Veres Rivne vs Chayka: result 1-0 and analysis
Druha LigaRegular Season - 23Kick-off on May 1, 2019 at 02:00 PM (UTC)Stadion Avanhard, Lutsk
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What was the result of Veres Rivne vs Chayka?
Veres Rivne won 1-0 on May 1, 2019.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Veres Rivne have 7 wins, 5 draws and 3 defeats; Chayka have 4, 4 and 7.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 25, 2019 | Nyva Ternopil(away) | 2-1 | Druha Liga |
| Apr 19, 2019 | Bukovyna(away) | 0-0 | Druha Liga |
| Apr 13, 2019 | Kalush(away) | 0-0 | Druha Liga |
| Apr 6, 2019 | Cherkashchyna-Akademiya(home) | 0-1 | Druha Liga |
| Nov 10, 2018 | Nyva Ternopil(away) | 1-0 | Druha Liga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 25, 2019 | Kalush(home) | 2-1 | Druha Liga |
| Apr 18, 2019 | Nyva Vinnytsya(home) | 2-1 | Druha Liga |
| Apr 13, 2019 | Minai(away) | 2-1 | Druha Liga |
| Apr 6, 2019 | Nyva Vinnytsya(away) | 0-1 | Druha Liga |
| Nov 10, 2018 | Polessya(home) | 0-1 | Druha Liga |
What does the head-to-head say?
Across the last 2 meetings: 1 Veres Rivne win, 1 draw, 0 Chayka wins.
| Date | Score | Competition |
|---|---|---|
| Nov 3, 2018 | Veres Rivne 1-1 Chayka | Druha Liga |
| Sep 1, 2018 | Chayka 0-1 Veres Rivne | Druha Liga |
How many goals should we expect?
Veres Rivne score 0.7 and concede 0.5 goals per match over their last 15; Chayka score 0.8 and concede 1.1.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Veres Rivne | 0.7 | 0.5 | 8 | 4/15 | 2/15 |
| Chayka | 0.8 | 1.1 | 1 | 7/15 | 4/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 3 | Chayka | 30 | 17 | 6 | 7 | 58 | 41 | 57 |
A question about Veres Rivne vs Chayka?
Ask Footlab AI: lineups, absences, player form, stats, how the match could unfold.
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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