Lokomotiv Kyiv vs Kulykiv: result 1-2 and analysis
Druha LigaFinalKick-off on May 31, 2026 at 11:00 AM (UTC)Stadion NTK im. B. M. Bannikova, Kyiv
Full time
What was the result of Lokomotiv Kyiv vs Kulykiv?
Kulykiv won 1-2 on May 31, 2026.
Goalscorers
- 48′O. PanasyukKulykiv
- 56′B. MordasLokomotiv Kyiv
- 87′D. VolkovKulykiv
What is the recent form of both teams?
Over their last 15 matches in all competitions, Lokomotiv Kyiv have 10 wins, 2 draws and 3 defeats; Kulykiv have 10, 4 and 1.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 22, 2026 | Penuel(away) | 2-0 | Druha Liga |
| May 16, 2026 | Hirnyk-Sport(home) | 6-0 | Druha Liga |
| May 10, 2026 | Chornomorets II(away) | 5-0 | Druha Liga |
| May 6, 2026 | Livyi Bereg 2(home) | 3-0 | Druha Liga |
| May 2, 2026 | Rebel(away) | 2-1 | Druha Liga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 22, 2026 | Real Pharm(away) | 3-0 | Druha Liga |
| May 16, 2026 | Bukovyna 2(home) | 2-2 | Druha Liga |
| May 10, 2026 | Vilkhivtsi(away) | 2-0 | Druha Liga |
| May 6, 2026 | Uzhhorod(home) | 1-0 | Druha Liga |
| Apr 25, 2026 | Atlet(home) | 2-0 | Druha Liga |
How many goals should we expect?
Lokomotiv Kyiv score 2.1 and concede 0.7 goals per match over their last 15; Kulykiv score 2.1 and concede 0.4.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Lokomotiv Kyiv | 2.1 | 0.7 | 9 | 4/15 | 7/15 |
| Kulykiv | 2.1 | 0.4 | 11 | 4/15 | 7/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
Lokomotiv Kyiv sit 1st in Druha Liga (70 points from 30 matches) and Kulykiv sit 1st (68 points from 30 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 1 | Lokomotiv Kyiv | 30 | 22 | 4 | 4 | 65 | 16 | 70 |
| 1 | Kulykiv | 30 | 21 | 5 | 4 | 58 | 18 | 68 |
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