Mashuk-KMV vs Torpedo Miass: result 2-3 and analysis
Second League A - Spring Season SilverSpring Season Silver - 3Kick-off on March 18, 2024 at 11:00 AM (UTC)Central'nyj Stadion Mashuk, Pyatigorsk
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What was the result of Mashuk-KMV vs Torpedo Miass?
Torpedo Miass won 2-3 on March 18, 2024.
Goalscorers
- 25′D. KuzminTorpedo Miass
- 52′Vladislav ShpitalnyTorpedo Miass
- 72′A. KhutovMashuk-KMV (pen.)
- 81′M. MusaevMashuk-KMV
- 89′V. UlyanovskiyTorpedo Miass
What is the recent form of both teams?
Over their last 15 matches in all competitions, Mashuk-KMV have 8 wins, 5 draws and 2 defeats; Torpedo Miass have 7, 3 and 5.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Mar 9, 2024 | Dinamo Bryansk(away) | 1-0 | Second League A - Spring Season Silver |
| Mar 2, 2024 | Volga Ulyanovsk(home) | 1-1 | Second League A - Spring Season Silver |
| Nov 25, 2023 | Druzhba(away) | 5-0 | Second League - Group 1 |
| Nov 19, 2023 | Kuban Kholding(home) | 2-2 | Second League - Group 1 |
| Nov 12, 2023 | Rubin Yalta(away) | 1-0 | Second League - Group 1 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Mar 9, 2024 | Tekstilshchik(home) | 1-2 | Second League A - Spring Season Silver |
| Mar 2, 2024 | Kaluga(home) | 1-1 | Second League A - Spring Season Silver |
| Feb 18, 2024 | FK Sokol Saratov(away) | 0-1 | Friendlies Clubs |
| Feb 2, 2024 | FK Neftekhimik(away) | 0-3 | Friendlies Clubs |
| Nov 12, 2023 | Khimik Vurnary(away) | 0-0 | Second League - Group 4 |
How many goals should we expect?
Mashuk-KMV score 1.3 and concede 0.7 goals per match over their last 15; Torpedo Miass score 1.5 and concede 1.0.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Mashuk-KMV | 1.3 | 0.7 | 8 | 5/15 | 4/15 |
| Torpedo Miass | 1.5 | 1.0 | 6 | 6/15 | 7/15 |
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