Shakhtyor Petrikov vs Smorgon: result 4-0 and analysis
1. DivisionRegular Season - 4Kick-off on May 1, 2022 at 03:00 PM (UTC)Stadyen FOK Prypiać, Petryków
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What was the result of Shakhtyor Petrikov vs Smorgon?
Shakhtyor Petrikov won 4-0 on May 1, 2022.
Goalscorers
- 27′V. KurlovichShakhtyor Petrikov
- 53′V. KurlovichShakhtyor Petrikov
- 67′V. KurlovichShakhtyor Petrikov
- 89′M. KovalevichShakhtyor Petrikov (pen.)
What is the recent form of both teams?
Over their last 15 matches in all competitions, Shakhtyor Petrikov have 6 wins, 5 draws and 4 defeats; Smorgon have 5, 3 and 7.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 23, 2022 | Orsha(away) | 9-1 | 1. Division |
| Apr 17, 2022 | Osipovichy(home) | 4-2 | 1. Division |
| Apr 9, 2022 | Naftan(away) | 1-1 | 1. Division |
| Mar 5, 2022 | Volna(away) | 2-3 | Friendlies Clubs |
| Mar 2, 2022 | FC Isloch Minsk R.(away) | 1-3 | Friendlies Clubs |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 22, 2022 | Baranovichi(home) | 3-0 | 1. Division |
| Apr 15, 2022 | Lokomotiv Gomel(away) | 1-4 | 1. Division |
| Apr 10, 2022 | Slonim(home) | 2-0 | 1. Division |
| Nov 28, 2021 | FC Minsk(home) | 1-0 | Premier League |
| Nov 20, 2021 | FC Gomel(away) | 0-0 | Premier League |
How many goals should we expect?
Shakhtyor Petrikov score 2.3 and concede 1.5 goals per match over their last 15; Smorgon score 1.1 and concede 2.0.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Shakhtyor Petrikov | 2.3 | 1.5 | 4 | 11/15 | 10/15 |
| Smorgon | 1.1 | 2.0 | 6 | 7/15 | 8/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 14 | Smorgon | 21 | 6 | 5 | 10 | 24 | 30 | 23 |
| 16 | Smorgon | 12 | 2 | 4 | 6 | 14 | 20 | 10 |
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