· Coupe de France
Cheminots Paray
ATT
5/10
DEF
5/10
0:3
Villefranche-Beaujolais
5/10
ATT
5/10
DEF
Full-time
Best Pick
BTTS
63%
Correct Score91′
Top
1-1
10.4%
9.63
Top
2-1
9.1%
10.99
1-2
7.5%
13.42
1-0
7.2%
13.81
2-2
6.5%
15.32
2-0
6.3%
15.77
0-1
5.9%
16.86
3-1
5.3%
18.82
145%
2.21TOP
X23%
4.31
232%
3.16
1X68%
X255%
1277%
xG — Expected Goals
Cheminots Paray
Cheminots Paray exp
Villefranche-Beaujolais
Villefranche-Beaujolais exp
goal
Probable XI4-4-2
Loudot
Bernard
Voisin
Longin
Gagneaud
Deschaintre
Bouchot
Bouillet
Muneret
Moinot
Benameur
Impact Player Hot Head
Lineups not yet announced — full squad analysis below
Cheminots Paray13 players
No squad metrics available
Bastien LoudotGK
Jeremy CharvonGK
Anthony BernardDEF
Baptiste VoisinDEF
Etienne LonginDEF
Jean GagneaudDEF
Sylvain MoinotDEF
Zakaria BenameurDEF
Benoit DeschaintreMID
Franck BouchotMID
Mathieu BouilletMID
Pierre Yves MuneretMID
Sébastien ScirpoliMID
Villefranche-Beaujolais4 players
48.8/ 99Average
Top Rated
1Nassim SabihiFWD52
2Loïc EtogaMID49
3Fred Ondoa OnambeleDEF48
Cheminots Paray13
PlayerOverall RatingImpactAggressionDiscipline
Bastien Loudot————
Jeremy Charvon————
Anthony Bernard————
Baptiste Voisin————
Etienne Longin————
Jean Gagneaud————
Sylvain Moinot————
Zakaria Benameur————
Benoit Deschaintre————
Franck Bouchot————
Mathieu Bouillet————
Pierre Yves Muneret————
Sébastien Scirpoli————
Villefranche-Beaujolais29
PlayerOverall RatingImpactAggressionDiscipline
26
Nassim Sabihi52525152
29
Loïc Etoga49504550
12
Fred Ondoa Onambele48494550
22
Paolo Limon46454550
1
Sullivan Péan————
16
Titouan Wilzius————
5
Boris Moltenis————
23
Dembo Gassama————
Erwan Norde————
2
Jason Ngouabi Lougagui————
19
Kemryk Nagera————
4
Marvin Tshibuabua————
8
Maxime Etuin————
Player Rankings
Snipers
Top goal threats
1
Nassim SabihiVillefranche-Beaujolais
52
Wall
Top defenders
1
Fred Ondoa OnambeleVillefranche-Beaujolais
49
Control
Top playmakers
1
Loïc EtogaVillefranche-Beaujolais
50
2
Paolo LimonVillefranche-Beaujolais
45
Bad Boys
Most likely to get booked
1
Fred Ondoa OnambeleVillefranche-Beaujolais
50
2
Loïc EtogaVillefranche-Beaujolais
50
3
Paolo LimonVillefranche-Beaujolais
50
4
Nassim SabihiVillefranche-Beaujolais
52
Power Rankings
Strongest overall
1
Nassim SabihiVillefranche-Beaujolais
52
2
Loïc EtogaVillefranche-Beaujolais
49
3
Fred Ondoa OnambeleVillefranche-Beaujolais
48
4
Paolo LimonVillefranche-Beaujolais
46

Frequently Asked Questions

Our Poisson model calculates the probability of every possible scoreline for Cheminots Paray vs Villefranche-Beaujolais 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 Cheminots Paray vs Villefranche-Beaujolais 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 Cheminots Paray 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 Cheminots Paray vs Villefranche-Beaujolais 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 Cheminots Paray 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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