· Turkish Cup
Yıldırım Belediyesispor
ATT
5/10
DEF
5/10
vs
Yeni Amasyaspor
5/10
ATT
5/10
DEF
Scheduled· Wed 7 Oct · 11:30
Best Pick
BTTS
66%
Correct Score
Top
1-1
9.5%
10.58
Top
2-1
9%
11.13
1-2
7.2%
13.92
2-2
6.8%
14.65
1-0
6.2%
16.06
2-0
5.9%
16.90
3-1
5.7%
17.56
0-1
5%
20.10
147%
2.14TOP
X22%
4.51
231%
3.22
1X69%
X253%
1278%
Probable XI4-4-2
Arslan
Urgenc
Karaoglu
Bora
Aşkar
Çağdaş
Polat
Badak
Yalçın
Biyik
Yüceer
Impact Player Hot Head
Lineups not yet announced — full squad analysis below
Yıldırım Belediyesispor5 players
45.0/ 99Average
Top Rated
1B. BadakMID46
2Ulaş Oktay YıldızMID46
3Yusuf AkyelMID46
Yeni Amasyaspor1 players
45.0/ 99Average
Top Rated
1Yunus Emre KobyaFWD45
Yıldırım Belediyesispor22
PlayerOverall RatingImpactAggressionDiscipline
B. Badak46454550
Ulaş Oktay Yıldız46454550
Yusuf Akyel46454550
Semih Görer45454550
Tahsin Özler42442850
Hüseyin Arslan————
Recep Tayip Kaya————
Benjamin Urgenc————
Efe Karaoglu————
H. Bora————
Melih Aşkar————
Mustafa Kocabas————
Arda Çağdaş————
Yeni Amasyaspor43
PlayerOverall RatingImpactAggressionDiscipline
Yunus Emre Kobya45454550
Halilibrahim Efe Kazan————
Orhan Bostan————
Y. Nacar————
Yusuf Aklan————
Ali Erkin————
Ali İhsan Keskin————
Azat Güner————
Doruk Laleci————
Fatih Ergen————
H. Hicin————
H. Şavur————
Kerem Hayta————
Player Rankings
Snipers
Top goal threats
1
Yunus Emre KobyaYeni Amasyaspor
45
2
Tahsin ÖzlerYıldırım Belediyesispor
44
Wall
Top defenders
1
Semih GörerYıldırım Belediyesispor
45
Control
Top playmakers
1
B. BadakYıldırım Belediyesispor
45
2
Ulaş Oktay YıldızYıldırım Belediyesispor
45
3
Yusuf AkyelYıldırım Belediyesispor
45
Bad Boys
Most likely to get booked
1
Semih GörerYıldırım Belediyesispor
50
2
B. BadakYıldırım Belediyesispor
50
3
Ulaş Oktay YıldızYıldırım Belediyesispor
50
4
Yusuf AkyelYıldırım Belediyesispor
50
5
Tahsin ÖzlerYıldırım Belediyesispor
50
Power Rankings
Strongest overall
1
B. BadakYıldırım Belediyesispor
46
2
Ulaş Oktay YıldızYıldırım Belediyesispor
46
3
Yusuf AkyelYıldırım Belediyesispor
46
4
Semih GörerYıldırım Belediyesispor
45
5
Yunus Emre KobyaYeni Amasyaspor
45

Frequently Asked Questions

Our Poisson model calculates the probability of every possible scoreline for Yıldırım Belediyesispor vs Yeni Amasyaspor 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 Yıldırım Belediyesispor vs Yeni Amasyaspor 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 Yıldırım Belediyesispor 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 Yıldırım Belediyesispor vs Yeni Amasyaspor 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 Yıldırım Belediyesispor 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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