Minerva Punjab vs Sudeva: result 3-2 and analysis
I-LeagueRegular Season - 9Kick-off on April 2, 2022 at 11:35 AM (UTC)Kalyani Stadium, Kalyani
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What was the result of Minerva Punjab vs Sudeva?
Minerva Punjab won 3-2 on April 2, 2022.
Goalscorers
- 5′Sreyas Valiyaveettu GopalanSudeva
- 39′A. SarkarSudeva
- 46′V. ChhakchhuakMinerva Punjab (o.g.)
- 49′S. PassiMinerva Punjab
- 55′S. DasMinerva Punjab (o.g.)
What is the recent form of both teams?
Over their last 15 matches in all competitions, Minerva Punjab have 6 wins, 4 draws and 5 defeats; Sudeva have 4, 3 and 8.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Mar 25, 2022 | Real Kashmir(home) | 0-2 | I-League |
| Mar 20, 2022 | NEROCA(home) | 1-1 | I-League |
| Mar 15, 2022 | Sreenidi Deccan(home) | 1-2 | I-League |
| Mar 11, 2022 | Aizawl(home) | 4-3 | I-League |
| Mar 8, 2022 | Kenkre(away) | 4-0 | I-League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Mar 29, 2022 | Real Kashmir(away) | 2-2 | I-League |
| Mar 24, 2022 | NEROCA(home) | 1-1 | I-League |
| Mar 20, 2022 | Sreenidi Deccan(home) | 0-1 | I-League |
| Mar 15, 2022 | Aizawl(home) | 1-2 | I-League |
| Mar 11, 2022 | Rajasthan United(away) | 0-0 | I-League |
What does the head-to-head say?
Across the last 1 meetings: 0 Minerva Punjab win(s), 1 draw(s), 0 Sudeva win(s).
| Date | Score | Competition |
|---|---|---|
| Jan 29, 2021 | Minerva Punjab 0-0 Sudeva | I-League |
Last archived meeting: Minerva Punjab vs Sudeva on Jan 29, 2021
How many goals should we expect?
Minerva Punjab score 1.6 and concede 1.3 goals per match over their last 15; Sudeva score 0.9 and concede 1.2.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Minerva Punjab | 1.6 | 1.3 | 5 | 7/15 | 6/15 |
| Sudeva | 0.9 | 1.2 | 4 | 7/15 | 6/15 |
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