· Coupe de France
Bethune
ATT
5/10
DEF
4/10
3:3
Nancy
4/10
ATT
3/10
DEF
Full-time
Best Pick
Over 2.5
63%
Correct Score120′
Top
1-1
9.9%
12.00
Top
2-1
9.6%
34.00
1-0
7.6%
34.00
2-0
7.3%
51.00
1-2
6.5%
10.00
2-2
6.3%
21.00
3-1
6.1%
67.00
0-1
5.2%
11.00
152%
1.93TOP
X22%
4.50
226%
3.84
1X74%
X248%
1278%
xG — Expected Goals
Bethune
Bethune exp
Nancy
Nancy exp
goal
Probable XI4-4-2
Lorandi
Debuire
Thumerel
Mahieu
Faouzi
Fadani
Herault
Loconte
Evrard
Janeszko
Galliano
Impact Player Hot Head
Lineups not yet announced — full squad analysis below
Bethune12 players
No squad metrics available
Romain LorandiGK
Benoit DebuireDEF
Gauthier ThumerelDEF
Hugo MahieuDEF
Sofiane FaouziDEF
Tom VerbekeDEF
Ayoub El FadaniMID
Enzo HeraultMID
Enzo LoconteMID
Thomas EvrardMID
Anthony JaneszkoFWD
M. Galliano GallianoFWD
Nancy13 players
48.8/ 99Average
Top Rated
1Yannis NahounouDEF55
2Geoffrey LembetGK53
3Elydjah MendyDEF51
Bethune12
PlayerOverall RatingImpactAggressionDiscipline
Romain Lorandi————
Benoit Debuire————
Gauthier Thumerel————
Hugo Mahieu————
Sofiane Faouzi————
Tom Verbeke————
Ayoub El Fadani————
Enzo Herault————
Enzo Loconte————
Thomas Evrard————
Anthony Janeszko————
M. Galliano Galliano————
Nancy32
PlayerOverall RatingImpactAggressionDiscipline
77
Yannis Nahounou55556247
30
Geoffrey Lembet53537450
21
Elydjah Mendy51524852
25
Jérémy Gélin51534552
44
Enzo Tacafred50485251
11
Sidi Ibrahim Cissé50495252
14
Nicolas Saint-Ruf  49544746
10
Adrian Dabasse49485051
4
Nehemiah Fernandez48494352
29
Noam Obougoujacquet47455750
26
Zakaria Ztouti45454550
70
Nordine Kandil 44424750
18
Hugo Barbier43454346
Player Rankings
Snipers
Top goal threats
1
Sidi Ibrahim CisséNancy
49
2
Adrian DabasseNancy
48
3
Noam ObougoujacquetNancy
45
4
Zakaria ZtoutiNancy
45
5
Nordine Kandil Nancy
42
Wall
Top defenders
1
Yannis NahounouNancy
55
2
Nicolas Saint-Ruf  Nancy
54
3
Elydjah MendyNancy
52
4
Nehemiah FernandezNancy
49
5
Enzo TacafredNancy
48
Control
Top playmakers
1
Jérémy GélinNancy
53
2
Hugo BarbierNancy
45
Bad Boys
Most likely to get booked
1
Nicolas Saint-Ruf  Nancy
46
2
Hugo BarbierNancy
46
3
Yannis NahounouNancy
47
4
Geoffrey LembetNancy
50
5
Noam ObougoujacquetNancy
50
Power Rankings
Strongest overall
1
Yannis NahounouNancy
55
2
Geoffrey LembetNancy
53
3
Elydjah MendyNancy
51
4
Jérémy GélinNancy
51
5
Enzo TacafredNancy
50

Frequently Asked Questions

Our Poisson model calculates the probability of every possible scoreline for Bethune vs Nancy 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 Bethune vs Nancy 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 Bethune 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 Bethune vs Nancy 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 Bethune 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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