Rakvere Tarvas vs Maardu: result 3-4 and analysis
Esiliiga ARegular SeasonKick-off on April 23, 2017 at 04:00 PM (UTC)Rakvere linnastaadion, Rakvere
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What was the result of Rakvere Tarvas vs Maardu?
Maardu won 3-4 on April 23, 2017.
Goalscorers
- 5′Ilja ZelentsovMaardu (pen.)
- 38′Nikita BrõlinMaardu
- 40′H. HangRakvere Tarvas
- 49′Nikita BrõlinMaardu
- 50′Vitali GussevMaardu
- 75′Vitali GussevRakvere Tarvas (o.g.)
- 90′H. HangRakvere Tarvas
What is the recent form of both teams?
Over their last 15 matches in all competitions, Rakvere Tarvas have 3 wins, 3 draws and 9 defeats; Maardu have 7, 2 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 14, 2017 | Tallinna Kalev(home) | 1-1 | Esiliiga A |
| Apr 9, 2017 | FCI Levadia II(away) | 0-0 | Esiliiga A |
| Apr 2, 2017 | Tartu Welco(home) | 4-0 | Esiliiga A |
| Mar 19, 2017 | FCI Tallinn II(away) | 4-3 | Esiliiga A |
| Mar 11, 2017 | Flora II(home) | 0-6 | Esiliiga A |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 16, 2017 | Kuressaare(home) | 5-1 | Esiliiga A |
| Apr 9, 2017 | Tartu Santos(away) | 4-3 | Esiliiga A |
| Apr 2, 2017 | Elva(home) | 1-2 | Esiliiga A |
| Mar 19, 2017 | Flora II(away) | 1-1 | Esiliiga A |
| Mar 11, 2017 | Tallinna Kalev(away) | 1-0 | Esiliiga A |
How many goals should we expect?
Rakvere Tarvas score 0.9 and concede 2.1 goals per match over their last 15; Maardu score 2.3 and concede 2.1.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Rakvere Tarvas | 0.9 | 2.1 | 2 | 5/15 | 8/15 |
| Maardu | 2.3 | 2.1 | 2 | 11/15 | 11/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 7 | Maardu | 24 | 9 | 5 | 10 | 36 | 51 | 32 |
| 8 | Maardu | 15 | 4 | 4 | 7 | 19 | 33 | 16 |
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