· Liga 1
Persik Kediri
ATT
5/10
DEF
4/10
vs
Madura United
5/10
ATT
5/10
DEF
Запланирован· Fri 9 Oct · 08:30
Лучший выбор
ОБЕ ЗАБЬЮТ
54%
Точный счёт
Отличная
1-1
11.8%
8.46
Отличная
1-0
10.3%
9.73
2-1
9.4%
10.65
2-0
8.2%
12.25
0-1
7.4%
13.45
1-2
6.8%
14.72
0-0
6.5%
15.47
2-2
5.4%
18.53
148%
2.10TOP
X25%
4.01
228%
3.63
1X73%
X253%
1276%
Probable XI4-4-2
Ramadhani
Salman
Pamungkas
Park
Kiko
Jayanto
Zidane
Otto
Barbosa
Alrizky
Asraf
Impact Player Hot Head
Составы ещё не объявлены — полный анализ игроков ниже
Persik Kediri20 игроков
46.7/ 99Средний
Лучшие
1KikoDEF73
2Althaf AlrizkyFWD63
3José EnriqueFWD62
Madura United24 игроков
51.8/ 99Средний
Лучшие
1Iran JuniorMID95
2Jorge Ambrosio MendonçaDEF82
3Aji KusumaFWD80
Persik Kediri24
PlayerОбщий РейтингВлияниеАгрессияДисциплина
Kiko73737455
Althaf Alrizky63575872
José Enrique62506481
Jun-Heong Park57425472
Andhika Ramadhani5455950
Bayu Otto54414078
Yoga Aditama53374083
Ernesto Gómez51534747
Dimas Pamungkas45454550
Eduardo Barbosa44352378
Dzaky Asraf43384856
Fransiskus Alesandro Nimo Olepue43305072
Daffa Salman42486230
Madura United26
PlayerОбщий РейтингВлияниеАгрессияДисциплина
Iran Junior95956291
Jorge Ambrosio Mendonça82997546
Aji Kusuma80749991
Taufany Muslihuddin75626883
Giovani Numberi73606475
Rifqi Ray62419972
Ahmad Rusadi61534476
Feby Ramzy55427656
Lulinha55607935
Mochammad Diky53539252
Juan Santacruz53633450
Dede Sapari51444861
Dimitar Mitkov51464867
Рейтинги игроков
Снайперы
Главные голевые угрозы
1
Aji KusumaMadura United
74
2
Gali FreitasMadura United
63
3
LulinhaMadura United
60
4
Althaf AlrizkyPersik Kediri
57
5
Ernesto GómezPersik Kediri
53
Стена
Лучшие защитники
1
Jorge Ambrosio MendonçaMadura United
99
2
KikoPersik Kediri
73
3
Pedro MonteiroMadura United
69
4
Giovani NumberiMadura United
60
5
Ahmad RusadiMadura United
53
Контроль
Лучшие плеймейкеры
1
Iran JuniorMadura United
95
2
Juan SantacruzMadura United
63
3
Taufany MuslihuddinMadura United
62
4
Jon ToralPersik Kediri
53
5
Zanadin FarizPersik Kediri
53
Хулиганы
Склонны к карточкам
1
Zanadin FarizPersik Kediri
1
2
Gali FreitasMadura United
1
3
Pedro MonteiroMadura United
4
4
Jon ToralPersik Kediri
15
5
Paulo SitanggangMadura United
15
Рейтинг силы
Сильнейшие в целом
1
Iran JuniorMadura United
95
2
Jorge Ambrosio MendonçaMadura United
82
3
Aji KusumaMadura United
80
4
Taufany MuslihuddinMadura United
75
5
KikoPersik Kediri
73

Часто задаваемые вопросы

Our Poisson model calculates the probability of every possible scoreline for Persik Kediri vs Madura United 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 Persik Kediri vs Madura United 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 Persik Kediri 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 Persik Kediri vs Madura United 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 Persik Kediri 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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