Match

VPS vs Olimpija Ljubljana: result 1-0 and analysis

UEFA Europa League1st Qualifying RoundKick-off on June 29, 2017 at 04:00 PM (UTC)Lemonsoft Stadion, Vaasa

VPS
1-0
Olimpija Ljubljana

Full time

What was the result of VPS vs Olimpija Ljubljana?

VPS won 1-0 on June 29, 2017.

Goalscorers

  • 12′J. VahteraVPS

Official lineup for VPS vs Olimpija Ljubljana

The starting elevens fielded at kick-off.

VPS

3-1-4-2
  1. 10S. Morrissey
  2. 5M. Viitikko
  1. 6J. Voutilainen
  2. 15Jonas Levänen
  3. 9Juho Lähde
  4. 7J. Hakola
  1. 17J. Vahtera
  1. 2T. Lahti
  2. 4J. Engström
  3. 20V. Lampi
  1. 1M. Meerits

Olimpija Ljubljana

4-3-3
  1. 26Leon Benko
  2. 17I. Abass
  3. 11N. Oduwa
  1. 88D. Miškić
  2. 90Tomislav Tomić
  3. 10G. Brkić
  1. 32N. Mitrovič
  2. 44D. Štiglec
  3. 27A. Zarifović
  4. 30Branko Ilič
  1. 41N. Vidmar
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What is the recent form of both teams?

Over their last 15 matches in all competitions, VPS have 7 wins, 5 draws and 3 defeats; Olimpija Ljubljana have 1, 0 and 1.

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

VPS
DateOpponentScoreCompetition
Jun 22, 2017Rops(home)1-0Veikkausliiga
Jun 17, 2017SJK(away)1-0Veikkausliiga
Jun 14, 2017KuPS(away)2-2Veikkausliiga
Jun 3, 2017Lahti(away)0-0Veikkausliiga
May 31, 2017HIFK Helsinki(home)1-1Veikkausliiga
Olimpija Ljubljana
DateOpponentScoreCompetition
Jul 20, 2016AS Trencin(away)3-2UEFA Champions League
Jul 13, 2016AS Trencin(home)3-4UEFA Champions League

How many goals should we expect?

VPS score 1.4 and concede 1.3 goals per match over their last 15; Olimpija Ljubljana score 3.0 and concede 3.0.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
VPS1.41.358/157/15
Olimpija Ljubljana3.03.002/22/2

Over the last 15 matches in all competitions.

A question about VPS vs Olimpija Ljubljana?

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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