· Stars League
Al Shahaniya
ATT
5/10
DEF
5/10
vs
Al-Sadd
10/10
ATT
5/10
DEF
Scheduled· Thu 22 Oct · 14:30
Best Pick
Over 2.5
65%
Correct Score
Top
1-1
9.7%
13.00
Top
1-2
9.4%
10.00
0-1
7%
15.00
0-2
6.8%
11.00
2-1
6.7%
23.00
2-2
6.5%
17.00
1-3
6.1%
10.00
1-0
5%
34.00
127%
7.00
X22%
6.00
251%
1.27TOP
1X49%
X273%
1278%

Combined Bet Builder

3 legs

Al-Sadd’s 2.78 xG and explosive +105% attack power make them strong favorites to win, while Al Shahaniya’s 1.14 xG gives the hosts a credible route to score. With both defenses rated stable rather than dominant, the match profile points toward goals at both ends and over 3.5 overall.

1Match WinnerAl-Sadd
2Match GoalsOver 3.5
3Both Teams to ScoreYes
Probable XI4-4-2
Mordou
Al-Salati
Al-Salati
Ellethy
Naser
Meherzi
Al-Yazidi
Sulimane
Qadry
Moustafa
Traore
Impact Player Hot Head
Lineups not yet announced — full squad analysis below
Al Shahaniya26 players
50.1/ 99Average
Top Rated
1Francesco Antonucci MID79
2Abdulla Al-SalatiDEF69
3Ali QadryMID67
Al-Sadd32 players
50.1/ 99Average
Top Rated
1Abdessamed BounacerDEF94
2ClaudinhoMID82
3Paul CaddisMID71
Al Shahaniya39
PlayerOverall RatingImpactAggressionDiscipline
Francesco Antonucci 79993466
Abdulla Al-Salati69546870
Ali Qadry67844550
Sven van Beek62632491
Álvaro Sanz60504676
Mohammed Balah58515372
Pelle van Amersfoort57457468
A. Meherzi55555850
Zvonimir Sarlija54585646
Omar Al-Emadi53485856
Ibrahima Diallo51418447
Abdoulaye Traore5172251
Abdulrahman Mussed51476056
Al-Sadd41
PlayerOverall RatingImpactAggressionDiscipline
Abdessamed Bounacer94995879
Claudinho82913784
Paul Caddis71588273
Ahmed Suhail67683878
Hashim Ali67626967
Youcef Atal61456767
Rafa Mujica61547859
Yusuf Abdurisag58425691
Tarek Salman57435371
Meshaal Barsham5657950
Younes El Hannach55318957
Marcelo Brozović55564856
Alessio Romagnoli 54494267
Player Rankings
Snipers
Top goal threats
1
Abdoulaye TraoreAl Shahaniya
72
2
Hashim AliAl-Sadd
62
3
GiovaniAl-Sadd
56
4
Rafa MujicaAl-Sadd
54
5
LucãoAl Shahaniya
51
Wall
Top defenders
1
Abdessamed BounacerAl-Sadd
99
2
Ahmed SuhailAl-Sadd
68
3
Sven van BeekAl Shahaniya
63
4
Zvonimir SarlijaAl Shahaniya
58
5
Abdulla Al-SalatiAl Shahaniya
54
Control
Top playmakers
1
Francesco Antonucci Al Shahaniya
99
2
ClaudinhoAl-Sadd
91
3
Ali QadryAl Shahaniya
84
4
Paul CaddisAl-Sadd
58
5
Marcelo BrozovićAl-Sadd
56
Bad Boys
Most likely to get booked
1
Bahaa EllethyAl Shahaniya
1
2
Abdoulaye TraoreAl Shahaniya
1
3
Anas Abdulsalam AbwenyAl-Sadd
1
4
Mohamed Camara Al-Sadd
1
5
Marc MuniesaAl Shahaniya
5
Power Rankings
Strongest overall
1
Abdessamed BounacerAl-Sadd
94
2
ClaudinhoAl-Sadd
82
3
Francesco Antonucci Al Shahaniya
79
4
Paul CaddisAl-Sadd
71
5
Abdulla Al-SalatiAl Shahaniya
69

Frequently Asked Questions

Our Poisson model calculates the probability of every possible scoreline for Al Shahaniya vs Al-Sadd 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 Shahaniya vs Al-Sadd 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 Shahaniya 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 Shahaniya vs Al-Sadd 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 Shahaniya 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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