· AFC Cup
Kuwait SC
ATT
5/10
DEF
5/10
vs
FC Nasaf
5/10
ATT
6/10
DEF
Scheduled· Wed 4 Nov · 16:00
Best Pick
BTTS
54%
Correct Score
Top
1-1
11.4%
8.74
Top
1-0
10.5%
9.52
2-1
9.7%
10.35
2-0
8.9%
11.27
0-1
6.8%
14.77
1-2
6.2%
16.06
0-0
6.2%
16.08
3-1
5.4%
18.39
151%
1.95TOP
X24%
4.15
224%
4.08
1X75%
X248%
1275%
Probable XI4-4-2
Kameel
Zola
Hammoud
Al-Saab
Al-Enezi
Al-Qarzaei
Al-Dhefiri
Dara
Jesús
Amoory
Kameel
Impact Player Hot Head
Lineups not yet announced — full squad analysis below
Kuwait SC15 players
52.1/ 99Average
Top Rated
1Fahad HammoudDEF75
2Yousef NasserFWD70
3Sami Al-SaneaDEF62
FC Nasaf14 players
53.8/ 99Average
Top Rated
1Alibek DavronovDEF67
2Murodbek RahmatovMID64
3Bobur AbdikholikovFWD61
Kuwait SC35
PlayerOverall RatingImpactAggressionDiscipline
Fahad Hammoud75994550
Yousef Nasser70676467
Sami Al-Sanea62705450
Oumar Gonzalez 56674050
Ahmad Al-Dhefiri56534961
Ali Pour Dara54534956
Saud Al-Hoshan53543450
Mohammad Freih50484161
Mohsen Ghareeb48504550
Redha Hani47464750
Taha Yassine Khenissi47434461
Arsène Zola46624130
Meshari Ghanam46454550
FC Nasaf27
PlayerOverall RatingImpactAggressionDiscipline
Alibek Davronov67466083
Murodbek Rahmatov64625067
Bobur Abdikholikov61565372
Zafarmurod Abdurakhmatov58485367
Sharof Mukhiddinov58604261
Umar Eshmuradov56525161
Oybek Rustamov53596040
Adenis Shala52514856
Abduvokhid Nematov51513450
Abbos Gulomov51455461
Diyorbek Abdunazarov49455650
Yusuf Otubanjo47425556
Akramzhon Komilov44424550
Player Rankings
Snipers
Top goal threats
1
Yousef NasserKuwait SC
67
2
Bobur AbdikholikovFC Nasaf
56
3
Adenis ShalaFC Nasaf
51
4
Abbos GulomovFC Nasaf
45
5
Taha Yassine KhenissiKuwait SC
43
Wall
Top defenders
1
Fahad HammoudKuwait SC
99
2
Sami Al-SaneaKuwait SC
70
3
Oumar Gonzalez Kuwait SC
67
4
Arsène ZolaKuwait SC
62
5
Golib GaybullaevFC Nasaf
53
Control
Top playmakers
1
Murodbek RahmatovFC Nasaf
62
2
Sharof MukhiddinovFC Nasaf
60
3
Oybek RustamovFC Nasaf
59
4
Ahmad Al-DhefiriKuwait SC
53
5
Ali Pour DaraKuwait SC
53
Bad Boys
Most likely to get booked
1
Abdullah Al-QarzaeiKuwait SC
13
2
E. BarrahmaKuwait SC
18
3
Arsène ZolaKuwait SC
30
4
Golib GaybullaevFC Nasaf
30
5
Oybek RustamovFC Nasaf
40
Power Rankings
Strongest overall
1
Fahad HammoudKuwait SC
75
2
Yousef NasserKuwait SC
70
3
Alibek DavronovFC Nasaf
67
4
Murodbek RahmatovFC Nasaf
64
5
Sami Al-SaneaKuwait SC
62

Frequently Asked Questions

Our Poisson model calculates the probability of every possible scoreline for Kuwait SC vs FC Nasaf 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 Kuwait SC vs FC Nasaf 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 Kuwait SC 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 Kuwait SC vs FC Nasaf 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 Kuwait SC 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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