Moralo vs Miajadas: result 1-2 and analysis
Tercera División RFEF - Group 14Group 14 - 11Kick-off on November 1, 2019 at 11:00 AM (UTC)Estadio Municipal de Navalmoral de la Mata, Navalmoral de la Mata
Full time
What was the result of Moralo vs Miajadas?
Miajadas won 1-2 on November 1, 2019.
Goalscorers
- 61′SusoMoralo
- 78′Javier RamiroMiajadas
- 88′Rubén JesúsMiajadas
What is the recent form of both teams?
Over their last 10 matches in all competitions, Moralo have 4 wins, 5 draws and 1 defeats; Miajadas have 3, 1 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 27, 2019 | Azuaga(away) | 0-1 | Tercera División RFEF - Group 14 |
| Oct 20, 2019 | Extremadura UD II(home) | 1-1 | Tercera División RFEF - Group 14 |
| Oct 13, 2019 | Olivenza(away) | 1-1 | Tercera División RFEF - Group 14 |
| Oct 6, 2019 | Villanovense(home) | 1-1 | Tercera División RFEF - Group 14 |
| Sep 29, 2019 | Diocesano(away) | 1-0 | Tercera División RFEF - Group 14 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 27, 2019 | Cacereño(home) | 0-2 | Tercera División RFEF - Group 14 |
| Oct 20, 2019 | Valdivia(away) | 0-0 | Tercera División RFEF - Group 14 |
| Oct 13, 2019 | Azuaga(away) | 1-5 | Tercera División RFEF - Group 14 |
| Oct 6, 2019 | Extremadura UD II(home) | 1-4 | Tercera División RFEF - Group 14 |
| Sep 29, 2019 | Olivenza(away) | 0-3 | Tercera División RFEF - Group 14 |
How many goals should we expect?
Moralo score 1.1 and concede 0.7 goals per match over their last 10; Miajadas score 0.9 and concede 1.8.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Moralo | 1.1 | 0.7 | 4 | 5/10 | 1/10 |
| Miajadas | 0.9 | 1.8 | 3 | 4/10 | 5/10 |
Over the last 10 matches in all competitions.
Where do both teams sit in the table?
The current season has no played match yet: final standings of the 2025-26 season.
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 3 | Moralo | 34 | 17 | 11 | 6 | 54 | 32 | 62 |
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