Match

Padova vs Fermana: result 0-0 and analysis

Serie C - Girone ARegular Season - 17Kick-off on December 4, 2017 at 07:45 PM (UTC)Stadio Comunale Euganeo, Padova

Padova
0-0
Fermana

Full time

What was the result of Padova vs Fermana?

Padova and Fermana drew 0-0 on December 4, 2017.

Official lineup for Padova vs Fermana

The starting elevens fielded at kick-off.

Padova

  1. 17Marco Guidone
  2. 27Petar Zivkov
  3. 28A. Capello
  1. 7N. Pulzetti
  2. 11G. Pinzi
  3. 21D. Marcandella
  4. 25L. Belingheri
  1. 5T. Trevisan
  2. 20L. Ravanelli
  3. 23D. Cappelletti
  1. 22D. Merelli

Fermana

  1. 7Andrea Petrucci
  2. 17M. Sansovini
  3. 29A. Lupoli
  1. 2Bachir Mouhamed Manè
  2. 8Alex Misin
  3. 20A. Doninelli
  4. 24Roberto Grieco
  5. 12P. Ginestra
  1. 5Marco Comotto
  2. 15G. Clemente
  3. 30N. Sperotto
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What is the recent form of both teams?

Over their last 15 matches in all competitions, Padova have 10 wins, 2 draws and 3 defeats; Fermana have 4, 6 and 4.

The competition is shown for every match: in pre-season, several of these games are friendlies.

Padova
DateOpponentScoreCompetition
Nov 25, 2017Albinoleffe(away)2-1Serie C - Girone A
Nov 17, 2017Triestina(home)2-1Serie C - Girone A
Nov 12, 2017Pordenone(away)2-1Serie C - Girone A
Nov 8, 2017Mestre(home)2-1Serie C - Girone A
Nov 5, 2017Feralpisalo(away)2-2Serie C - Girone A
Fermana
DateOpponentScoreCompetition
Nov 19, 2017Gubbio(away)0-0Serie C - Girone A
Nov 8, 2017Feralpisalo(away)2-1Serie C - Girone A
Nov 5, 2017Albinoleffe(home)0-3Serie C - Girone A
Oct 29, 2017Pordenone(home)0-0Serie C - Girone A
Oct 22, 2017Reggiana(away)0-0Serie C - Girone A

How many goals should we expect?

Padova score 1.5 and concede 0.9 goals per match over their last 15; Fermana score 0.9 and concede 0.9.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
Padova1.50.958/1510/15
Fermana0.90.973/145/14

Over the last 15 matches in all competitions.

A question about Padova vs Fermana?

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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

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