Match

DSK Gomel vs SKVICH: result 0-3 and analysis

1. DivisionRegular Season - 4Kick-off on May 11, 2012 at 12:30 PM (UTC)Stadyen DYuSSh-8, Gomel

DSK Gomel
0-3
SKVICH

Full time

What was the result of DSK Gomel vs SKVICH?

SKVICH won 0-3 on May 11, 2012.

Goalscorers

  • 37′Denis SashchekoSKVICH
  • 49′Y. MarkhelSKVICH (pen.)
  • 68′Y. MarkhelSKVICH

Official lineup for DSK Gomel vs SKVICH

The starting elevens fielded at kick-off.

DSK Gomel

  1. AA. Klop
  2. VV. Lagutin
  1. II. Misochenko
  2. DDmitri Ryabtsev
  3. AA. Kudryavtsev
  4. DD. Gradoboev
  5. AAleksey Pinchuk
  1. PPavel Tarasenko
  2. AA. Efremov
  3. IIlya Saplin
  1. OO. Kovalev

SKVICH

  1. DDenis Sashcheko
  2. VVitaly Shepetovskiy
  3. AAleksandr Mikhnovets
  4. VVladimir Margulets
  5. SS. Shumanov
  6. VV. Zamara
  7. YY. Markhel
  1. AAleksey Belousov
  2. VVladimir Shibeko
  3. DD. Lekhavitskiy
  1. VVitali Makauchyk
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What is the recent form of both teams?

Over their last 3 matches in all competitions, DSK Gomel have 0 wins, 1 draw and 2 defeats; SKVICH have 2, 0 and 1.

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

DSK Gomel
DateOpponentScoreCompetition
May 5, 2012Byaroza 2010(away)0-11. Division
Apr 28, 2012Sputnik(home)0-01. Division
Apr 21, 2012FC Dnepr Mogilev(away)0-41. Division
SKVICH
DateOpponentScoreCompetition
May 5, 2012Rudensk(home)2-11. Division
Apr 28, 2012Gorodeya(away)0-11. Division
Apr 21, 2012Khimik Svetlogorsk(home)2-01. Division

How many goals should we expect?

DSK Gomel score 0.0 and concede 1.7 goals per match over their last 3; SKVICH score 1.3 and concede 0.7.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
DSK Gomel0.01.710/31/3
SKVICH1.30.711/31/3

Over the last 3 matches in all competitions.

A question about DSK Gomel vs SKVICH?

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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