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

Friday, 16/01/2026 at 19:00

Full time

Match report · Ligue 1

AS Monaco Home 1.25 xG · 14 shots

Lorient Away 1.38 xG · 14 shots

13 The chances were evenly matched

Goals

68' Ahmadou Bamba Dieng Lorient · 0.55 xG chance 0–1
76' Ansu Fati AS Monaco · 0.38 xG chance 1–1
85' Jean Victor Makengo Lorient · 0.20 xG chance 1–2
87' Karim Dermane Lorient · 0.09 xG chance 1–3

The shots behind it

AS Monaco Lorient

Shots: 14; 14
On target: 7; 4
Inside the box: 9; 8
xG per shot: 0.09; 0.10
Open play xG: 1.20; 1.30
Set-piece xG: 0.11; 0.09
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: 1.32 for AS Monaco and 1.38 for Lorient.

Shot map

Both teams shown attacking the same goal for comparison.

All shots

28 shots · 2.70 xG

Hover, focus or tap a shot to read it.

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

Recent form

Last 6 · xG per match

AS Monaco

1.36 xG created 2.15 xGA

L 2.83 created, 3.16 conceded against RC Lens
L 1.33 created, 3.69 conceded against Stade Rennais
W 0.52 created, 1.33 conceded against Paris Saint-Germain
L 0.60 created, 1.53 conceded against Stade Brestois
L 2.21 created, 1.79 conceded against Olympique de Marseille
L 0.69 created, 1.40 conceded against Olympique Lyonnais

Lorient

1.43 xG created 0.75 xGA

D 1.36 created, 1.32 conceded against Toulouse
D 0.32 created, 0.84 conceded against Nantes
W 2.38 created, 0.82 conceded against Nice
W 2.57 created, 0.43 conceded against Olympique Lyonnais
D 0.53 created, 0.69 conceded against RC Strasbourg
D 1.44 created, 0.41 conceded against Metz

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

Head to head

AS Monaco: 0 won · 0 drawn · 1 lost

Lorient 3:1 AS Monaco 27/09/2025 xG 1.98 – 0.92

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.