· Liga 1
Arema FC
ATT
6/10
DEF
5/10
2:2
Bhayangkara Presisi Indonesia FC
5/10
ATT
4/10
DEF
Full-time
Best Pick
BTTS
55%
Correct Score52′
Top
1-1
11.2%
7.00
Top
1-0
10.1%
9.00
2-1
9.7%
10.00
2-0
8.7%
11.00
0-1
6.5%
12.00
1-2
6.2%
13.00
0-0
5.9%
11.00
3-1
5.6%
17.00
152%
1.93TOP
X24%
4.21
224%
4.10
1X76%
X248%
1276%
xG — Expected Goals
Arema FC
Arema FC exp
Bhayangkara Presisi Indonesia FC
Bhayangkara Presisi Indonesia FC exp
goal
per 15 min
0–15′
15–30′
30–45′
45–60′
60–75′
75–90′
Arema FC
Bhayangkara Presisi Indonesia FC
Confirmed XI4-3-3
30
Satryo
19
Syarif
3
Landis
5
Maia
87
Farisi
34
Otusanya
66
Yama
25
Blade
7
Silva
98
MV
95
Careca
Impact Player Hot Head
Arema FC23 players
50.6/ 99Average
Top Rated
1Teuku Razzaa Fachrezi AzizFWD83
2Robi DarwisMID73
3Hansamu YamaDEF65
Bhayangkara Presisi Indonesia FC25 players
48.2/ 99Average
Top Rated
1Nehar SadikiDEF75
2Moussa SidibéFWD71
3Frengky Deaner MissaDEF68
Player Rankings
Snipers
Top goal threats
1
Teuku Razzaa Fachrezi AzizArema FC
99
2
Moussa SidibéBhayangkara Presisi Indonesia FC
73
3
Ryan KurniaBhayangkara Presisi Indonesia FC
66
4
AllanoBhayangkara Presisi Indonesia FC
56
5
Sani Rizki FauziBhayangkara Presisi Indonesia FC
55
Wall
Top defenders
1
Hansamu YamaArema FC
70
2
Nehar SadikiBhayangkara Presisi Indonesia FC
65
3
Diego Luiz LandisArema FC
64
4
Walisson MaiaArema FC
57
5
Frengky Deaner MissaBhayangkara Presisi Indonesia FC
51
Control
Top playmakers
1
Robi DarwisArema FC
99
2
Gustavo FrançaArema FC
74
3
Hanif SjahbandiArema FC
73
4
Ryo Matsumura Bhayangkara Presisi Indonesia FC
68
5
Arkhan FikriArema FC
56
Bad Boys
Most likely to get booked
1
Salim Akbar TuhareaArema FC
1
2
AllanoBhayangkara Presisi Indonesia FC
1
3
Teuku IchsanBhayangkara Presisi Indonesia FC
7
4
Andhika WijayaBhayangkara Presisi Indonesia FC
14
5
Ryan KurniaBhayangkara Presisi Indonesia FC
25
Power Rankings
Strongest overall
1
Teuku Razzaa Fachrezi AzizArema FC
83
2
Nehar SadikiBhayangkara Presisi Indonesia FC
75
3
Robi DarwisArema FC
73
4
Moussa SidibéBhayangkara Presisi Indonesia FC
71
5
Frengky Deaner MissaBhayangkara Presisi Indonesia FC
68

Frequently Asked Questions

Our Poisson model calculates the probability of every possible scoreline for Arema FC vs Bhayangkara Presisi Indonesia FC 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 Arema FC vs Bhayangkara Presisi Indonesia FC 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 Arema FC 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 Arema FC vs Bhayangkara Presisi Indonesia FC 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 Arema FC 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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