Balvu vs Super Nova: result 0-10 and analysis
1. LigaRegular Season - 9Kick-off on June 1, 2019 at 02:00 PM (UTC)Rugāju stadions, Rugāji
Full time
What was the result of Balvu vs Super Nova?
Super Nova won 0-10 on June 1, 2019.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Balvu have 3 wins, 0 draws and 12 defeats; Super Nova have 12, 0 and 3.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 25, 2019 | Dinamo Rīga / Staicele(away) | 0-4 | 1. Liga |
| May 18, 2019 | Smiltene(home) | 1-6 | 1. Liga |
| May 11, 2019 | Rēzekne FA(away) | 0-6 | 1. Liga |
| May 4, 2019 | New Project(home) | 2-1 | 1. Liga |
| Apr 27, 2019 | Auda(away) | 2-6 | 1. Liga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 26, 2019 | Grobiņa(home) | 5-0 | 1. Liga |
| May 18, 2019 | JDFS Alberts(away) | 1-2 | 1. Liga |
| May 11, 2019 | Tukums(home) | 0-1 | 1. Liga |
| May 4, 2019 | Auda(home) | 1-0 | 1. Liga |
| Apr 27, 2019 | Dinamo Rīga / Staicele(away) | 5-0 | 1. Liga |
What does the head-to-head say?
Across the last 2 meetings: 0 Balvu wins, 0 draws, 2 Super Nova wins.
| Date | Score | Competition |
|---|---|---|
| Sep 22, 2018 | Super Nova 7-1 Balvu | 1. Liga |
| Jun 2, 2018 | Balvu 0-4 Super Nova | 1. Liga |
How many goals should we expect?
Balvu score 0.9 and concede 4.7 goals per match over their last 15; Super Nova score 3.1 and concede 0.9.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Balvu | 0.9 | 4.7 | 2 | 8/15 | 13/15 |
| Super Nova | 3.1 | 0.9 | 9 | 4/15 | 11/15 |
Over the last 15 matches in all competitions.
A question about Balvu vs Super Nova?
Ask Footlab AI: lineups, absences, player form, stats, how the match could unfold.
Sign-in required. No odds displayed, no affiliation: the method is published and the accuracy is measured.
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