Match

Skjold Sæby vs Silkeborg KFUM: result 0-2 and analysis

Denmark Series - Group 4Group 4 - 1Kick-off on August 15, 2020 at 11:30 AM (UTC)Fælledparken, København

Skjold Sæby
0-2
Silkeborg KFUM

Full time

What was the result of Skjold Sæby vs Silkeborg KFUM?

Silkeborg KFUM won 0-2 on August 15, 2020.

What is the recent form of both teams?

Over their last 15 matches in all competitions, Skjold Sæby have 4 wins, 1 draw and 10 defeats; Silkeborg KFUM have 10, 2 and 3.

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

Skjold Sæby
DateOpponentScoreCompetition
Aug 8, 2020Jammerbugt(away)0-5Friendlies Clubs
Nov 2, 2019VRI(away)2-2Denmark Series - Group 4
Oct 26, 2019Silkeborg KFUM(home)1-5Denmark Series - Group 4
Oct 19, 2019Djursland(away)1-3Denmark Series - Group 4
Oct 12, 2019Nørresundby(home)1-0Denmark Series - Group 4
Silkeborg KFUM
DateOpponentScoreCompetition
Feb 29, 2020Ringkøbing(away)2-2Friendlies Clubs
Feb 22, 2020VSK Århus(away)2-0Friendlies Clubs
Nov 1, 2019Lyseng(home)4-3Denmark Series - Group 4
Oct 26, 2019Skjold Sæby(away)5-1Denmark Series - Group 4
Oct 18, 2019Aarhus Fremad II(home)2-2Denmark Series - Group 4

What does the head-to-head say?

Across the last 2 meetings: 0 Skjold Sæby wins, 0 draws, 2 Silkeborg KFUM wins.

DateScoreCompetition
Oct 26, 2019Skjold Sæby 1-5 Silkeborg KFUMDenmark Series - Group 4
Aug 23, 2019Silkeborg KFUM 3-0 Skjold SæbyDenmark Series - Group 4

Last archived meeting: Skjold Sæby vs Silkeborg KFUM on Oct 26, 2019

How many goals should we expect?

Skjold Sæby score 1.7 and concede 2.7 goals per match over their last 15; Silkeborg KFUM score 2.6 and concede 1.7.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
Skjold Sæby1.72.739/1513/15
Silkeborg KFUM2.61.7312/1513/15

Over the last 15 matches in all competitions.

A question about Skjold Sæby vs Silkeborg KFUM?

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

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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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