Sloga Mravince vs Zagora: result 1-0 and analysis
Third NL - JugSouth - 6Kick-off on September 29, 2019 at 02:00 PM (UTC)Stadion Glavica, Mravince
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What was the result of Sloga Mravince vs Zagora?
Sloga Mravince won 1-0 on September 29, 2019.
What is the recent form of both teams?
Over their last 7 matches in all competitions, Sloga Mravince have 4 wins, 1 draw and 2 defeats; Zagora have 2, 2 and 4.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 22, 2019 | Neretvanac Opuzen(away) | 3-2 | Third NL - Jug |
| Sep 18, 2019 | NK Zadar(home) | 1-1 | Third NL - Jug |
| Sep 14, 2019 | Uskok Klis(away) | 2-1 | Third NL - Jug |
| Sep 8, 2019 | Jadran LP(home) | 2-1 | Third NL - Jug |
| Aug 31, 2019 | Hrvace(away) | 3-4 | Third NL - Jug |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 25, 2019 | NK Zadar(home) | 1-2 | Cup |
| Sep 21, 2019 | Primorac Biograd(home) | 0-2 | Third NL - Jug |
| Sep 18, 2019 | GOŠK Dubrovnik(away) | 0-0 | Third NL - Jug |
| Sep 14, 2019 | RNK Split(home) | 1-1 | Third NL - Jug |
| Sep 8, 2019 | Neretva Metković(away) | 1-0 | Third NL - Jug |
How many goals should we expect?
Sloga Mravince score 2.0 and concede 1.6 goals per match over their last 7; Zagora score 1.1 and concede 1.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Sloga Mravince | 2.0 | 1.6 | 0 | 6/7 | 5/7 |
| Zagora | 1.1 | 1.3 | 2 | 4/8 | 3/8 |
Over the last 7 matches in all competitions.
Where do both teams sit in the table?
Sloga Mravince sit 4th in Third NL - Jug (48 points from 30 matches) and Zagora sit 1st (69 points from 30 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 1 | Zagora | 30 | 22 | 3 | 5 | 71 | 32 | 69 |
| 4 | Sloga Mravince | 30 | 13 | 9 | 8 | 50 | 39 | 48 |
A question about Sloga Mravince vs Zagora?
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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