· Virsliga
Grobiņa
ATT
3/10
DEF
5/10
vs
Riga
10/10
ATT
7/10
DEF
Programmata· Mon 26 Oct · 16:00
Migliore scelta
Vittoria in trasferta
66%
Risultato esatto
Eccellente
0-1
14%
9.50
Eccellente
0-2
13.3%
7.00
1-1
9.9%
13.00
1-2
9.4%
10.00
0-3
8.4%
7.50
0-0
7.4%
21.00
1-3
6%
11.00
1-0
5.2%
29.00
113%
10.00
X21%
6.00
266%
1.18TOP
1X34%
X287%
1279%

Combinata

3 selezioni

Riga FC are the clear attacking force: their 2.39 xG and +100% attack power point to sustained pressure and a strong case for the away win. Grobinas’ 0.65 xG makes a goal the main hurdle, but even a limited contribution could combine with Riga’s scoring threat to push this toward over 3.5 goals and both teams to score.

1Match WinnerRiga FC
2Match GoalsOver 3.5
3Both Teams to ScoreYes
Probable XI4-4-2
Pinčuks
Jovanović
Molotkovs
Druzinins
Leitans
Zjuzins
Sirbu
Galata
Kļuškins
Aruna
Baydal
Impact Player Hot Head
Formazioni non ancora annunciate — analisi completa della rosa sotto
Grobiņa28 giocatori
46.0/ 99Medio
Migliori
1Davids DruzininsDEF69
2Aleksa JovanovićDEF64
3Aleksandrs MolotkovsDEF63
Riga31 giocatori
50.9/ 99Medio
Migliori
1Salah Oulad M'HandMID78
2Ahmed AnkrahMID72
3Juan ChristianFWD72
Grobiņa36
PlayerValutazioneImpattoAggressivitàDisciplina
Davids Druzinins69695762
Aleksa Jovanović64821872
Aleksandrs Molotkovs63576261
Dodo57435883
Devids Dobrecovs56515367
Hirotaka Yamada55377860
Roberts Ozols53525256
A. Aruna53514361
Gustavs Leitans52635337
Vjačeslavs Kudrjavcevs51485761
Dans Sirbu51403478
Gļebs Kļuškins50596731
Olgerts Rascevskis49454861
Riga41
PlayerValutazioneImpattoAggressivitàDisciplina
Salah Oulad M'Hand78717368
Ahmed Ankrah72737554
Juan Christian72785356
Coli Saco71654978
Renars Varslavans69593991
Mohamed Badamosi5880547
Marko Regza57495272
Abner 56574261
Iago Siqueira56813730
Raki Aouani55544661
Karl Gameni Wassom54675735
Kenan Piric52534550
Caio Ferreira52534550
Classifiche giocatori
Cecchini
Maggior minaccia di gol
1
Mohamed BadamosiRiga
80
2
Juan ChristianRiga
78
3
Reginaldo RamiresRiga
69
4
Raki AouaniRiga
54
5
Caio FerreiraRiga
53
Muro
Migliori difensori
1
Aleksa JovanovićGrobiņa
82
2
Davids DruzininsGrobiņa
69
3
Gustavs LeitansGrobiņa
63
4
Aleksandrs MolotkovsGrobiņa
57
5
Abner Riga
57
Controllo
Migliori registi
1
Iago SiqueiraRiga
81
2
Ahmed AnkrahRiga
73
3
Salah Oulad M'HandRiga
71
4
Karl Gameni WassomRiga
67
5
Coli SacoRiga
65
Cattivi ragazzi
Più propensi ai cartellini
1
Ivan TyshchenkoGrobiņa
1
2
J. RibeiroGrobiņa
1
3
Maksims FjodorovsGrobiņa
1
4
Brian PeñaRiga
1
5
Reginaldo RamiresRiga
1
Classifica potenza
Più forti in assoluto
1
Salah Oulad M'HandRiga
78
2
Ahmed AnkrahRiga
72
3
Juan ChristianRiga
72
4
Coli SacoRiga
71
5
Davids DruzininsGrobiņa
69

Domande frequenti

Our Poisson model calculates the probability of every possible scoreline for Grobiņa vs Riga based on each team's expected goals (xG). The top-3 most likely scorelines are shown above with their probability percentages. Even the highest-probability score rarely exceeds 12-15% chance, as football is a low-scoring sport.

The Bet Builder combines multiple selections from the Grobiņa vs Riga match into one bet. Our AI identifies outcomes that complement each other — for example, a home win paired with over 2.5 goals and both teams to score. All selections must win for the combined bet to pay out, which means higher combined odds but also higher risk.

xG (expected goals) measures the quality of scoring chances. If Grobiņa has an xG of 1.8, it means they are expected to score around 1-2 goals based on chance quality. The model uses pre-match xG to build a probability table for all possible scorelines. A team can overperform xG (score more than expected) or underperform xG (score fewer).

Yes, all predictions on ProSoccer are completely free. You can view predicted scorelines, over/under probabilities, and bet builder suggestions for Grobiņa vs Riga without paying or registering. Odds values are revealed after a tap to keep the page compliant with search engine guidelines.

A value bet occurs when the probability of an outcome is higher than what the bookmaker odds suggest. For example, if our model gives Grobiņa a 55% chance of winning but the odds imply only 40%, that is a value bet. Our AI highlights selections where the model probability exceeds the implied probability from the odds.

AI predictions use statistical modeling (Poisson distribution) based on historical data and pre-match metrics. They are more reliable over large samples than for any single match. No prediction is guaranteed — football has inherent unpredictability. Our model typically identifies the correct top-3 scorelines in 25-30% of matches, which is significantly better than random chance.

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