AS Monaco 3:1 Nantes: xG & match report · Ligue 1

Friday, 13/02/2026 at 21:05

Full time

Match report · Ligue 1

AS Monaco Home 1.53 xG · 12 shots

Nantes Away 0.93 xG · 13 shots

31 The scoreline reflected the chances

Goals

25' Simon Adingra AS Monaco · 0.37 xG chance 1–0
28' Simon Adingra AS Monaco · 0.11 xG chance 2–0
30' Denis Zakaria AS Monaco · 0.18 xG chance 3–0
45' Fabien Centonze Nantes · 0.27 xG chance 3–1

The shots behind it

AS Monaco Nantes

Shots: 12; 13
On target: 6; 2
Inside the box: 10; 8
xG per shot: 0.14; 0.07
Open play xG: 1.30; 0.68
Set-piece xG: 0.32; 0.23
Penalties: —; —

Shot-level xG may differ from the published match total

The provider publishes the match total separately from its shot-by-shot values. Those values are rounded to two decimals and, leaving out penalties and own goals, add up to its non-penalty xG: 1.64 for AS Monaco and 0.92 for Nantes.

Shot map

Both teams shown attacking the same goal for comparison.

All shots

25 shots · 2.53 xG

Hover, focus or tap a shot to read it.

AS Monaco
Nantes
Filled = goal
Dot area = xG (the smallest chances drawn at a minimum size)

Recent form

Last 6 · xG per match

AS Monaco

1.22 xG created 0.94 xGA

L 2.21 created, 1.79 conceded against Olympique de Marseille
L 0.69 created, 1.40 conceded against Olympique Lyonnais
L 1.25 created, 1.38 conceded against Lorient
D 0.43 created, 0.21 conceded against Le Havre
W 2.12 created, 0.38 conceded against Stade Rennais
D 0.61 created, 0.50 conceded against Nice

Nantes

1.29 xG created 1.12 xGA

L 0.35 created, 2.39 conceded against Angers
W 3.63 created, 0.75 conceded against Olympique de Marseille
L 0.36 created, 0.97 conceded against Paris FC
L 1.59 created, 0.87 conceded against Nice
L 1.05 created, 0.55 conceded against Lorient
L 0.73 created, 1.21 conceded against Olympique Lyonnais

xG created xG conceded (xGA) W / D / L: the match result

Head to head

AS Monaco: 1 won · 0 drawn · 0 lost

Nantes 3:5 AS Monaco 29/10/2025 xG 1.62 – 4.31

Model details

Show

The model never priced this match before kick-off, so there is no projection to read the result against.

Limitations

The model reads expected goals and nothing else. It does not know the lineups, who is injured or suspended, what either side has to play for, the weather, or how congested the schedule around this match is.