· First Professional League
切诺摩尔
ATT
4/10
DEF
4/10
vs
维拉特萨
5/10
ATT
4/10
DEF
未开始· Mon 2 Nov · 15:00
最佳推荐
小 2.5
60%
精确比分
顶级
1-0
13.2%
6.00
顶级
1-1
13%
6.50
0-0
10%
8.00
0-1
9.8%
10.00
2-0
8.8%
8.50
2-1
8.6%
9.00
1-2
6.3%
15.00
0-2
4.8%
19.00
145%
1.91TOP
X28%
3.30
228%
4.33
1X73%
X256%
1273%
Probable XI3-5-2
Manasiev
Donchev
Bandaró
Nyagolov
Todorov
Beyhan
Teles
Bounaas
Banev
Kolev
Sidney
Impact Player Hot Head Shooter

Celso Sidney — lives for the goal, and when he smells a chance he rarely hesitates

Georgi Lazarov — gets in behind constantly, so a goal here would surprise nobody

Padilla Jorge — always sniffing around the box — the kind of player who just ends up on the scoresheet

阵容尚未公布 — 下方为完整球队分析
切诺摩尔38 球员
45.9/ 99中等
最佳
1Gustavo FrançaFWD72
2Vlatko DrobarovDEF70
3Rosen StefanovDEF64
维拉特萨29 球员
52.8/ 99中等
最佳
1Milen StoevDEF84
2Kassim HadjiMID83
3José GallegosMID61
切诺摩尔51
Player综合评分影响力侵略性纪律
Gustavo França72745961
Vlatko Drobarov70665173
Rosen Stefanov64558054
Georgi Ventsislavov63754750
N. Lumbu63774550
Nikolay Zlatev60683450
Padilla Jorge55625735
Weslen Junior54596935
Plamen Iliev5253950
Georgi Lazarov51465162
Bandaró50474063
Ventsislav Kerchev49575240
Aleksandar Todorov49342691
维拉特萨36
Player综合评分影响力侵略性纪律
Milen Stoev84866171
Kassim Hadji83755589
José Gallegos61663269
Sainey Sanyang59533384
Martin Smolenski59694151
Kristiyan Malinov57279284
Daniel Genov 57587143
Lazar Boyanov55631678
Martin Dimitrov55555056
Martin Stoychev55344883
Tamimou Ouorou53553167
Radoslav Tsonev53792829
Marin Orlinov52529950
赛前预测· 阵容尚未公布
最佳射手
高影响力前锋
1
Padilla Jorge
切诺摩尔
影响
62
2.93
2
Martin Petkov
维拉特萨
影响
59
4.00
3
Daniel Genov 
维拉特萨
影响
58
5.50
4
Preslav Borukov
维拉特萨
影响
54
3.91
5
F. Gigov
维拉特萨
影响
51
4.36
6
Aleksandar Kolev
切诺摩尔
影响
47
3.12
球员排名
狙击手
最大进球威胁
1
Gustavo França切诺摩尔
74
2
Nikolay Zlatev切诺摩尔
68
3
Padilla Jorge切诺摩尔
62
4
Weslen Junior切诺摩尔
59
5
Martin Petkov维拉特萨
59
城墙
最佳后卫
1
Milen Stoev维拉特萨
86
2
N. Lumbu切诺摩尔
77
3
Georgi Ventsislavov切诺摩尔
75
4
Vlatko Drobarov切诺摩尔
66
5
Lazar Boyanov维拉特萨
63
控制
最佳组织者
1
Radoslav Tsonev维拉特萨
79
2
Kassim Hadji维拉特萨
75
3
Martin Smolenski维拉特萨
69
4
José Gallegos维拉特萨
66
5
Mohamed Achi切诺摩尔
59
坏小子
最可能吃牌
1
Preslav Borukov维拉特萨
1
2
Tsvetomir Panov切诺摩尔
2
3
Yoan Bornosuzov维拉特萨
9
4
Luciano Gastón Squadrone切诺摩尔
13
5
Dani Martín切诺摩尔
16
力量排名
综合最强
1
Milen Stoev维拉特萨
84
2
Kassim Hadji维拉特萨
83
3
Gustavo França切诺摩尔
72
4
Vlatko Drobarov切诺摩尔
70
5
Rosen Stefanov切诺摩尔
64

常见问题

Our Poisson model calculates the probability of every possible scoreline for 切诺摩尔 vs 维拉特萨 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 切诺摩尔 vs 维拉特萨 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 切诺摩尔 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 切诺摩尔 vs 维拉特萨 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 切诺摩尔 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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