· Uae League
Al Wasl
ATT
6/10
DEF
8/10
vs
Al Dhafra
3/10
ATT
3/10
DEF
Programmata· Fri 30 Oct · 12:55
Migliore scelta
Vittoria in casa
69%
Risultato esatto
Eccellente
2-0
11.7%
8.57
Eccellente
1-0
10.5%
9.57
2-1
9.7%
10.31
3-0
8.7%
11.51
1-1
8.7%
11.51
3-1
7.2%
13.86
4-0
4.8%
20.62
0-0
4.7%
21.37
169%
1.45TOP
X18%
5.46
213%
7.98
1X87%
X231%
1282%
Probable XI4-4-2
Amer
Saleh
Adryelson
Vareta
Hugo 
Ahmed
Puertas
Lima
Alves
Saleh
Bousso
Impact Player Hot Head
Formazioni non ancora annunciate — analisi completa della rosa sotto
Al Wasl33 giocatori
51.4/ 99Medio
Migliori
1SerginhoFWD86
2Gabriel VaretaDEF77
3AdryelsonDEF73
Al Dhafra32 giocatori
49.5/ 99Medio
Migliori
1Rostand Delord Menpweh DjoohMID71
2Leonard AmasimekuDEF64
3Zayed Al AmeriFWD64
Al Wasl38
PlayerValutazioneImpattoAggressivitàDisciplina
Serginho86994856
Gabriel Vareta77606391
Adryelson73803382
Malek Janeer72607971
Tahnoon Al-Zaabi67556272
Ridwan Popoola65478071
Hugo 61405583
Takashi Uchino61317591
Siaka Sidibe60605060
Nicolás Giménez59754143
Abdulrahman Saleh58269991
Pedro Malheiro57256391
Miguel Borja57605449
Al Dhafra39
PlayerValutazioneImpattoAggressivitàDisciplina
Rostand Delord Menpweh Djooh71545884
Leonard Amasimeku64525376
Zayed Al Ameri64752850
Mansor Al Harbi62358191
Zé Welinton60515667
Serafim59544569
Arielson59486972
Marcelinho59486474
Dramane Koumare58742756
Feras Saleh Alkhaseebi57564761
Mohammed Ibrahim Al Hammadi55746311
Ezeckiel Noumonvi54403985
Vitinho54623950
Classifiche giocatori
Cecchini
Maggior minaccia di gol
1
SerginhoAl Wasl
99
2
Brahian PalaciosAl Wasl
79
3
Zayed Al AmeriAl Dhafra
75
4
Mohammed Ibrahim Al HammadiAl Dhafra
74
5
Renato JúniorAl Wasl
62
Muro
Migliori difensori
1
AdryelsonAl Wasl
80
2
Dramane KoumareAl Dhafra
74
3
Mouhcine RabjaAl Dhafra
70
4
Sasa IvkovicAl Wasl
65
5
Gabriel VaretaAl Wasl
60
Controllo
Migliori registi
1
Nicolás GiménezAl Wasl
75
2
Renato TapiaAl Wasl
63
3
VitinhoAl Dhafra
62
4
Malek JaneerAl Wasl
60
5
Siaka SidibeAl Wasl
60
Cattivi ragazzi
Più propensi ai cartellini
1
Soufiane BouftiniAl Wasl
1
2
Renato TapiaAl Wasl
1
3
Brahian PalaciosAl Wasl
1
4
Mouhcine RabjaAl Dhafra
1
5
Yousif AlmarzooqiAl Dhafra
1
Classifica potenza
Più forti in assoluto
1
SerginhoAl Wasl
86
2
Gabriel VaretaAl Wasl
77
3
AdryelsonAl Wasl
73
4
Malek JaneerAl Wasl
72
5
Rostand Delord Menpweh DjoohAl Dhafra
71

Domande frequenti

Our Poisson model calculates the probability of every possible scoreline for Al Wasl vs Al Dhafra 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 Al Wasl vs Al Dhafra 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 Al Wasl 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 Al Wasl vs Al Dhafra 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 Al Wasl 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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