0-3 | Birinci Dasta |
| Mar 16, 2017 | Qaradağ Lökbatan(home) | 0-3 | Birinci Dasta |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 21, 2017 | Turan(home) | 1-1 | Birinci Dasta |
| Apr 13, 2017 | Şərurspor(home) | 3-0 | Birinci Dasta |
| Apr 8, 2017 | Ağsu(away) | 1-4 | Birinci Dasta |
| Mar 30, 2017 | Bakılı(home) | 3-0 | Birinci Dasta |
| Mar 27, 2017 | Səbail(home) | 0-4 | Birinci Dasta |
What does the head-to-head say?
Across the last 3 meetings: 1 Rəvan win, 0 draws, 2 Şahdağ wins.
| Date | Score | Competition |
|---|---|---|
| Nov 25, 2016 | Şahdağ 4-1 Rəvan | Birinci Dasta |
| May 27, 2015 | Rəvan 1-0 Şahdağ | Birinci Dasta |
| Nov 22, 2014 | Şahdağ 1-0 Rəvan | Birinci Dasta |
How many goals should we expect?
Rəvan score 0.9 and concede 2.7 goals per match over their last 15; Şahdağ score 1.3 and concede 1.6.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Rəvan | 0.9 | 2.7 | 1 | 7/15 | 13/15 |
| Şahdağ | 1.3 | 1.6 | 4 | 6/15 | 9/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 1 | Şahdağ | 4 | 4 | 0 | 0 | 13 | 1 | 12 |
A question about Rəvan vs Şahdağ?
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