Match

AJ Fano vs Padova: result 3-1 and analysis

Serie C - Girone ARegular Season - 4Kick-off on September 13, 2016 at 06:30 PM (UTC)Stadio Raffaele Mancini, Fano

AJ Fano
3-1
Padova

Full time

What was the result of AJ Fano vs Padova?

AJ Fano won 3-1 on September 13, 2016.

Goalscorers

  • 18′N. GucciAJ Fano
  • 43′Nicola MadonnaPadova
  • 61′N. GucciAJ Fano
  • 83′N. GucciAJ Fano

Official lineup for AJ Fano vs Padova

The starting elevens fielded at kick-off.

AJ Fano

  1. 9N. Gucci
  1. 10Davide Borrelli
  2. 14A. Bellemo
  3. 11R. Cocuzza
  4. 19M. Taino
  5. 23L. Gualdi
  6. 27G. Schiavini
  1. 5M. Ferrani
  2. 6Andrea Torta
  3. 13Stefano Lanini
  1. 1Pietro Menegatti

Padova

  1. 9C. Altinier
  2. 21Luis María Alfageme
  1. 5F. Dettori
  2. 6Matteo Mandorlini
  3. 8C. De Risio
  4. 16Nicola Madonna
  1. 2A. Tentardini
  2. 13A. Sbraga
  3. 19M. Russo
  4. 25Emerson
  1. 22A. Favaro
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What is the recent form of both teams?

Over their last 3 matches in all competitions, AJ Fano have 0 wins, 1 draw and 2 defeats; Padova have 1, 1 and 0.

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

AJ Fano
DateOpponentScoreCompetition
Sep 8, 2016Albinoleffe(away)1-1Serie C - Girone A
Sep 3, 2016Santarcangelo(home)0-2Serie C - Girone A
Aug 27, 2016Sudtirol(away)0-2Serie C - Girone A
Padova
DateOpponentScoreCompetition
Sep 10, 2016Forli(home)2-0Serie C - Girone A
Sep 3, 2016Albinoleffe(home)1-1Serie C - Girone A

How many goals should we expect?

AJ Fano score 0.3 and concede 1.7 goals per match over their last 3; Padova score 1.5 and concede 0.5.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
AJ Fano0.31.701/30/3
Padova1.50.511/20/2

Over the last 3 matches in all competitions.

A question about AJ Fano vs Padova?

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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