Saned Joniškis vs Šiauliai: result 1-3 and analysis
CupRound of 16Kick-off on June 23, 2021 at 03:00 PM (UTC)
Full time
What was the result of Saned Joniškis vs Šiauliai?
Šiauliai won 1-3 on June 23, 2021.
Goalscorers
- 18′J. PetravičiusŠiauliai
- 29′315549Saned Joniškis
- 45′Algis JankauskasŠiauliai
- 90′D. DovydaitisŠiauliai
Official lineup for Saned Joniškis vs Šiauliai
The starting elevens fielded at kick-off.
Saned Joniškis
- MMarius Šluta
- GG. Gutkovas
- JJ. Budrys
- VV. Šimkus
- EE. Nocius
- PP. Bieliauskas
- DD. Kelpšas
- DD. Nacickas
- KKildras Kavaliukas
- KK. Bagočius
- SS. Kužmarskis
Šiauliai
- DD. Dovydaitis
- JJ. Petravičius
- DD. Kubilinskas
- SSergej Amirzian
- GGabrielius Micevičius
- SS. Paulius
- EE. Pilypas
- AAlgis Jankauskas
- RR. Lekiatas
- KK. Mantinis
- GG. Baliutavičius
What is the recent form of both teams?
Over their last 2 matches in all competitions, Saned Joniškis have 1 win, 0 draws and 1 defeat; Šiauliai have 11, 2 and 2.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 22, 2021 | Fortūna Kaunas(away) | 4-0 | Cup |
| Jun 28, 2020 | Viltis Vilnius(away) | 0-11 | Cup |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 19, 2021 | Panevėžys II(away) | 1-2 | 1 Lyga |
| Jun 12, 2021 | Žalgiris II(home) | 5-0 | 1 Lyga |
| May 22, 2021 | Panerys Vilnius(away) | 2-1 | Cup |
| May 16, 2021 | Kauno Žalgiris II(away) | 2-0 | 1 Lyga |
| May 8, 2021 | Atmosfera(home) | 5-1 | 1 Lyga |
How many goals should we expect?
Saned Joniškis score 2.0 and concede 5.5 goals per match over their last 2; Šiauliai score 2.7 and concede 0.7.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Saned Joniškis | 2.0 | 5.5 | 1 | 0/2 | 2/2 |
| Šiauliai | 2.7 | 0.7 | 7 | 7/15 | 11/15 |
Over the last 2 matches in all competitions.
A question about Saned Joniškis vs Šiauliai?
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