NEROCA vs East Bengal: result 0-2 and analysis
I-LeagueRegular Season - 1Kick-off on October 27, 2018 at 08:30 AM (UTC)Khuman Lampak Main Stadium, Imphal
Full time
What was the result of NEROCA vs East Bengal?
East Bengal won 0-2 on October 27, 2018.
Goalscorers
- 10′E. EsquedaEast Bengal
- 48′E. EsquedaEast Bengal (pen.)
Official lineup for NEROCA vs East Bengal
The starting elevens fielded at kick-off.
NEROCA
- 11O. Chidi
- 12Singam Subhash Singh
- 14Malemnganba Meitei Kshetrimayum
- 8T. Singh
- 10Katsumi Yusa
- 2W. Meetei
- 6Moirangmayum Singh
- 4Eduardo Soares Ferreira
- 19D. Meitei
- 28Aryn Glen Williams
- 1Mauro Boerchio
East Bengal
- 9E. Esqueda
- 17D. Ralte
- 22J. Justin
- 20Lalrindika Ralte
- 21Y. Longvah
- 2Johnny Acosta Zamora
- 3Borja Gómez Pérez
- 5K. Singh
- 27Lalramchullova
- 41M. Mohammed
- 40R. Dagar
What is the recent form of both teams?
Over their last 2 matches in all competitions, NEROCA have 1 win, 0 draws and 1 defeat; East Bengal have 3, 0 and 1.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 13, 2018 | Bengaluru(away) | 1-3 | AIFF Super Cup |
| Apr 6, 2018 | Kerala Blasters(away) | 3-2 | AIFF Super Cup |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 20, 2018 | Bengaluru(home) | 1-4 | AIFF Super Cup |
| Apr 16, 2018 | Goa(home) | 1-0 | AIFF Super Cup |
| Apr 8, 2018 | Aizawl(away) | 1-0 | AIFF Super Cup |
| Apr 5, 2018 | Mumbai City(away) | 2-1 | AIFF Super Cup |
How many goals should we expect?
NEROCA score 2.0 and concede 2.5 goals per match over their last 2; East Bengal score 1.3 and concede 1.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| NEROCA | 2.0 | 2.5 | 0 | 2/2 | 2/2 |
| East Bengal | 1.3 | 1.3 | 2 | 2/4 | 2/4 |
Over the last 2 matches in all competitions.
A question about NEROCA vs East Bengal?
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