Murom vs Irkutsk: prediction and stats
Second League - Group 2Group 2 - 8Kick-off on May 17, 2026 at 02:00 PM (UTC)Stadion Park 50, Murom
Match cancelled
What is the recent form of both teams?
Over their last 15 matches in all competitions, Murom have 5 wins, 3 draws and 7 defeats; Irkutsk have 5, 2 and 8.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 10, 2026 | Dinamo Vologda(away) | 1-0 | Second League - Group 2 |
| May 3, 2026 | Baltika II(home) | 2-1 | Second League - Group 2 |
| Apr 26, 2026 | Yenisey II(away) | 1-0 | Second League - Group 2 |
| Apr 19, 2026 | Chertanovo Moscow(home) | 1-1 | Second League - Group 2 |
| Apr 12, 2026 | Kosmos Dolgoprudny(away) | 1-0 | Second League - Group 2 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 14, 2026 | Spartak Moscow 2(home) | 0-1 | Second League - Group 2 |
| May 10, 2026 | Luki-Energiya(home) | 0-1 | Second League - Group 2 |
| Apr 26, 2026 | Torpedo Vladimir(home) | 2-1 | Second League - Group 2 |
| Apr 12, 2026 | Dinamo Vologda(away) | 0-3 | Second League - Group 2 |
| Apr 5, 2026 | Baltika II(home) | 0-1 | Second League - Group 2 |
How many goals should we expect?
Murom score 0.9 and concede 1.3 goals per match over their last 15; Irkutsk score 0.9 and concede 1.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Murom | 0.9 | 1.3 | 6 | 6/15 | 7/15 |
| Irkutsk | 0.9 | 1.3 | 4 | 6/15 | 7/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
Murom sit 1st in Second League - Group 2 (44 points from 21 matches) and Irkutsk sit 15th (11 points from 21 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 1 | Murom | 21 | 14 | 2 | 5 | 35 | 17 | 44 |
| 15 | Irkutsk | 21 | 3 | 2 | 16 | 11 | 46 | 11 |
A question about Murom vs Irkutsk?
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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