Montana vs Nesebar: result 1-3 and analysis
Second LeagueRegular Season - 7Kick-off on September 9, 2017 at 02:00 PM (UTC)Stadion Ogosta, Montana
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What was the result of Montana vs Nesebar?
Nesebar won 1-3 on September 9, 2017.
Goalscorers
- 5′A. IlievMontana
- 6′I. KolevNesebar
- 11′Z. PehlivanovNesebar
- 38′I. KolevNesebar
What is the recent form of both teams?
Over their last 6 matches in all competitions, Montana have 2 wins, 1 draws and 3 defeats; Nesebar 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 |
|---|---|---|---|
| Aug 26, 2017 | Chernomorets Balchik(away) | 0-1 | Second League |
| Aug 20, 2017 | Neftochimic Burgas(home) | 4-0 | Second League |
| Aug 12, 2017 | Lokomotiv Sofia(away) | 0-1 | Second League |
| Aug 7, 2017 | Maritsa Plovdiv(home) | 2-1 | Second League |
| Jul 29, 2017 | Strumska Slava(away) | 0-1 | Second League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 27, 2017 | Oborishte(home) | 2-1 | Second League |
| Aug 21, 2017 | Botev Vratsa(away) | 1-1 | Second League |
| Aug 13, 2017 | Ludogorets II(home) | 3-1 | Second League |
| Aug 5, 2017 | Botev Galabovo(away) | 1-2 | Second League |
| Jul 29, 2017 | Sozopol(home) | 0-0 | Second League |
How many goals should we expect?
Montana score 1.0 and concede 0.7 goals per match over their last 6; Nesebar score 1.3 and concede 1.6.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Montana | 1.0 | 0.7 | 2 | 1/6 | 2/6 |
| Nesebar | 1.3 | 1.6 | 3 | 8/15 | 10/15 |
Over the last 6 matches in all competitions.
Where do both teams sit in the table?
Montana sit 8th in Second League (7 points from 5 matches) and Nesebar sit 3rd (9 points from 5 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 3 | Nesebar | 5 | 3 | 0 | 2 | 12 | 8 | 9 |
| 8 | Montana | 5 | 2 | 1 | 2 | 9 | 8 | 7 |
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