· Primera B
Envigado
ATT
5/10
DEF
8/10
2:0
Boca Juniors de Cali
6/10
ATT
3/10
DEF
全场
最佳推荐
小 2.5
64%
精确比分93′
顶级
1-0
16.6%
6.00
顶级
1-1
12.1%
8.00
0-0
11.8%
8.00
2-0
11.7%
6.50
0-1
8.6%
15.00
2-1
8.5%
10.00
3-0
5.5%
9.50
1-2
4.4%
23.00
153%
1.88TOP
X27%
3.65
219%
5.14
1X80%
X246%
1272%
xG — Expected Goals
Envigado
Envigado exp
Boca Juniors de Cali
Boca Juniors de Cali exp
goal
每15分钟
0–15′
15–30′
30–45′
45–60′
60–75′
75–90′
Envigado
Boca Juniors de Cali
Probable XI4-4-2
88
Tovar
Al-Haj
30
Agrón
Caviedes
36
Murillo
17
Vargas
30
Tenorio
29
Zapata
21
López
9
Rodríguez
80
Torres
Impact Player Hot Head
阵容尚未公布 — 下方为完整球队分析
Envigado36 球员
54.2/ 99中等
最佳
1Neymar UribeDEF80
2Jhojan Camilo Nieva RoldánMID74
3Edison LópezMID66
Boca Juniors de Cali27 球员
51.0/ 99中等
最佳
1Brayan FernandezFWD75
2Andrés CuadrosMID74
3John Wilmar Arango MonsalveMID67
Envigado58
Player综合评分影响力侵略性纪律
4
Neymar Uribe80758760
70
Jhojan Camilo Nieva Roldán74884659
21
Edison López66585673
17
Gabriel Arrieta66637359
27
J. Quejada65507364
15
Gendry Cuervo63486370
13
Tomás Soto63704756
28
Jhon Gamboa62762664
77
Dayron Andrés Valencia Mosquera62588353
19
Stiwart Acuña62654954
29
Daniel Zapata60459952
20
Juan José Cataño59644158
18
William Hurtado59693557
Boca Juniors de Cali39
Player综合评分影响力侵略性纪律
Brayan Fernandez75739960
Andrés Cuadros74628374
18
John Wilmar Arango Monsalve6798952
34
Deyman Cortes65589962
26
Harold Yecid Ortiz Quinayas61566358
8
Jean Vallejo60536757
17
José Andrade57663258
7
Juan Camilo Cuero Torres56594252
23
Marlon Lucumi56575551
20
Juan Vásquez55316769
12
Euler Orlando Obando Caicedo53539952
35
Juan Manuel Viveros Mrinez53554951
11
Didier Fabián Henao Beitar49345763
球员排名
狙击手
最大进球威胁
1
Brayan FernandezBoca Juniors de Cali
73
2
Stiwart AcuñaEnvigado
65
3
Gabriel ArrietaEnvigado
63
4
J. HernándezEnvigado
61
5
Juan Camilo Cuero TorresBoca Juniors de Cali
59
城墙
最佳后卫
1
Jhon GamboaEnvigado
76
2
Neymar UribeEnvigado
75
3
Kevin HurtadoBoca Juniors de Cali
58
4
Harold Yecid Ortiz QuinayasBoca Juniors de Cali
56
5
Juan Manuel Viveros MrinezBoca Juniors de Cali
55
控制
最佳组织者
1
John Wilmar Arango MonsalveBoca Juniors de Cali
98
2
Jhojan Camilo Nieva RoldánEnvigado
88
3
Tomás SotoEnvigado
70
4
William HurtadoEnvigado
69
5
José AndradeBoca Juniors de Cali
66
坏小子
最可能吃牌
1
Nilzo RamírezEnvigado
1
2
Andrés TovarEnvigado
50
3
Jaime MoraEnvigado
50
4
Juan MontoyaEnvigado
50
5
M. MarulandaEnvigado
50
力量排名
综合最强
1
Neymar UribeEnvigado
80
2
Brayan FernandezBoca Juniors de Cali
75
3
Jhojan Camilo Nieva RoldánEnvigado
74
4
Andrés CuadrosBoca Juniors de Cali
74
5
John Wilmar Arango MonsalveBoca Juniors de Cali
67

常见问题

Our Poisson model calculates the probability of every possible scoreline for Envigado vs Boca Juniors de Cali 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 Envigado vs Boca Juniors de Cali 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 Envigado 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 Envigado vs Boca Juniors de Cali 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 Envigado 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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