Match

Byåsen vs Moss: result 1-2 and analysis

2. Division - Group 1Regular Season - 9Kick-off on June 10, 2019 at 02:00 PM (UTC)Byåsen Arena, Trondheim

Byåsen
1-2
Moss

Full time

What was the result of Byåsen vs Moss?

Moss won 1-2 on June 10, 2019.

Goalscorers

  • 38′A. SanyangMoss
  • 56′191730Byåsen
  • 64′A. SanyangMoss

Official lineup for Byåsen vs Moss

The starting elevens fielded at kick-off.

Byåsen

  1. 11Andreas Rye
  1. 8Ø. Haugen
  2. 21H. Hammer
  3. 4L. Vatten
  4. 7A. Berbatovci
  5. 14K. Andreassen
  6. 15S. Nordskag
  1. 2Bongani Lionel Kamanzi
  2. 5E. Langørgen
  3. 9Robin Yosefa Utseth Bjørnholm-Jatta
  1. 1Alexander Hovdevik

Moss

  1. 10Thomas Klaussen
  2. 18R. Elshaug
  3. 19A. Sanyang
  4. 20R. Svindland
  1. 8S. Ali
  2. 9C. Skårn
  3. 2O. Jenssen
  4. 7M. Aarstrand
  5. 11T. Reinback
  6. 12A. Wasenius
  1. 15S. Andersen
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What is the recent form of both teams?

Over their last 9 matches in all competitions, Byåsen have 2 wins, 2 draws and 5 defeats; Moss have 4, 0 and 6.

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

Byåsen
DateOpponentScoreCompetition
Jun 2, 2019Levanger(away)2-12. Division - Group 1
May 25, 2019Nardo(home)1-12. Division - Group 1
May 19, 2019Bryne(away)2-22. Division - Group 1
May 11, 2019Fredrikstad(home)0-12. Division - Group 1
May 5, 2019Vidar(away)1-42. Division - Group 1
Moss
DateOpponentScoreCompetition
Jun 1, 2019Fredrikstad(home)0-32. Division - Group 1
May 26, 2019hodd(away)2-42. Division - Group 1
May 22, 2019Kongsvinger(home)1-2NM Cupen
May 16, 2019Kvik Halden(home)1-42. Division - Group 1
May 11, 2019Arendal(away)0-32. Division - Group 1

How many goals should we expect?

Byåsen score 1.2 and concede 2.1 goals per match over their last 9; Moss score 1.5 and concede 1.8.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
Byåsen1.22.106/96/9
Moss1.51.844/107/10

Over the last 9 matches in all competitions.

A question about Byåsen vs Moss?

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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