FK Liepaja’s 2.09 xG and +18% attack edge point to sustained scoring pressure, while Tukums’ defense is 32% weaker than average. Liepaja’s 1.27 first-half xG against Tukums’ 0.27 makes a fast home lead likely; with the visitors adding some scoring potential, Over 2.5 and a Liepaja win form the logical bet builder.
1Match WinnerFK Liepaja
2Match GoalsOver 2.5
3First Half WinnerFK Liepaja
Probable XI4-4-2
Sorokins
Molotkovs
Silva
Straalman
Junior
Haïdara
Korobenko
Cardoso
Mshindi
Ogunniyi
Leite
Impact Player Hot Head
Sestavy ještě nebyly oznámeny — níže kompletní analýza kádru
FK Liepaja35 hráči
50.7/ 99Průměrný
Nejlepší
1Andriy KorobenkoMID78
2Ivans PatrikejevsMID73
3Afonso LeiteFWD73
FK Tukums 2000/TSS31 hráči
52.5/ 99Průměrný
Nejlepší
1Joseph Oloko EdeFWD91
2Renē BaumanisMID90
3Rudolfs MelkisDEF79
FK Liepaja38
PlayerCelkové HodnoceníImpaktAgreseDisciplína
Andriy Korobenko78763891
Ivans Patrikejevs73606179
Afonso Leite73844550
Abiodun Ogunniyi69586889
Rodolphe Ekou66568756
Aleksandrs Molotkovs63576261
Lauris Lākutis59585856
Ilja Korotkovs58564367
Amilcar Júnior Silva56355974
Dodo56406289
Vladislavs Sorokins54476454
Kyvon Leidsman54367691
Alvis Sorokins51514550
FK Tukums 2000/TSS38
PlayerCelkové HodnoceníImpaktAgreseDisciplína
Joseph Oloko Ede91996165
Renē Baumanis90869989
Rudolfs Melkis79658489
Shun Shibata68566275
Koyo Shigema67537567
Rudolfs Reingolcs66617554
Bogdans Samoilovs59702660
Emīls Sprukts55438067
Iļja Atligins55458261
Davis Valmiers54517544
Jun Toba54434968
Yushin Koki54495656
Niks Dusalijevs54495361
Žebříčky hráčů
Střelci
Největší gólová hrozba
1
Joseph Oloko EdeFK Tukums 2000/TSS
99
2
Afonso LeiteFK Liepaja
84
3
Abiodun OgunniyiFK Liepaja
58
4
Djibril GuèyeFK Liepaja
57
5
Danila PatijcuksFK Liepaja
51
Zeď
Nejlepší obránci
1
João Pedro de Souza BorgesFK Liepaja
71
2
Vjačeslavs IsajevsFK Liepaja
67
3
Helvijs JokstsFK Tukums 2000/TSS
67
4
Rudolfs MelkisFK Tukums 2000/TSS
65
5
Rudolfs ReingolcsFK Tukums 2000/TSS
61
Kontrola
Nejlepší tvůrci hry
1
Renē BaumanisFK Tukums 2000/TSS
86
2
Andriy KorobenkoFK Liepaja
76
3
Bogdans SamoilovsFK Tukums 2000/TSS
70
4
Fellipe CardosoFK Liepaja
68
5
Leonel StrumiaFK Liepaja
62
Zlobivci
Nejpravděpodobnější žlutá karta
1
Vjačeslavs IsajevsFK Liepaja
2
Agresivita 48
2
Danila PatijcuksFK Liepaja
3
Agresivita 67
3
Allan EnyouFK Tukums 2000/TSS
3
Agresivita 41
4
Martins StalsFK Tukums 2000/TSS
15
Agresivita 52
5
João Pedro de Souza BorgesFK Liepaja
16
Agresivita 39
Žebříček síly
Nejsilnější celkově
1
Joseph Oloko EdeFK Tukums 2000/TSS
91
2
Renē BaumanisFK Tukums 2000/TSS
90
3
Rudolfs MelkisFK Tukums 2000/TSS
79
4
Andriy KorobenkoFK Liepaja
78
5
Ivans PatrikejevsFK Liepaja
73
Frequently Asked Questions
Our Poisson model calculates the probability of every possible scoreline for FK Liepaja vs FK Tukums 2000/TSS 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 FK Liepaja vs FK Tukums 2000/TSS 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 FK Liepaja 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 FK Liepaja vs FK Tukums 2000/TSS 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 FK Liepaja 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.