Matelica vs Fermana: result 5-1 and analysis
Serie C - Girone BGirone B - 32Kick-off on March 21, 2021 at 04:30 PM (UTC)Stadio Helvia Recina, Macerata
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What was the result of Matelica vs Fermana?
Matelica won 5-1 on March 21, 2021.
Goalscorers
- 4′V. LeonettiMatelica
- 8′Davide CaisFermana
- 10′Federico MorettiMatelica
- 35′E. VolpicelliMatelica (pen.)
- 45′V. LeonettiMatelica
- 66′E. VolpicelliMatelica
What is the recent form of both teams?
Over their last 15 matches in all competitions, Matelica have 6 wins, 3 draws and 6 defeats; Fermana have 5, 7 and 3.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Mar 17, 2021 | Cesena(away) | 2-2 | Serie C - Girone B |
| Mar 14, 2021 | Padova(home) | 4-1 | Serie C - Girone B |
| Mar 7, 2021 | Legnago Salus(home) | 5-1 | Serie C - Girone B |
| Mar 3, 2021 | Ravenna(away) | 1-0 | Serie C - Girone B |
| Feb 27, 2021 | Virtus Verona(home) | 1-0 | Serie C - Girone B |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Mar 16, 2021 | Triestina(home) | 2-2 | Serie C - Girone B |
| Mar 13, 2021 | Arezzo(away) | 0-1 | Serie C - Girone B |
| Mar 7, 2021 | AJ Fano(away) | 1-1 | Serie C - Girone B |
| Mar 3, 2021 | Cesena(home) | 2-1 | Serie C - Girone B |
| Feb 28, 2021 | Carpi(away) | 0-0 | Serie C - Girone B |
What does the head-to-head say?
Across the last 1 meetings: 0 Matelica win(s), 1 draw(s), 0 Fermana win(s).
| Date | Score | Competition |
|---|---|---|
| Nov 29, 2020 | Fermana 1-1 Matelica | Serie C - Girone B |
How many goals should we expect?
Matelica score 1.5 and concede 1.6 goals per match over their last 15; Fermana score 1.1 and concede 0.8.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Matelica | 1.5 | 1.6 | 4 | 9/15 | 8/15 |
| Fermana | 1.1 | 0.8 | 4 | 8/15 | 3/15 |
Over the last 15 matches in all competitions.
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