Izberbash vs Sevastopol: result 0-3 and analysis
Second League - Group 1Group 1 - 3Kick-off on April 11, 2026 at 12:00 PM (UTC)
Full time
What was the result of Izberbash vs Sevastopol?
Sevastopol won 0-3 on April 11, 2026.
Goalscorers
- 24′V. GevlychSevastopol
- 54′A. DuguSevastopol
- 90′M. SuprunSevastopol
What is the recent form of both teams?
Over their last 2 matches in all competitions, Izberbash have 1 win, 0 draws and 1 defeat; Sevastopol have 11, 4 and 0.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 4, 2026 | Nart Cherkessk(away) | 0-5 | Second League - Group 1 |
| Mar 28, 2026 | Druzhba(home) | 2-1 | Second League - Group 1 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 4, 2026 | Rostov II(home) | 2-1 | Second League - Group 1 |
| Mar 28, 2026 | Lugansk(away) | 4-1 | Second League - Group 1 |
| Feb 20, 2026 | Orel(away) | 6-3 | Friendlies Clubs |
| Feb 15, 2026 | Irtysh Omsk(away) | 2-0 | Friendlies Clubs |
| Feb 1, 2026 | Chernomorets(away) | 1-1 | Friendlies Clubs |
How many goals should we expect?
Izberbash score 1.0 and concede 3.0 goals per match over their last 2; Sevastopol score 2.1 and concede 0.8.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Izberbash | 1.0 | 3.0 | 0 | 1/2 | 2/2 |
| Sevastopol | 2.1 | 0.8 | 6 | 9/15 | 7/15 |
Over the last 2 matches in all competitions.
Where do both teams sit in the table?
Izberbash sit 12th in Second League - Group 1 (18 points from 21 matches) and Sevastopol sit 1st (50 points from 21 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 1 | Sevastopol | 21 | 16 | 2 | 3 | 38 | 17 | 50 |
| 12 | Izberbash | 21 | 6 | 0 | 15 | 19 | 57 | 18 |
A question about Izberbash vs Sevastopol?
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