Qizilqum vs Navbahor: prediction and stats
Super LeagueRegular Season - 27Kick-off on November 6, 2026 at 04:00 PM (UTC)Yoshlar Sport Majmuasi, Navoiy
The Footlab model makes Navbahor the favourite at 46%, against 28% for a draw and 25% for Qizilqum. The most likely score is 1-1.
This model is measured at 53.9% 1X2 accuracy on a temporal hold-out, against 33.3% for random guessing. See the measured accuracy
Probabilities recomputed on Aug 25, 2026 — the full match card is recomputed continuously until kick-off.
Who will win Qizilqum vs Navbahor?
Navbahor starts as the favourite with a 160-point Elo edge (1,740 vs 1,580).
What is the recent form of both teams?
Over their last 15 matches in all competitions, Qizilqum have 4 wins, 2 draws and 9 defeats; Navbahor have 8, 4 and 3.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 18, 2026 | Sogdiana(away) | 1-2 | Super League |
| Aug 14, 2026 | Mash'al(home) | 2-0 | Super League |
| Aug 8, 2026 | Neftchi(away) | 0-5 | Super League |
| Jul 28, 2026 | Nasaf(away) | 0-1 | Super League |
| Jul 23, 2026 | Navbahor(away) | 1-1 | Super League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 21, 2026 | Nasaf(home) | 1-0 | Super League |
| Aug 14, 2026 | Bunyodkor(home) | 4-3 | Super League |
| Aug 7, 2026 | Surkhon(away) | 1-0 | Super League |
| Aug 2, 2026 | Xorazm(home) | 5-1 | Super League |
| Jul 28, 2026 | Neftchi(away) | 1-1 | Super League |
What does the head-to-head say?
Across the last 6 meetings: 1 Qizilqum win(s), 2 draw(s), 3 Navbahor win(s).
| Date | Score | Competition |
|---|---|---|
| Jul 23, 2026 | Navbahor 1-1 Qizilqum | Super League |
| Sep 27, 2025 | Navbahor 1-0 Qizilqum | Super League |
| May 4, 2025 | Qizilqum 3-2 Navbahor | Super League |
| Nov 22, 2024 | Qizilqum 1-5 Navbahor | Super League |
| Jun 20, 2024 | Navbahor 0-0 Qizilqum | Super League |
| Jul 30, 2023 | Qizilqum 1-2 Navbahor | Super League |
How many goals should we expect?
Qizilqum score 0.7 and concede 1.5 goals per match over their last 15; Navbahor score 1.7 and concede 1.0. The model gives a 43% probability of over 2.5 goals and 48% for both teams to score.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Qizilqum | 0.7 | 1.5 | 4 | 5/15 | 6/15 |
| Navbahor | 1.7 | 1.0 | 6 | 9/15 | 6/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
Qizilqum sit 11th in Super League (13 points from 11 matches) and Navbahor sit 3rd (20 points from 11 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 3 | Navbahor | 11 | 6 | 2 | 3 | 14 | 8 | 20 |
| 4 | Navbahor | 18 | 10 | 4 | 4 | 29 | 17 | 34 |
| 11 | Qizilqum | 11 | 4 | 1 | 6 | 8 | 15 | 13 |
| 12 | Qizilqum | 18 | 6 | 2 | 10 | 16 | 26 | 20 |
Verdict, probable XI and verified absences
The full match card recomputes this prediction continuously until kick-off: multi-market verdict, player-by-player probable XI and web-verified absences.
Open the full match card in the app
No odds, no affiliation: the method is published and the accuracy is measured.
How does Footlab 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. Its accuracy is measured continuously on the predictions actually published. Methodology and measured accuracy
Frequently asked questions
- Who is the favourite for Qizilqum vs Navbahor?
- The Footlab model makes Navbahor the favourite at 46%, against 28% for a draw and 25% for Qizilqum.
- Where and when is Qizilqum vs Navbahor played?
- Qizilqum vs Navbahor is played on November 6, 2026 at 04:00 PM (UTC) at Yoshlar Sport Majmuasi, in the Super League.
- Will there be over 2.5 goals?
- The Footlab model gives a 43% probability of at least three goals in this match.
- How reliable is this prediction?
- The Footlab model is measured at 53.9% correct 1X2 outcomes on a temporal hold-out, against 33.3% for random guessing. The breakdown by competition and Elo gap is published on the accuracy page.