· Division 1
Al Akhdoud
ATT
5/10
DEF
5/10
vs
Al Ula
7/10
ATT
7/10
DEF
Programmata· Thu 8 Oct · 17:00
Migliore scelta
GOL DI ENTRAMBE
57%
Risultato esatto
Eccellente
1-1
11.8%
8.48
Eccellente
1-2
8.7%
11.52
0-1
8.7%
11.54
2-1
8%
12.46
1-0
8%
12.49
0-2
6.4%
15.68
2-2
5.9%
16.93
0-0
5.9%
16.99
135%
2.86
X25%
3.99
240%
2.50TOP
1X60%
X265%
1275%
Probable XI4-4-2
Al-Amri
Alex
Hawsawi
Al-Harbi
Al-Zabdani
Hazazi
Aldaghrir
Gül
Al-Jahif
Dambelley
Majrashi
Impact Player Hot Head
Formazioni non ancora annunciate — analisi completa della rosa sotto
Al Akhdoud15 giocatori
49.1/ 99Medio
Migliori
1Rui PedroMID70
2AlexDEF62
3Hatem Al-JahaniGK55
Al Ula30 giocatori
55.0/ 99Forte
Migliori
1Abdulfattah AdamFWD91
2Aseel Abdullah AbdulrazaqFWD84
3Freej Al-JizaniFWD81
Al Akhdoud27
PlayerValutazioneImpattoAggressivitàDisciplina
Rui Pedro70893856
Alex62624567
Hatem Al-Jahani55571750
Mohammed Al-Jahif55653850
Rakan Al-Najjar54542350
Hassan Al-Harbi53562278
Nawaf Al-Hawsawi53444867
Saud Salem52365767
Balla Sangaré46434456
Mohammed Abo Abd45403761
Khaled Al-Lazam45483841
Ali Al-Amri44413556
Agi Dambelley38444326
Al Ula41
PlayerValutazioneImpattoAggressivitàDisciplina
Abdulfattah Adam91906989
Aseel Abdullah Abdulrazaq84999926
Freej Al-Jizani81828561
Efthymios Koulouris76802191
André Horta71973050
Abdulmajeed Al-Sulayhim70634583
Sylla Sow70753173
Damyan Yordanov67996523
Khaled Al-Shamrani66417491
Yousef Al-Honaifesh65706750
Yasser Yaqoub Ibrahim62376775
Ali Al-Zubaidi60308390
Yousef Haqawi59674256
Classifiche giocatori
Cecchini
Maggior minaccia di gol
1
Aseel Abdullah AbdulrazaqAl Ula
99
2
Abdulfattah AdamAl Ula
90
3
Freej Al-JizaniAl Ula
82
4
Efthymios KoulourisAl Ula
80
5
Sylla SowAl Ula
75
Muro
Migliori difensori
1
Khaled Al RuwailyAl Ula
76
2
Yousef HaqawiAl Ula
67
3
Matija NastasićAl Ula
63
4
AlexAl Akhdoud
62
5
Hassan Al-HarbiAl Akhdoud
56
Controllo
Migliori registi
1
Damyan YordanovAl Ula
99
2
André HortaAl Ula
97
3
Rui PedroAl Akhdoud
89
4
Yousef Al-HonaifeshAl Ula
70
5
Mohammed Al-JahifAl Akhdoud
65
Cattivi ragazzi
Più propensi ai cartellini
1
Mohammed Abbas Al-NakhliAl Ula
1
2
Matija NastasićAl Ula
5
3
Khaled Al RuwailyAl Ula
7
4
Faisal Al-AsmariAl Ula
7
5
Ayman Al-KhulaifAl Ula
15
Classifica potenza
Più forti in assoluto
1
Abdulfattah AdamAl Ula
91
2
Aseel Abdullah AbdulrazaqAl Ula
84
3
Freej Al-JizaniAl Ula
81
4
Efthymios KoulourisAl Ula
76
5
André HortaAl Ula
71

Domande frequenti

Our Poisson model calculates the probability of every possible scoreline for Al Akhdoud vs Al Ula 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 Akhdoud vs Al Ula 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 Akhdoud 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 Akhdoud vs Al Ula 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 Akhdoud 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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