YuA-Stroy-DYuSSh vs Uzda: prediction and stats
2. DivisionMatchday 20Kick-off on September 6, 2019 at 12:00 AM (UTC)Stadyen Haradski, Zhitkovichi
Match cancelled
What is the recent form of both teams?
Over their last 15 matches in all competitions, YuA-Stroy-DYuSSh have 2 wins, 4 draws and 9 defeats; Uzda have 8, 0 and 7.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 11, 2019 | NFK Minsk(home) | 0-3 | Coppa |
| Nov 10, 2018 | FC Energetik-Bgu Minsk(away) | 1-5 | 1. Division |
| Nov 3, 2018 | Volna(home) | 1-2 | 1. Division |
| Oct 27, 2018 | Slonim(away) | 0-0 | 1. Division |
| Oct 20, 2018 | Smorgon(home) | 1-0 | 1. Division |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 31, 2019 | Oshmyany(home) | 3-6 | 2. Division |
| Aug 24, 2019 | Čist́(home) | 1-6 | 2. Division |
| Aug 17, 2019 | DYuSSh-3 Pinsk(home) | 2-0 | 2. Division |
| Aug 10, 2019 | Belshina II(home) | 6-3 | 2. Division |
| Jul 24, 2019 | Arsenal(away) | 2-1 | 2. Division |
What does the head-to-head say?
Across the last 6 meetings: 1 YuA-Stroy-DYuSSh win, 1 draw, 4 Uzda wins.
| Date | Score | Competition |
|---|---|---|
| Oct 21, 2017 | YuA-Stroy-DYuSSh 3-1 Uzda | 2. Division |
| Jul 19, 2017 | Uzda 1-1 YuA-Stroy-DYuSSh | 2. Division |
| Aug 29, 2015 | Uzda 7-1 YuA-Stroy-DYuSSh | 2. Division |
| Jun 13, 2015 | YuA-Stroy-DYuSSh 0-6 Uzda | 2. Division |
| Jul 20, 2014 | YuA-Stroy-DYuSSh 2-5 Uzda | 2. Division |
| May 4, 2014 | Uzda 4-0 YuA-Stroy-DYuSSh | 2. Division |
Last archived meeting: YuA-Stroy-DYuSSh vs Uzda on Oct 21, 2017
How many goals should we expect?
YuA-Stroy-DYuSSh score 0.7 and concede 1.8 goals per match over their last 15; Uzda score 2.8 and concede 2.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| YuA-Stroy-DYuSSh | 0.7 | 1.8 | 3 | 7/15 | 8/15 |
| Uzda | 2.8 | 2.3 | 3 | 10/15 | 12/15 |
Over the last 15 matches in all competitions.
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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