Zarafshon Panjakent vs Regar-TadAZ: result 1-4 and analysis
Vysshaya LigaMatchday 8Kick-off on May 27, 2012 at 12:00 PM (UTC)
Full time
What was the result of Zarafshon Panjakent vs Regar-TadAZ?
Regar-TadAZ won 1-4 on May 27, 2012.
What is the recent form of both teams?
Over their last 6 matches in all competitions, Zarafshon Panjakent have 1 win, 2 draws and 3 defeats; Regar-TadAZ have 12, 2 and 1.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 20, 2012 | Khatlon(away) | 0-4 | Vysshaya Liga |
| May 12, 2012 | CSKA Pomir(home) | 1-1 | Vysshaya Liga |
| Apr 28, 2012 | Parvoz(home) | 2-6 | Vysshaya Liga |
| Apr 21, 2012 | Guardia Dushanbe(away) | 3-0 | Vysshaya Liga |
| Apr 14, 2012 | Barki Tajik(home) | 2-2 | Vysshaya Liga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 19, 2012 | Khujand(home) | 2-0 | Vysshaya Liga |
| May 13, 2012 | Khosilot Farkhor(away) | 2-1 | Vysshaya Liga |
| May 6, 2012 | Khatlon(away) | 1-1 | Vysshaya Liga |
| Apr 29, 2012 | CSKA Pomir(home) | 2-0 | Vysshaya Liga |
| Apr 15, 2012 | Parvoz(home) | 4-1 | Vysshaya Liga |
How many goals should we expect?
Zarafshon Panjakent score 1.3 and concede 2.5 goals per match over their last 6; Regar-TadAZ score 2.7 and concede 0.7.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Zarafshon Panjakent | 1.3 | 2.5 | 1 | 3/6 | 4/6 |
| Regar-TadAZ | 2.7 | 0.7 | 8 | 6/15 | 9/15 |
Over the last 6 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 1 | Regar-TadAZ | 21 | 12 | 7 | 2 | 28 | 12 | 43 |
A question about Zarafshon Panjakent vs Regar-TadAZ?
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