Fátima vs Lourinhanense: prediction and stats
Campeonato de Portugal Prio - Group FGroup F - 19Kick-off on March 7, 2021 at 03:00 PM (UTC)Estádio Papa Francisco, Fátima
Match cancelled
What is the recent form of both teams?
Over their last 15 matches in all competitions, Fátima have 1 win, 5 draws and 9 defeats; Lourinhanense have 1, 6 and 8.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Nov 29, 2020 | União Almeirim(home) | 0-3 | Campeonato de Portugal Prio - Group F |
| Nov 15, 2020 | Alverca(home) | 0-6 | Campeonato de Portugal Prio - Group F |
| Nov 8, 2020 | Sacavenense(away) | 1-1 | Campeonato de Portugal Prio - Group F |
| Oct 18, 2020 | Loures(away) | 0-3 | Campeonato de Portugal Prio - Group F |
| Oct 4, 2020 | Torreense(home) | 0-4 | Campeonato de Portugal Prio - Group F |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Feb 28, 2021 | Loures(home) | 1-2 | Campeonato de Portugal Prio - Group F |
| Feb 16, 2021 | União Almeirim(away) | 0-3 | Campeonato de Portugal Prio - Group F |
| Feb 13, 2021 | Caldas(home) | 0-1 | Campeonato de Portugal Prio - Group F |
| Feb 7, 2021 | Pêro Pinheiro(away) | 1-1 | Campeonato de Portugal Prio - Group F |
| Jan 31, 2021 | 1º Dezembro(home) | 1-1 | Campeonato de Portugal Prio - Group F |
How many goals should we expect?
Fátima score 0.7 and concede 2.2 goals per match over their last 15; Lourinhanense score 0.7 and concede 1.9.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Fátima | 0.7 | 2.2 | 2 | 6/15 | 10/15 |
| Lourinhanense | 0.7 | 1.9 | 1 | 8/15 | 6/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 11 | Lourinhanense | 20 | 2 | 6 | 12 | 19 | 43 | 12 |
A question about Fátima vs Lourinhanense?
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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