Aral vs Pakhtakor II: result 3-0 and analysis
Pro League ARegular Season - 9Kick-off on June 3, 2026 at 01:00 PM (UTC)Stadion Turon, Nukus
Full time
What was the result of Aral vs Pakhtakor II?
Aral won 3-0 on June 3, 2026.
Goalscorers
- 10′Ruslan KalmagambetovAral
- 36′665194Aral (o.g.)
- 47′Ruslan KalmagambetovAral
What is the recent form of both teams?
Over their last 15 matches in all competitions, Aral have 9 wins, 3 draws and 3 defeats; Pakhtakor II have 1, 1 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 29, 2026 | Qiziriq(away) | 1-0 | Pro League A |
| May 6, 2026 | Yaypan(home) | 5-1 | Pro League A |
| May 1, 2026 | Lochin(away) | 2-2 | Pro League A |
| Apr 26, 2026 | FarDu(home) | 2-0 | Pro League A |
| Apr 21, 2026 | Kattaqurgon(away) | 1-1 | Pro League A |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 30, 2026 | Gazalkent(home) | 1-2 | Pro League A |
| May 22, 2026 | Yaypan(home) | 0-1 | Pro League A |
| May 5, 2026 | Shortan(away) | 0-2 | Pro League A |
| May 1, 2026 | Jayxun(home) | 0-3 | Pro League A |
| Apr 25, 2026 | Metalourg(home) | 0-5 | Pro League A |
How many goals should we expect?
Aral score 1.7 and concede 0.9 goals per match over their last 15; Pakhtakor II score 0.8 and concede 2.1.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Aral | 1.7 | 0.9 | 5 | 8/15 | 7/15 |
| Pakhtakor II | 0.8 | 2.1 | 0 | 3/8 | 4/8 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
Aral sit 1st in Pro League A (55 points from 22 matches) and Pakhtakor II sit 12th (10 points from 22 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 1 | Aral | 22 | 17 | 4 | 1 | 47 | 14 | 55 |
| 12 | Pakhtakor II | 22 | 3 | 1 | 18 | 16 | 51 | 10 |
A question about Aral vs Pakhtakor II?
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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