· AFC Champions League Elite
Al Ittihad
ATT
7/10
DEF
7/10
vs
Al Ain
6/10
ATT
5/10
DEF
Programmata· Mon 2 Nov · 18:15
Migliore scelta
Vittoria in casa
57%
Risultato esatto
Eccellente
1-0
11%
9.12
Eccellente
1-1
10.9%
9.18
2-0
9.9%
10.06
2-1
9.9%
10.13
0-0
6%
16.53
3-0
6%
16.65
0-1
6%
16.65
3-1
6%
16.76
157%
1.77TOP
X23%
4.36
220%
4.88
1X80%
X243%
1277%
Probable XI4-4-2
Al-Shanqity
Al-Julaydan
Sharahili
Pereira
Abdi
Hawsawi
Ortega
Lopy
Al-Ghamdi
Al-Oboud
Bishri
Impact Player Hot Head
Formazioni non ancora annunciate — analisi completa della rosa sotto
Al Ittihad30 giocatori
47.9/ 99Medio
Migliori
1Mahamadou DoumbiaMID74
2Mukhtar AliMID74
3Houssem AouarMID62
Al Ain16 giocatori
57.1/ 99Forte
Migliori
1H. RahimiFWD68
2Đorđe SkokoDEF66
3ErikDEF65
Al Ittihad47
PlayerValutazioneImpattoAggressivitàDisciplina
Mahamadou Doumbia74745472
Mukhtar Ali74687961
Houssem Aouar62583183
Youssef En-Nesyri59543583
Faisal Al-Ghamdi56653950
Roger Fernandes55534861
Dion Lopy54544556
Predrag Rajković53536556
Faris Abdi53365867
Hassan Kadesh52434172
Hamed Al-Ghamdi52544850
George Ilenikhena51424278
Saleh Al-Shehri51495750
Al Ain33
PlayerValutazioneImpattoAggressivitàDisciplina
H. Rahimi68904619
Đorđe Skoko66486078
Erik65449978
Y. Ben Khaleq65457172
Rafa Rodrigues63446672
M. Palacios61594767
A. Traoré59504872
Marcos André58674550
Georgios Giakoumakis57598141
Rami Rabia54544361
S. Rahimi54554256
Khalid Eissa52523450
Alejandro Romero50594938
Classifiche giocatori
Cecchini
Maggior minaccia di gol
1
H. RahimiAl Ain
90
2
Georgios GiakoumakisAl Ain
59
3
S. RahimiAl Ain
55
4
Youssef En-NesyriAl Ittihad
54
5
Roger FernandesAl Ittihad
53
Muro
Migliori difensori
1
Marcos AndréAl Ain
67
2
Danilo PereiraAl Ittihad
58
3
Rami RabiaAl Ain
54
4
Stephane KellerAl Ittihad
49
5
Saad Al-MousaAl Ittihad
48
Controllo
Migliori registi
1
Mahamadou DoumbiaAl Ittihad
74
2
Mukhtar AliAl Ittihad
68
3
Faisal Al-GhamdiAl Ittihad
65
4
Alejandro RomeroAl Ain
59
5
M. PalaciosAl Ain
59
Cattivi ragazzi
Più propensi ai cartellini
1
Abdulrahman Al-OboudAl Ittihad
1
2
Jan-Carlo SimićAl Ittihad
4
3
Richard RíosAl Ittihad
11
4
H. RahimiAl Ain
19
5
Ahmed Al-JulaydanAl Ittihad
36
Classifica potenza
Più forti in assoluto
1
Mahamadou DoumbiaAl Ittihad
74
2
Mukhtar AliAl Ittihad
74
3
H. RahimiAl Ain
68
4
Đorđe SkokoAl Ain
66
5
ErikAl Ain
65

Domande frequenti

Our Poisson model calculates the probability of every possible scoreline for Al Ittihad vs Al Ain 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 Ittihad vs Al Ain 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 Ittihad 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 Ittihad vs Al Ain 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 Ittihad 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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