Tollygunge Agragami vs Patha Chakra: result 2-1 and analysis
Calcutta Premier DivisionRegular Season - 11Kick-off on August 9, 2023 at 09:30 AM (UTC)Rabindra Sarobar Stadium, Kolkata, West Bengal
Full time
What was the result of Tollygunge Agragami vs Patha Chakra?
Tollygunge Agragami won 2-1 on August 9, 2023.
What is the recent form of both teams?
Over their last 7 matches in all competitions, Tollygunge Agragami have 1 wins, 2 draws and 4 defeats; Patha Chakra have 0, 3 and 5.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 2, 2023 | Army Red(home) | 1-3 | Calcutta Premier Division |
| Jul 30, 2023 | Southern Samity(home) | 1-3 | Calcutta Premier Division |
| Jul 25, 2023 | Food Corporation(home) | 2-2 | Calcutta Premier Division |
| Jul 18, 2023 | Peerless(away) | 0-1 | Calcutta Premier Division |
| Jul 15, 2023 | Calcutta(away) | 2-0 | Calcutta Premier Division |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 6, 2023 | Army Red(home) | 1-1 | Calcutta Premier Division |
| Aug 3, 2023 | Food Corporation(home) | 1-1 | Calcutta Premier Division |
| Jul 28, 2023 | Dalhousie(home) | 1-1 | Calcutta Premier Division |
| Jul 24, 2023 | Peerless(away) | 1-4 | Calcutta Premier Division |
| Jul 18, 2023 | Mohammedan(away) | 0-4 | Calcutta Premier Division |
How many goals should we expect?
Tollygunge Agragami score 1.0 and concede 2.0 goals per match over their last 7; Patha Chakra score 0.8 and concede 2.4.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Tollygunge Agragami | 1.0 | 2.0 | 2 | 4/7 | 4/7 |
| Patha Chakra | 0.8 | 2.4 | 0 | 6/8 | 4/8 |
Over the last 7 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 19 | Patha Chakra | 9 | 2 | 1 | 6 | 9 | 29 | 7 |
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