Match

Pasaquina vs Santa Tecla: result 0-3 and analysis

Primera DivisionClausura - 12Kick-off on March 17, 2019 at 09:00 PM (UTC)Estadio San Sebastian, Pasaquina

Pasaquina
0-3
Santa Tecla

Full time

What was the result of Pasaquina vs Santa Tecla?

Santa Tecla won 0-3 on March 17, 2019.

Goalscorers

  • 1′W. TorresSanta Tecla
  • 18′J. BarahonaSanta Tecla
  • 29′Erick Alejandro RiveraSanta Tecla

What is the recent form of both teams?

Over their last 15 matches in all competitions, Pasaquina have 4 wins, 6 draws and 5 defeats; Santa Tecla have 5, 6 and 4.

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

Pasaquina
DateOpponentScoreCompetition
Mar 10, 2019Audaz(home)1-0Primera Division
Mar 3, 2019Águila(away)1-4Primera Division
Feb 28, 2019FAS(home)1-1Primera Division
Feb 24, 2019Municipal Limeño(away)0-1Primera Division
Feb 17, 2019Alianza(home)0-0Primera Division
Santa Tecla
DateOpponentScoreCompetition
Mar 10, 2019Sonsonate(home)3-2Primera Division
Mar 3, 2019Audaz(away)0-3Primera Division
Mar 1, 2019Águila(home)2-2Primera Division
Feb 24, 2019FAS(away)1-0Primera Division
Feb 17, 2019Municipal Limeño(home)0-1Primera Division

What does the head-to-head say?

Across the last 6 meetings: 0 Pasaquina win(s), 3 draw(s), 3 Santa Tecla win(s).

DateScoreCompetition
Jan 13, 2019Santa Tecla 2-2 PasaquinaPrimera Division
Oct 21, 2018Santa Tecla 2-2 PasaquinaPrimera Division
Aug 19, 2018Pasaquina 0-1 Santa TeclaPrimera Division
Mar 28, 2018Pasaquina 1-1 Santa TeclaPrimera Division
Feb 4, 2018Santa Tecla 2-0 PasaquinaPrimera Division
Nov 25, 2017Santa Tecla 3-1 PasaquinaPrimera Division

Last archived meeting: Santa Tecla vs Pasaquina on Jan 13, 2019

How many goals should we expect?

Pasaquina score 1.2 and concede 1.5 goals per match over their last 15; Santa Tecla score 1.5 and concede 1.6.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
Pasaquina1.21.558/158/15
Santa Tecla1.51.6211/159/15

Over the last 15 matches in all competitions.

How does Footlab 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. Its accuracy is measured continuously on the predictions actually published. Methodology and measured accuracy

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