Tekstilshchik vs Forte Taganrog: result 4-1 and analysis
Second League A - Division A SilverFall Season Silver - 7Kick-off on August 27, 2023 at 01:00 PM (UTC)Stadion Tekstilshchik, Ivanovo
Full time
What was the result of Tekstilshchik vs Forte Taganrog?
Tekstilshchik won 4-1 on August 27, 2023.
Goalscorers
- 4′D. KalinTekstilshchik
- 8′N. SimdyankinTekstilshchik
- 40′D. GorovykhTekstilshchik
- 76′P. VolodkinForte Taganrog
- 90′A. ShlenkinTekstilshchik
What is the recent form of both teams?
Over their last 15 matches in all competitions, Tekstilshchik have 3 wins, 7 draws and 5 defeats; Forte Taganrog have 1, 7 and 7.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 22, 2023 | Amkal(home) | 0-0 | Cup |
| Aug 17, 2023 | Chertanovo Moscow(away) | 1-1 | Second League A - Division A Silver |
| Aug 12, 2023 | Metallurg Lipetsk(away) | 1-1 | Second League A - Division A Silver |
| Aug 5, 2023 | Amkar(home) | 1-0 | Second League A - Division A Silver |
| Jul 29, 2023 | Chelyabinsk(away) | 1-1 | Second League A - Division A Silver |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 23, 2023 | Metallurg Lipetsk(away) | 1-1 | Cup |
| Aug 19, 2023 | Metallurg Lipetsk(home) | 1-3 | Second League A - Division A Silver |
| Aug 12, 2023 | Amkar(away) | 1-1 | Second League A - Division A Silver |
| Aug 5, 2023 | Chelyabinsk(home) | 2-2 | Second League A - Division A Silver |
| Jul 29, 2023 | Novosibirsk(away) | 0-1 | Second League A - Division A Silver |
How many goals should we expect?
Tekstilshchik score 0.8 and concede 1.1 goals per match over their last 15; Forte Taganrog score 0.7 and concede 1.4.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Tekstilshchik | 0.8 | 1.1 | 5 | 6/15 | 3/15 |
| Forte Taganrog | 0.7 | 1.4 | 4 | 8/15 | 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