Match

Sydvest vs Næsby: result 3-1 and analysis

2nd Division - Group 2Regular Season - 12Kick-off on October 22, 2016 at 11:00 AM (UTC)BankParken, Tønder

Sydvest
3-1
Næsby

Full time

What was the result of Sydvest vs Næsby?

Sydvest won 3-1 on October 22, 2016.

What is the recent form of both teams?

Over their last 15 matches in all competitions, Sydvest have 7 wins, 2 draws and 6 defeats; Næsby have 4, 3 and 8.

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

Sydvest
DateOpponentScoreCompetition
Oct 15, 2016Marienlyst(away)4-02nd Division - Group 2
Oct 7, 2016Kolding IF(away)4-32nd Division - Group 2
Oct 1, 2016Dalum(home)0-22nd Division - Group 2
Sep 24, 2016Svendborg(away)0-22nd Division - Group 2
Sep 17, 2016Marienlyst(home)0-12nd Division - Group 2
Næsby
DateOpponentScoreCompetition
Oct 15, 2016Dalum(home)1-12nd Division - Group 2
Oct 8, 2016Svendborg(away)0-12nd Division - Group 2
Oct 1, 2016Middelfart(home)1-02nd Division - Group 2
Sep 25, 2016Greve(away)0-02nd Division - Group 2
Sep 17, 2016Kolding IF(home)1-32nd Division - Group 2

What does the head-to-head say?

In the last meeting: 0 Sydvest wins, 0 draws, 1 Næsby win.

DateScoreCompetition
Aug 6, 2016Næsby 3-1 Sydvest2nd Division - Group 2

Last archived meeting: Næsby vs Sydvest on Aug 6, 2016

How many goals should we expect?

Sydvest score 1.9 and concede 1.8 goals per match over their last 15; Næsby score 1.0 and concede 1.6.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
Sydvest1.91.829/1511/15
Næsby1.01.649/158/15

Over the last 15 matches in all competitions.

Where do both teams sit in the table?

Sydvest sit 10th in 2nd Division - Group 2 (18 points from 17 matches) and Næsby sit 9th (18 points from 17 matches).

2019-20 standings
#ClubPWDLGFGAPts
9Næsby17467202718
10Sydvest17539223418

A question about Sydvest vs Næsby?

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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