Sudtirol vs Fermana: result 2-2 and analysis
Serie C - Girone ARegular Season - 3Kick-off on September 10, 2017 at 04:30 PM (UTC)Stadio Marco Druso, Bozen
Full time
What was the result of Sudtirol vs Fermana?
Sudtirol and Fermana drew 2-2 on September 10, 2017.
Goalscorers
- 59′H. FinkSudtirol
- 65′E. GyasiSudtirol
- 74′A. LupoliFermana
- 84′M. SansoviniFermana (pen.)
Official lineup for Sudtirol vs Fermana
The starting elevens fielded at kick-off.
Sudtirol
- 20A. Gatto
- 7Michael Cia
- 10H. Fink
- 14L. Berardocco
- 21F. Tait
- 2F. Sgarbi
- 3P. Frascatore
- 11A. Zanchi
- 13M. Baldan
- 17E. Gyasi
- 1D. Offredi
Fermana
- 7Andrea Petrucci
- 9Luca Cremona
- 4Gianluca Urbinati
- 8Alex Misin
- 10M. D'Angelo
- 11I. Iotti
- 24Roberto Grieco
- 5Marco Comotto
- 21M. Gennari
- 30N. Sperotto
- 1Mattia Valentini
What is the recent form of both teams?
Over their last 15 matches in all competitions, Sudtirol have 7 wins, 1 draw and 7 defeats; Fermana have 0, 0 and 1.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 3, 2017 | Pordenone(away) | 1-3 | Serie C - Girone A |
| Aug 27, 2017 | Albinoleffe(home) | 1-0 | Serie C - Girone A |
| May 7, 2017 | Mantova(away) | 1-3 | Serie C - Girone A |
| Apr 30, 2017 | Padova(home) | 1-0 | Serie C - Girone A |
| Apr 24, 2017 | Parma(away) | 1-0 | Serie C - Girone A |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 27, 2017 | Ravenna(away) | 0-1 | Serie C - Girone A |
How many goals should we expect?
Sudtirol score 0.8 and concede 1.1 goals per match over their last 15; Fermana score 0.0 and concede 1.0.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Sudtirol | 0.8 | 1.1 | 8 | 4/15 | 4/15 |
| Fermana | 0.0 | 1.0 | 0 | 0/1 | 0/1 |
Over the last 15 matches in all competitions.
A question about Sudtirol vs Fermana?
Ask Footlab AI: lineups, absences, player form, stats, how the match could unfold.
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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