Match

Barcelona U19 vs PSV U19: result 2-1 and analysis

UEFA Youth LeagueGroup Stage - 1Kick-off on September 18, 2018 at 12:00 PM (UTC)Camp 1 del Ciutat Esportiva Joan Gamper, Sant Joan Despí

Barcelona U19
2-1
PSV U19

Full time

What was the result of Barcelona U19 vs PSV U19?

Barcelona U19 won 2-1 on September 18, 2018.

Goalscorers

  • 11′Lucas de VegaBarcelona U19
  • 77′K. de La FuentePSV U19 (o.g.)
  • 88′Nico GonzálezBarcelona U19

Official lineup for Barcelona U19 vs PSV U19

The starting elevens fielded at kick-off.

Barcelona U19

  1. 7K. de La Fuente
  2. 9Abel Ruiz
  3. 11Nils Mortimer
  1. 5Juan Miranda
  2. 6Jandro Orellana
  3. 8Lucas de Vega
  4. 10Monchu
  1. 2Sergi Rosanas
  2. 3Arnau Comas
  3. 4Joan Rojas
  1. 1Arnau Tenas

PSV U19

  1. 7J. Piroe
  2. 10M. Ihattaren
  3. 11N. Thomas
  1. 6K. Oostenbrink
  2. 8M. Sadílek
  3. 9Y. Vertessen
  1. 2J. Teze
  2. 3Tijn Daverveld
  3. 4M. Kreekels
  4. 5R. Zeegers
  1. 1K. van Dorp
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What is the recent form of both teams?

Over their last 10 matches in all competitions, Barcelona U19 have 9 wins, 1 draw and 0 defeats; PSV U19 have 0, 0 and 0.

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

Barcelona U19
DateOpponentScoreCompetition
Apr 23, 2018Chelsea U19(away)3-0UEFA Youth League
Apr 20, 2018Manchester City U19(away)5-4UEFA Youth League
Mar 13, 2018Atlético Madrid U19(home)2-0UEFA Youth League
Feb 20, 2018PSG U19(away)1-0UEFA Youth League
Dec 5, 2017Sporting CP U19(home)1-1UEFA Youth League

Where do both teams sit in the table?

Barcelona U19 sit 8th in UEFA Youth League (13 points from 6 matches) and PSV U19 sit 19th (8 points from 6 matches).

2025-26 standings
#ClubPWDLGFGAPts
8Barcelona U19641113913
19PSV U1962221398

A question about Barcelona U19 vs PSV U19?

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

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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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