Match

AJ Fano vs Parma: result 0-1 and analysis

Serie C - Girone ARegular Season - 11Kick-off on October 29, 2016 at 04:30 PM (UTC)Stadio Raffaele Mancini, Fano

AJ Fano
0-1
Parma

Full time

What was the result of AJ Fano vs Parma?

Parma won 0-1 on October 29, 2016.

Goalscorers

  • 86′E. CalaiòParma

Official lineup for AJ Fano vs Parma

The starting elevens fielded at kick-off.

AJ Fano

  1. 9N. Gucci
  1. 7Umberto Cazzola
  2. 14A. Bellemo
  3. 21G. Gabbianelli
  4. 15S. Masini
  5. 19M. Taino
  6. 23L. Gualdi
  1. 5M. Ferrani
  2. 6Andrea Torta
  3. 16W. Zullo
  1. 1Pietro Menegatti

Parma

  1. 9M. Nocciolini
  2. 10Y. Baraye
  3. 32Felice Evacuo
  1. 4Francesco Corapi
  2. 8Davide Giorgino
  3. 29M. Scavone
  1. 2Michele Canini
  2. 6Alessandro Lucarelli
  3. 21L. Nunzella
  4. 26A. Coly
  1. 1K. Zommers
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What is the recent form of both teams?

Over their last 10 matches in all competitions, AJ Fano have 1 win, 4 draws and 5 defeats; Parma have 5, 6 and 4.

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

AJ Fano
DateOpponentScoreCompetition
Oct 22, 2016Feralpisalo(away)0-0Serie C - Girone A
Oct 15, 2016Ancona(home)1-1Serie C - Girone A
Oct 8, 2016Reggiana(away)1-3Serie C - Girone A
Oct 1, 2016Maceratese(home)0-0Serie C - Girone A
Sep 24, 2016Teramo(away)0-2Serie C - Girone A
Parma
DateOpponentScoreCompetition
Oct 22, 2016Mantova(home)1-0Serie C - Girone A
Oct 15, 2016Forli(away)5-3Serie C - Girone A
Oct 10, 2016Feralpisalo(home)1-2Serie C - Girone A
Oct 1, 2016Sambenedettese(away)2-2Serie C - Girone A
Sep 24, 2016Albinoleffe(home)1-0Serie C - Girone A

How many goals should we expect?

AJ Fano score 0.6 and concede 1.3 goals per match over their last 10; Parma score 1.5 and concede 1.6.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
AJ Fano0.61.324/102/10
Parma1.51.658/1510/15

Over the last 10 matches in all competitions.

A question about AJ Fano vs Parma?

Ask Footlab AI: lineups, absences, player form, stats, how the match could unfold.

Sign-in required. No odds displayed, no affiliation: the method is published and the accuracy is measured.

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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