Muktijoddha SKC vs Farashganj: result 0-0 and analysis
Premier LeagueRegular Season - 9Kick-off on October 3, 2017 at 10:30 AM (UTC)Sheikh Fazlul Haque Mani Stadium, Gopalganj
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What was the result of Muktijoddha SKC vs Farashganj?
Muktijoddha SKC and Farashganj drew 0-0 on October 3, 2017.
Official lineup for Muktijoddha SKC vs Farashganj
The starting elevens fielded at kick-off.
Muktijoddha SKC
- 6S. Bipul
- 8Mohamed Nazmul Islam Rasel
- 2S. Rony
- 4M. Saikat
- 11H. Kayes
- 19M. Malek
- 24A. Inusah
- 27S. Munna
- 99Islam Mohamed
- 23M. Alam
- 1U. Barua
Farashganj
- 10Matthew Chinedu
- 21J. Mollick
- 77S. Khan
- 1M. Uddin
- 4K. Sabuj
- 6M. Sunni
- 7M. Sujon
- 9M. Nahi
- 12S. Naraka
- 15M. Mandy
- 17M. Hossain
What is the recent form of both teams?
Over their last 15 matches in all competitions, Muktijoddha SKC have 5 wins, 1 draw and 9 defeats; Farashganj have 1, 1 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 11, 2017 | Abahani(home) | 0-2 | Premier League |
| Aug 30, 2017 | Abahani Chittagong(home) | 0-1 | Premier League |
| Aug 26, 2017 | Sheikh Jamal(home) | 1-2 | Premier League |
| Aug 22, 2017 | Brothers Union(away) | 0-1 | Premier League |
| Aug 18, 2017 | Saif(away) | 0-2 | Premier League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 12, 2017 | Arambagh(home) | 1-2 | Premier League |
| Sep 6, 2017 | Rahmatgonj MFS(away) | 1-1 | Premier League |
| Aug 27, 2017 | Sheikh Russel(home) | 1-2 | Premier League |
| Aug 21, 2017 | Team BJMC(away) | 0-1 | Premier League |
| Aug 14, 2017 | Mohammedan Dhaka(home) | 0-4 | Premier League |
How many goals should we expect?
Muktijoddha SKC score 0.8 and concede 1.3 goals per match over their last 15; Farashganj score 0.5 and concede 1.6.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Muktijoddha SKC | 0.8 | 1.3 | 4 | 3/15 | 3/15 |
| Farashganj | 0.5 | 1.6 | 1 | 3/8 | 3/8 |
Over the last 15 matches in all competitions.
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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