· Friendly International
United States
ATT
7/10
DEF
2/10
vs
Canada
5/10
ATT
6/10
DEF
Planlandı· Wed 7 Oct · 00:00
En iyi tahmin
Üst 2.5
57%
Doğru skor
Mükemmel
1-1
10.7%
9.38
Mükemmel
2-1
9.9%
10.15
1-0
9.7%
10.34
2-0
8.9%
11.18
3-1
6.1%
16.46
1-2
5.9%
17.02
0-1
5.8%
17.34
3-0
5.5%
18.14
155%
1.82TOP
X23%
4.40
222%
4.45
1X78%
X245%
1277%
Probable XI4-4-2
Schwake
Freeman
Robinson
Trusty
Carter-Vickers
Mehmeti
Morris
Cremaschi
Aaronson
Zendejas
White
Impact Player Hot Head
Kadrolar henüz açıklanmadı — aşağıda tam kadro analizi
United States48 oyuncu
60.4/ 99Güçlü
En İyiler
1Sebastian BerhalterMID97
2Auston TrustyDEF93
3Tyler AdamsMID91
Canada43 oyuncu
59.5/ 99Güçlü
En İyiler
1Mathieu ChoinièreMID93
2Liam MillarFWD90
3Nathan-Dylan SalibaMID89
United States74
PlayerGenel DereceEtkiAgresyonDisiplin
Sebastian Berhalter97999091
Auston Trusty93956678
Tyler Adams91879889
Julian Hall81924756
Mathis Albert81973950
Malik Tillman 80809758
Haji Wright 80865661
Aidan Morris 74658167
Brooklyn Raines72606972
Cristian Roldán71778547
Tanner Tessmann71536989
Folarin Balogun7199328
Brian Gutiérrez70645872
Canada54
PlayerGenel DereceEtkiAgresyonDisiplin
Mathieu Choinière93999970
Liam Millar90959961
Nathan-Dylan Saliba89879083
Jonathan Osorio 87877472
T. Oluwaseyi86939941
Ismaël Koné81696791
Luc De Fougerolles76656972
Kamal Miller71775261
Promise David 7099951
Alfie Jones67498067
Ali Ahmed67518272
J. Russell-Rowe66773450
Jacob Shaffelburg65549978
Oyuncu sıralamaları
Keskin nişancılar
En büyük gol tehdidi
1
Folarin BalogunUnited States
99
2
Promise David Canada
99
3
Mathis AlbertUnited States
97
4
Liam MillarCanada
95
5
T. OluwaseyiCanada
93
Duvar
En iyi savunmacılar
1
Auston TrustyUnited States
95
2
Chris RichardsUnited States
85
3
Miles RobinsonUnited States
79
4
Kamal MillerCanada
77
5
Joel WatermanCanada
70
Kontrol
En iyi oyun kurucular
1
Sebastian BerhalterUnited States
99
2
Mathieu ChoinièreCanada
99
3
Giovanni Reyna United States
97
4
Tyler AdamsUnited States
87
5
Jonathan Osorio Canada
87
Yaramaz çocuklar
Kart görme olasılığı en yüksek
1
Chris RichardsUnited States
1
2
Giovanni Reyna United States
1
3
Derek CorneliusCanada
1
4
Promise David Canada
1
5
Junior HoilettCanada
3
Güç sıralaması
Genel olarak en güçlüler
1
Sebastian BerhalterUnited States
97
2
Auston TrustyUnited States
93
3
Mathieu ChoinièreCanada
93
4
Tyler AdamsUnited States
91
5
Liam MillarCanada
90

Sıkça Sorulan Sorular

Our Poisson model calculates the probability of every possible scoreline for United States vs Canada 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 United States vs Canada 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 United States 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 United States vs Canada 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 United States 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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