· Premier League
Arsenal FC
ATT
7/10
DEF
7/10
vs
Everton
4/10
ATT
7/10
DEF
Planlandı· Sat 24 Oct · 14:00

AI Maç Analizi

Arsenal’s solid attacking edge and expected territorial pressure should keep Everton pinned back, while repeated waves and set-piece opportunities create mounting danger. Once the visitors are forced to open up, the contest appears likely to produce the goals needed to clear the line.

Match GoalsOver 2.5
En iyi tahmin
Ev sahibi kazanır
60%
Doğru skor
Mükemmel
1-0
10.9%
8.00
Mükemmel
2-0
10.4%
7.50
1-1
10.4%
8.50
2-1
9.9%
9.50
3-0
6.6%
11.00
3-1
6.3%
13.00
0-0
5.7%
12.00
0-1
5.5%
21.00
160%
1.42TOP
X22%
4.50
218%
8.00
1X82%
X240%
1278%

Kombine

3 seçim

Arsenal should pin Everton back and keep the corner count climbing, with their attack carrying enough punch to break through. The Toffees can still threaten on the break, so both teams to score looks live; once the game opens up, the chances are there for over 2.5 goals and over 8.5 corners.

1Both Teams to ScoreYes
2Match GoalsOver 2.5
3Corners Over/UnderOver 8.5
Confirmed XI5-3-2
1
Raya
4
White
15
Konsa
6
Magalhães
33
Calafiori
49
Lewis-Skelly
41
Rice
10
Eze
8
Ødegaard
20
Madueke
29
Havertz
Impact Player Hot Head
Arsenal FC25 oyuncu
53.4/ 99Orta
En İyiler
1Gabriel Jesus  FWD70
2Declan RiceMID69
3Bruno GuimarãesMID68
Everton24 oyuncu
50.1/ 99Orta
En İyiler
1Michael KeaneDEF71
2Nathan Patterson DEF69
3Tyler DiblingFWD68
Oyuncu sıralamaları
Keskin nişancılar
En büyük gol tehdidi
1
Gabriel Jesus  Arsenal FC
99
2
Tyler DiblingEverton
78
3
Tyrique GeorgeEverton
69
4
Bukayo Saka Arsenal FC
62
5
BetoEverton
62
Duvar
En iyi savunmacılar
1
Michael KeaneEverton
74
2
James TarkowskiEverton
69
3
Jarrad Branthwaite Everton
64
4
Gabriel MagalhãesArsenal FC
62
5
Nathan Patterson Everton
60
Kontrol
En iyi oyun kurucular
1
Declan RiceArsenal FC
82
2
Bruno GuimarãesArsenal FC
72
3
Martin Ødegaard Arsenal FC
69
4
James GarnerEverton
67
5
Christian Nørgaard Everton
65
Yaramaz çocuklar
Kart görme olasılığı en yüksek
1
Gabriel Jesus  Arsenal FC
1
2
Gabriel MartinelliArsenal FC
1
3
Carlos AlcarazEverton
1
4
James GarnerEverton
1
5
Brennan JohnsonEverton
16
Güç sıralaması
Genel olarak en güçlüler
1
Michael KeaneEverton
71
2
Gabriel Jesus  Arsenal FC
70
3
Declan RiceArsenal FC
69
4
Nathan Patterson Everton
69
5
Bruno GuimarãesArsenal FC
68

Sıkça Sorulan Sorular

Our Poisson model calculates the probability of every possible scoreline for Arsenal FC vs Everton 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 Arsenal FC vs Everton 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 Arsenal 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 Arsenal FC vs Everton 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 Arsenal 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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