· K-League 1
Daejeon Citizen
ATT
6/10
DEF
5/10
vs
全北现代
4/10
ATT
7/10
DEF
未开始· Fri 9 Oct · 05:00
最佳推荐
小 2.5
53%
精确比分
顶级
1-1
12.2%
8.22
顶级
1-0
11.9%
8.39
2-1
9.3%
10.70
2-0
9.2%
10.92
0-1
7.9%
12.64
0-0
7.8%
12.89
1-2
6.2%
16.13
3-1
4.8%
20.89
149%
2.03TOP
X26%
3.91
225%
3.98
1X75%
X251%
1274%

组合投注

3 选项

Daejeon’s boosted attack and stable back line suggest they control territory and tempo, anchoring the double chance at home. Jeonbuk’s conservative, defense-first shape still leaves spaces on transitions, inviting a response and making both teams to score feel likely, while Daejeon’s sustained pressure points toward a high, stretched scoreline over the goal line.

1Double ChanceDaejeon Citizen FC or Draw
2Match GoalsOver 2.5
3Both Teams to ScoreYes
Probable XI4-4-2
Lee
Kryvotsiuk
Ha
Kim
Oh
Bobsin
Kim
Park
Lee
Oliveira
Ludwigson
Impact Player Hot Head
阵容尚未公布 — 下方为完整球队分析
Daejeon Citizen28 球员
53.3/ 99中等
最佳
1Jae-hee JeongFWD90
2Jun-beom KimMID86
3Kyu-hyun ParkDEF69
全北现代30 球员
53.6/ 99中等
最佳
1Italo VargasFWD84
2DodôMID77
3Bruno MotaFWD72
Daejeon Citizen37
Player综合评分影响力侵略性纪律
Jae-hee Jeong90996161
Jun-beom Kim86994972
Kyu-hyun Park69478787
Diogo Oliveira68599279
Masatoshi Ishida68666464
Yun-sung Kang67437589
Hyeon-sik Lee66528964
Min-kyu Joo64583986
Jong-eun Lim62585067
Anton Kryvotsiuk59605554
Sung-gwon Cho56545256
Jin-su Seo56465378
Jun-seo Lee52529950
全北现代54
Player综合评分影响力侵略性纪律
Italo Vargas84994156
Dodô77699172
Bruno Mota72714579
Ye-Geon Kim69477891
Yeong-jae Lee66992735
Seong-ung Maeng64488666
Gytis Paulauskas63558366
Jin-gyu Kim62993620
Andrea Compagno59765118
Bum-keun Song57589656
Tae-ho Jin57367367
Dong-jun Lee57545361
Oberdan56487054
球员排名
狙击手
最大进球威胁
1
Jae-hee JeongDaejeon Citizen
99
2
Italo Vargas全北现代
99
3
Andrea Compagno全北现代
76
4
Bruno Mota全北现代
71
5
Tiago Orobó全北现代
70
城墙
最佳后卫
1
Min-duk KimDaejeon Citizen
68
2
Wi-je Cho全北现代
64
3
Anton KryvotsiukDaejeon Citizen
60
4
Jong-eun LimDaejeon Citizen
58
5
Ji-su Park全北现代
58
控制
最佳组织者
1
Jun-beom KimDaejeon Citizen
99
2
Jin-gyu Kim全北现代
99
3
Yeong-jae Lee全北现代
99
4
Dodô全北现代
69
5
Sang-yun Kang全北现代
55
坏小子
最可能吃牌
1
Min-duk KimDaejeon Citizen
1
2
Lee Sang-Myung全北现代
1
3
Tae-hwan Kim全北现代
8
4
Moon-hwan KimDaejeon Citizen
13
5
Young-bin Kim全北现代
13
力量排名
综合最强
1
Jae-hee JeongDaejeon Citizen
90
2
Jun-beom KimDaejeon Citizen
86
3
Italo Vargas全北现代
84
4
Dodô全北现代
77
5
Bruno Mota全北现代
72

常见问题

Our Poisson model calculates the probability of every possible scoreline for Daejeon Citizen vs 全北现代 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 Daejeon Citizen vs 全北现代 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 Daejeon Citizen 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 Daejeon Citizen vs 全北现代 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 Daejeon Citizen 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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