Match

Kalju Nomme vs Shkendija: result 0-1 and analysis

UEFA Champions League1st Qualifying RoundKick-off on July 9, 2019 at 04:00 PM (UTC)Kadrioru staadion, Tallinn

Kalju Nomme
0-1
Shkendija

Full time

What was the result of Kalju Nomme vs Shkendija?

Shkendija won 0-1 on July 9, 2019.

Goalscorers

  • 81′Agim IbraimiShkendija (pen.)

Official lineup for Kalju Nomme vs Shkendija

The starting elevens fielded at kick-off.

Kalju Nomme

4-2-3-1
  1. 17R. Kirss
  1. 11Liliu
  2. 43K. Paur
  3. 7Réginald Mbu Alidor
  1. 15I. Subbotin
  2. 9Nikolay Mashichev
  1. 26A. Markovych
  2. 4V. Avilov
  3. 5Maximiliano Achille Uggè
  4. 2A. Kulinitš
  1. 96P. Londak

Shkendija

4-2-3-1
  1. 14M. Radeski
  1. 10Agim Ibraimi
  2. 7B. Ibraimi
  3. 8E. Totre
  1. 90Z. Husmani
  2. 5A. Alimi
  1. 4E. Bejtulai
  2. 6V. Musliu
  3. 16M. Murati
  4. 3G. Mici
  1. 1K. Zahov
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What is the recent form of both teams?

Over their last 15 matches in all competitions, Kalju Nomme have 10 wins, 5 draws and 0 defeats; Shkendija have 10, 2 and 3.

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

Kalju Nomme
DateOpponentScoreCompetition
Jul 5, 2019Trans Narva(away)1-1Meistriliiga
Jun 28, 2019Tammeka(away)0-0Meistriliiga
Jun 22, 2019Tulevik(home)2-1Meistriliiga
Jun 18, 2019Flora Tallinn(away)1-0Meistriliiga
Jun 15, 2019Trans Narva(home)3-2Meistriliiga
Shkendija
DateOpponentScoreCompetition
May 26, 2019Renova(away)2-3First League
May 19, 2019Akademija Pandev(home)4-1First League
May 12, 2019Pobeda(away)4-1First League
May 8, 2019Sileks(home)0-0First League
May 4, 2019FK Rabotnicki(away)1-0First League

How many goals should we expect?

Kalju Nomme score 1.9 and concede 0.7 goals per match over their last 15; Shkendija score 2.2 and concede 0.9.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
Kalju Nomme1.90.787/157/15
Shkendija2.20.968/159/15

Over the last 15 matches in all competitions.

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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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