Persebaya’s home edge and stronger attack point to a front-foot start: their 1.24 first-half xG dwarfs Persijap’s 0.15, supporting a lead by the break. With 1.75 full-match xG against Persijap’s 0.59 and the visitors’ weak attack, Persebaya should control the match; their scoring pressure makes Over 2.5 a logical fit.
1Match WinnerPersebaya Surabaya
2Match GoalsOver 2.5
3First Half WinnerPersebaya Surabaya
Probable XI4-4-2
Arido
Akbar
Catur
Jefferson
Ari
Maulana
Wicaksono
Ramalho
Rivera
Alex
Suaib
Impact Player Hot Head
Lineups not yet announced — full squad analysis below
Persebaya Surabaya32 players
50.8/ 99Average
Top Rated
1Ahmad Mujtaba Ilham AkbarDEF92
2Francisco RiveraMID72
3AlexFWD72
Persijap Jepara26 players
40.3/ 99Average
Top Rated
1Claudio Beckham de OliveraDEF59
2F. AfriyantoDEF58
3Muhammad ArdiansyahGK54
Persebaya Surabaya35
PlayerOverall RatingImpactAggressionDiscipline
Ahmad Mujtaba Ilham Akbar92999956
Francisco Rivera72992752
Alex72852954
Diogo Ramalho67568259
Arief Catur66477869
Mikael Tata64626656
Randy May63852850
Koko Ari 61579242
Aleandro Maulana61468956
Yusuf Meilana55319953
Ernando Ari5252950
Malik Risaldi51404283
D. Wicaksono50247367
Persijap Jepara40
PlayerOverall RatingImpactAggressionDiscipline
Claudio Beckham de Olivera59595656
F. Afriyanto58713256
Muhammad Ardiansyah5454950
Rahmatzoda Rahmatsho54383984
Frank Rikhard53485756
Sendri Johansah4949950
Tiri4785431
Rakasurya Handika46453950
Felix Marcelino46454550
Bil’asqan Hi Tenang45454550
Rahmat Hidayat44452565
Samuel Ofori43492850
R. Saepul42374756
Player Rankings
Snipers
Top goal threats
1
AlexPersebaya Surabaya
85
2
Ricky PratamaPersebaya Surabaya
45
3
Bil’asqan Hi TenangPersijap Jepara
45
4
Alfan SuaibPersebaya Surabaya
43
5
Dicky KurniawanPersebaya Surabaya
40
Wall
Top defenders
1
Ahmad Mujtaba Ilham AkbarPersebaya Surabaya
99
2
Randy MayPersebaya Surabaya
85
3
TiriPersijap Jepara
85
4
F. AfriyantoPersijap Jepara
71
5
Mikael TataPersebaya Surabaya
62
Control
Top playmakers
1
Francisco RiveraPersebaya Surabaya
99
2
Diogo RamalhoPersebaya Surabaya
56
3
Aleandro MaulanaPersebaya Surabaya
46
4
Felix MarcelinoPersijap Jepara
45
5
GledsonPersebaya Surabaya
40
Bad Boys
Most likely to get booked
1
Buyung Ismu LessyPersijap Jepara
1
Aggression 22
2
TiriPersijap Jepara
1
Aggression 43
3
Toni FirmansyahPersebaya Surabaya
23
Aggression 76
4
S. PutraPersebaya Surabaya
25
Aggression 67
5
Adzikry FadlillahPersijap Jepara
25
Aggression 29
Power Rankings
Strongest overall
1
Ahmad Mujtaba Ilham AkbarPersebaya Surabaya
92
2
Francisco RiveraPersebaya Surabaya
72
3
AlexPersebaya Surabaya
72
4
Diogo RamalhoPersebaya Surabaya
67
5
Arief CaturPersebaya Surabaya
66
Frequently Asked Questions
Our Poisson model calculates the probability of every possible scoreline for Persebaya Surabaya vs Persijap Jepara 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 Persebaya Surabaya vs Persijap Jepara 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 Persebaya Surabaya 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 Persebaya Surabaya vs Persijap Jepara 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 Persebaya Surabaya 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.