Match

Libourne vs Chauvigny: result 2-1 and analysis

National 3 - Group ANouvelle-Aquitaine - 2Kick-off on September 5, 2020 at 05:00 PM (UTC)Stade Jean-Antoine Moueix, Libourne

Libourne
2-1
Chauvigny

Full time

What was the result of Libourne vs Chauvigny?

Libourne won 2-1 on September 5, 2020.

Goalscorers

  • 10′R. CouterryLibourne
  • 32′A. LerbetChauvigny
  • 78′B. GeffrayLibourne

Official lineup for Libourne vs Chauvigny

The starting elevens fielded at kick-off.

Libourne

  1. 9A. Castera
  2. 11G. Sainte-Luce
  1. 3C. Janin
  2. 6R. Gauthier
  3. 7R. Couterry
  4. 8Q. Dousseaux
  5. 10V. Fuchs
  1. 2U. Tarbes
  2. 4Y. Zidane
  3. 5U. Gostisbehere
  1. 1T. Skrzypek

Chauvigny

  1. 10B. Chevrier
  1. 2P. Plat
  2. 7A. Lerbet
  3. 8K. Barritault
  4. 9B. Currit
  5. 11A. Ramdane
  1. 3A. Sylla
  2. 4J. Jover
  3. 5D. Dumont
  4. 6F. Türk
  1. 1J. Caillaud
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What is the recent form of both teams?

Over their last 3 matches in all competitions, Libourne have 0 wins, 1 draw and 2 defeats; Chauvigny have 6, 5 and 4.

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

Libourne
DateOpponentScoreCompetition
Dec 5, 2015Tours(home)0-2Coupe de France
Nov 14, 2015Bourges 18(home)2-2Coupe de France
Nov 15, 2014Lormont(home)1-2Coupe de France
Chauvigny
DateOpponentScoreCompetition
Aug 29, 2020Stade Bordelais(home)0-1National 3 - Group A
Feb 29, 2020Anglet Genets(away)1-3National 3 - Group A
Feb 15, 2020Bassin d'Arcachon Sud(home)2-0National 3 - Group A
Feb 8, 2020Stade Montois(away)3-0National 3 - Group A
Feb 1, 2020Poitiers(home)1-1National 3 - Group A

How many goals should we expect?

Libourne score 1.0 and concede 2.0 goals per match over their last 3; Chauvigny score 1.5 and concede 1.3.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
Libourne1.02.002/32/3
Chauvigny1.51.339/158/15

Over the last 3 matches in all competitions.

A question about Libourne vs Chauvigny?

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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