· Turkish Cup
Pazarspor
ATT
5/10
DEF
5/10
0:1
Aliağa FAŞ
5/10
ATT
4/10
DEF
Full-time
Best Pick
Over 2.5
66%
Correct Score93′
Top
1-1
9.3%
8.00
Top
2-1
9.3%
12.00
1-2
6.6%
9.00
1-0
6.6%
13.00
2-2
6.6%
13.00
2-0
6.6%
21.00
3-1
6.2%
26.00
0-1
4.6%
10.00
151%
1.95TOP
X22%
4.62
227%
3.71
1X73%
X249%
1278%
xG — Expected Goals
Pazarspor
Pazarspor exp
Aliağa FAŞ
Aliağa FAŞ exp
goal
per 15 min
0–15′
15–30′
30–45′
45–60′
60–75′
75–90′
Pazarspor
Aliağa FAŞ
Probable XI4-4-2
İlidi
Çağlayan
Şahin
Civelek
Meral
Çelik
Kartal
Bozacı
Vatansever
Taşdemir
Erol
Impact Player Hot Head
Lineups not yet announced — full squad analysis below
Pazarspor1 players
46.0/ 99Average
Top Rated
1Mert OzyildirimMID46
Aliağa FAŞ27 players
41.0/ 99Average
Top Rated
1Malik KaraahmetFWD59
2İbrahim YilmazFWD55
3Mertcan AçıkgözFWD54
Pazarspor45
PlayerOverall RatingImpactAggressionDiscipline
Mert Ozyildirim46454550
A. İlidi————
Ahmet Çağrı Güney————
D. Vural————
Eren Girgin————
A. Çağlayan————
Abdullah Şahin————
Aykut Civelek————
Bekir Mustafa Meral————
Can Bozaci————
Emre Akgun————
Eren Bayar————
Eren Türkkal————
Aliağa FAŞ59
PlayerOverall RatingImpactAggressionDiscipline
Malik Karaahmet59644550
İbrahim Yilmaz55584550
Mertcan Açıkgöz54574550
Emre Keskin46454550
Yusuf Yıldırım45454550
Koray Kılınç45454550
Mustafa Tahir Babaoğlu45454550
Alberk Koc41393950
Caner Cavlan41393950
Eren Tunalı41393950
K. Adar41393950
Oktay Kanci41393950
Sergen Piçinciol41393950
Player Rankings
Snipers
Top goal threats
1
Malik KaraahmetAliağa FAŞ
64
2
İbrahim YilmazAliağa FAŞ
58
3
Mertcan AçıkgözAliağa FAŞ
57
4
Koray KılınçAliağa FAŞ
45
5
Mustafa Tahir BabaoğluAliağa FAŞ
45
Wall
Top defenders
1
Yusuf YıldırımAliağa FAŞ
45
2
Alberk KocAliağa FAŞ
39
3
Caner CavlanAliağa FAŞ
39
4
Eren TunalıAliağa FAŞ
39
5
K. AdarAliağa FAŞ
39
Control
Top playmakers
1
Mert OzyildirimPazarspor
45
2
Emre KeskinAliağa FAŞ
45
3
Cumali BişiAliağa FAŞ
39
4
Hasan KiliçAliağa FAŞ
39
5
Muammer SarıkayaAliağa FAŞ
39
Bad Boys
Most likely to get booked
1
Mert OzyildirimPazarspor
50
2
Alberk KocAliağa FAŞ
50
3
Caner CavlanAliağa FAŞ
50
4
Eren TunalıAliağa FAŞ
50
5
Erhan KartalAliağa FAŞ
50
Power Rankings
Strongest overall
1
Malik KaraahmetAliağa FAŞ
59
2
İbrahim YilmazAliağa FAŞ
55
3
Mertcan AçıkgözAliağa FAŞ
54
4
Mert OzyildirimPazarspor
46
5
Emre KeskinAliağa FAŞ
46

Frequently Asked Questions

Our Poisson model calculates the probability of every possible scoreline for Pazarspor vs Aliağa FAŞ 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 Pazarspor vs Aliağa FAŞ 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 Pazarspor 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 Pazarspor vs Aliağa FAŞ 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 Pazarspor 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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