Lokomotiv Dryanovo vs Parva atomna: result 2-5 and analysis
Third League - NorthwestRegular Season - 11Kick-off on October 14, 2018 at 01:00 PM (UTC)Stadion Lokomotiv, Dryanovo
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What was the result of Lokomotiv Dryanovo vs Parva atomna?
Parva atomna won 2-5 on October 14, 2018.
What is the recent form of both teams?
Over their last 10 matches in all competitions, Lokomotiv Dryanovo have 1 wins, 0 draws and 9 defeats; Parva atomna have 4, 1 and 5.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 11, 2018 | Spartak Pleven(away) | 1-4 | Third League - Northwest |
| Oct 7, 2018 | Yantra Polski Trambesh(home) | 0-1 | Third League - Northwest |
| Sep 30, 2018 | Kom Berkovitsa(away) | 0-3 | Third League - Northwest |
| Sep 23, 2018 | Vihar Slavyanovo(home) | 0-1 | Third League - Northwest |
| Sep 16, 2018 | Bdin(away) | 1-6 | Third League - Northwest |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 11, 2018 | Akademik Svishtov(home) | 5-1 | Third League - Northwest |
| Oct 7, 2018 | Spartak Pleven(away) | 0-1 | Third League - Northwest |
| Sep 30, 2018 | Tryavna(home) | 1-1 | Third League - Northwest |
| Sep 23, 2018 | Yantra Polski Trambesh(away) | 0-1 | Third League - Northwest |
| Sep 16, 2018 | OFK Levski(home) | 4-0 | Third League - Northwest |
How many goals should we expect?
Lokomotiv Dryanovo score 0.9 and concede 3.2 goals per match over their last 10; Parva atomna score 1.9 and concede 1.5.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Lokomotiv Dryanovo | 0.9 | 3.2 | 1 | 6/10 | 7/10 |
| Parva atomna | 1.9 | 1.5 | 1 | 6/10 | 6/10 |
Over the last 10 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 13 | Lokomotiv Dryanovo | 24 | 4 | 7 | 13 | 22 | 43 | 19 |
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