Città Di Sant’Agata vs Licata: result 1-1 and analysis
Serie D - Girone IGroup I - 9Kick-off on October 31, 2021 at 01:30 PM (UTC)Campo da Calcio di Sant'Agata di Militello, Sant'Agata di Militello
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What was the result of Città Di Sant’Agata vs Licata?
Città Di Sant’Agata and Licata drew 1-1 on October 31, 2021.
Goalscorers
- 28′?Licata
- 40′?Città Di Sant’Agata
What is the recent form of both teams?
Over their last 9 matches in all competitions, Città Di Sant’Agata have 4 wins, 2 draws and 3 defeats; Licata 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 |
|---|---|---|---|
| Oct 24, 2021 | Giarre(away) | 0-1 | Serie D - Girone I |
| Oct 20, 2021 | Castrovillari(home) | 2-2 | Serie D - Girone I |
| Oct 17, 2021 | Santa Maria Cilento(away) | 1-2 | Serie D - Girone I |
| Oct 10, 2021 | Troina(home) | 3-1 | Serie D - Girone I |
| Oct 6, 2021 | Rende(away) | 1-0 | Serie D - Girone I |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 24, 2021 | Real Normanna(home) | 0-0 | Serie D - Girone I |
| Oct 20, 2021 | Paternò(away) | 0-1 | Serie D - Girone I |
| Oct 17, 2021 | Portici(home) | 4-0 | Serie D - Girone I |
| Oct 10, 2021 | Lamezia Terme(away) | 1-2 | Serie D - Girone I |
| Oct 6, 2021 | San Luca(home) | 2-0 | Serie D - Girone I |
How many goals should we expect?
Città Di Sant’Agata score 1.3 and concede 1.0 goals per match over their last 9; Licata score 1.5 and concede 1.1.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Città Di Sant’Agata | 1.3 | 1.0 | 3 | 5/9 | 4/9 |
| Licata | 1.5 | 1.1 | 7 | 5/15 | 6/15 |
Over the last 9 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 9 | Licata | 10 | 4 | 2 | 4 | 10 | 17 | 14 |
A question about Città Di Sant’Agata vs Licata?
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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