Match

Sepidrood Rasht vs Machine Sazi FC: result 1-1 and analysis

Persian Gulf Pro LeagueRegular Season - 18Kick-off on February 15, 2019 at 12:30 PM (UTC)Dr. Azodi Stadium, Rasht

Sepidrood Rasht
1-1
Machine Sazi FC

Full time

What was the result of Sepidrood Rasht vs Machine Sazi FC?

Sepidrood Rasht and Machine Sazi FC drew 1-1 on February 15, 2019.

Goalscorers

  • 78′30097Machine Sazi FC
  • 90′M. TohidastSepidrood Rasht

What is the recent form of both teams?

Over their last 15 matches in all competitions, Sepidrood Rasht have 3 wins, 4 draws and 8 defeats; Machine Sazi FC have 5, 8 and 2.

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

Sepidrood Rasht
DateOpponentScoreCompetition
Feb 10, 2019Sepahan FC(away)0-3Persian Gulf Pro League
Feb 5, 2019Saipa(home)2-2Persian Gulf Pro League
Jan 31, 2019Persepolis FC(home)0-1Hazfi Cup
Dec 7, 2018Esteghlal FC(home)0-5Persian Gulf Pro League
Nov 29, 2018Nassaji Mazandaran(away)2-2Persian Gulf Pro League
Machine Sazi FC
DateOpponentScoreCompetition
Feb 10, 2019Sanat Naft(home)1-0Persian Gulf Pro League
Feb 4, 2019Esteghlal Khuzestan(away)1-0Persian Gulf Pro League
Dec 7, 2018Padideh Khorasan(away)2-2Persian Gulf Pro League
Nov 29, 2018Persepolis FC(home)0-1Persian Gulf Pro League
Nov 23, 2018Sepahan FC(home)1-1Persian Gulf Pro League

What does the head-to-head say?

Across the last 1 meetings: 0 Sepidrood Rasht win(s), 1 draw(s), 0 Machine Sazi FC win(s).

DateScoreCompetition
Aug 10, 2018Machine Sazi FC 1-1 Sepidrood RashtPersian Gulf Pro League

Last archived meeting: Machine Sazi FC vs Sepidrood Rasht on Aug 10, 2018

How many goals should we expect?

Sepidrood Rasht score 0.5 and concede 1.3 goals per match over their last 15; Machine Sazi FC score 1.0 and concede 0.8.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
Sepidrood Rasht0.51.353/155/15
Machine Sazi FC1.00.868/155/15

Over the last 15 matches in all competitions.

How does Footlab 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. Its accuracy is measured continuously on the predictions actually published. Methodology and measured accuracy

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