Šilas vs Jonava: prediction and stats
1 LygaRegular Season - 12Kick-off on October 21, 2023 at 11:00 AM (UTC)Prienų stadionas, Prienai
Match cancelled
What is the recent form of both teams?
Over their last 15 matches in all competitions, Šilas have 4 wins, 2 draws and 9 defeats; Jonava have 2, 1 and 12.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 25, 2023 | Kauno Žalgiris II(away) | 0-3 | 1 Lyga |
| Sep 15, 2023 | Babrungas(away) | 2-6 | 1 Lyga |
| Sep 6, 2023 | Trakai II(home) | 0-4 | 1 Lyga |
| Aug 30, 2023 | BFA(home) | 0-0 | 1 Lyga |
| Aug 26, 2023 | Ekranas(away) | 1-0 | 1 Lyga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 13, 2023 | Babrungas(away) | 1-2 | 1 Lyga |
| Oct 7, 2023 | BFA(home) | 0-3 | 1 Lyga |
| Sep 29, 2023 | Ekranas(away) | 3-4 | 1 Lyga |
| Sep 17, 2023 | Panevėžys II(away) | 1-4 | 1 Lyga |
| Sep 1, 2023 | Garliava(home) | 2-1 | 1 Lyga |
What does the head-to-head say?
Across the last 6 meetings: 2 Šilas wins, 0 draws, 4 Jonava wins.
| Date | Score | Competition |
|---|---|---|
| Jun 4, 2023 | Jonava 0-2 Šilas | 1 Lyga |
| Aug 14, 2021 | Šilas 2-3 Jonava | 1 Lyga |
| Apr 16, 2021 | Jonava 3-2 Šilas | 1 Lyga |
| Aug 21, 2015 | Šilas 1-0 Jonava | 1 Lyga |
| May 12, 2015 | Jonava 4-0 Šilas | 1 Lyga |
| Sep 20, 2014 | Jonava 4-2 Šilas | 1 Lyga |
How many goals should we expect?
Šilas score 0.8 and concede 2.5 goals per match over their last 15; Jonava score 0.9 and concede 2.8.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Šilas | 0.8 | 2.5 | 6 | 5/15 | 9/15 |
| Jonava | 0.9 | 2.8 | 1 | 8/15 | 12/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 10 | Jonava | 26 | 7 | 6 | 13 | 28 | 35 | 27 |
A question about Šilas vs Jonava?
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