· Friendly International
Russia
ATT
7/10
DEF
8/10
vs
Nigeria
6/10
ATT
5/10
DEF
Scheduled· Tue 6 Oct · 16:00
Best Pick
Home Win
62%
Correct Score
Top
1-0
11.3%
8.81
Top
2-0
11%
9.06
1-1
10.2%
9.83
2-1
9.9%
10.10
3-0
7.2%
13.96
3-1
6.4%
15.57
0-0
5.8%
17.15
0-1
5.2%
19.12
162%
1.62TOP
X21%
4.67
217%
5.98
1X83%
X238%
1279%
Probable XI4-4-2
Maksimenko
Soldatenkov
Silyanov
Langovich
Adamov
Chernikov
Golovin
Batrakov
Miranchuk
Ibragimov
Sobolev
Impact Player Hot Head
Lineups not yet announced — full squad analysis below
Russia44 players
61.2/ 99Strong
Top Rated
1Ivan OblyakovMID96
2Ivan SergeevFWD95
3Lechi SadulaevFWD92
Nigeria40 players
43.2/ 99Average
Top Rated
1Calvin BasseyDEF65
2Raphael OnyedikaMID50
3Alex IwobiMID49
Russia69
PlayerOverall RatingImpactAggressionDiscipline
Ivan Oblyakov96998183
Ivan Sergeev95967489
Lechi Sadulaev92929083
Viktor Melekhin86797189
Matvey Kislyak83995361
Kirill Danilov80808356
K. Tyukavin79874367
Maksim Osipenko76706272
Alexander Silyanov75984056
Mingiyan Beveev75669959
Ilya Vakhania74569991
Evgeniy Morozov73567983
Nail Umyarov 70994635
Nigeria99
PlayerOverall RatingImpactAggressionDiscipline
Calvin Bassey65496372
Raphael Onyedika50474656
Alex Iwobi49434261
Fisayo Dele-Bashiru49464656
Akor Adams49464361
Maduka Okoye48483950
Christian Akpan48474850
Adebayo Adeleye46454550
Amas Obasogie46454550
Arthur Okonkwo46454550
Francis Uzoho46454550
S. Nwabali46454550
Alhassan Yusuf46454550
Player Rankings
Snipers
Top goal threats
1
Ivan SergeevRussia
96
2
Lechi SadulaevRussia
92
3
K. TyukavinRussia
87
4
Maksim GlushenkovRussia
71
5
Aleksandr SobolevRussia
63
Wall
Top defenders
1
Alexander SilyanovRussia
98
2
Kirill DanilovRussia
80
3
Viktor MelekhinRussia
79
4
Maksim OsipenkoRussia
70
5
Mingiyan BeveevRussia
66
Control
Top playmakers
1
Ivan OblyakovRussia
99
2
Matvey KislyakRussia
99
3
Nail Umyarov Russia
99
4
Aleksey BatrakovRussia
95
5
Danil PrutsevRussia
75
Bad Boys
Most likely to get booked
1
Aleksey BatrakovRussia
1
2
Maksim GlushenkovRussia
1
3
Zelimkhan BakaevRussia
1
4
Paul OnuachuNigeria
1
5
Artem KarpukasRussia
13
Power Rankings
Strongest overall
1
Ivan OblyakovRussia
96
2
Ivan SergeevRussia
95
3
Lechi SadulaevRussia
92
4
Viktor MelekhinRussia
86
5
Matvey KislyakRussia
83

Frequently Asked Questions

Our Poisson model calculates the probability of every possible scoreline for Russia vs Nigeria 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 Russia vs Nigeria 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 Russia 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 Russia vs Nigeria 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 Russia 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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