AS Monaco 1:3 Olympique Lyonnais: xG & match report · Ligue 1

Saturday, 03/01/2026 at 17:00

Full time

Match report · Ligue 1

AS Monaco Home 0.69 xG · 6 shots

Olympique Lyonnais Away 1.40 xG · 13 shots

13 The scoreline reflected the chances

Goals

38' Pavel Šulc Olympique Lyonnais · 0.75 xG chance 0–1
45' Mamadou Coulibaly AS Monaco · 0.14 xG chance 1–1
57' Pavel Šulc Olympique Lyonnais · 0.07 xG chance 1–2
79' Abner Vinícius Olympique Lyonnais · 0.12 xG chance 1–3

The shots behind it

AS Monaco Olympique Lyonnais

Shots: 6; 13
On target: 2; 9
Inside the box: 2; 7
xG per shot: 0.08; 0.11
Open play xG: 0.19; 0.47
Set-piece xG: 0.29; 0.95
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: 0.47 for AS Monaco and 1.40 for Olympique Lyonnais.

Shot map

Both teams shown attacking the same goal for comparison.

All shots

19 shots · 1.90 xG

Hover, focus or tap a shot to read it.

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

Recent form

Last 6 · xG per match

AS Monaco

1.35 xG created 2.06 xGA

L 0.61 created, 0.85 conceded against Paris FC
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

Olympique Lyonnais

1.30 xG created 1.62 xGA

D 0.20 created, 1.49 conceded against Stade Brestois
L 0.69 created, 1.42 conceded against Paris Saint-Germain
D 1.57 created, 2.07 conceded against Auxerre
W 2.35 created, 0.86 conceded against Nantes
L 0.43 created, 2.57 conceded against Lorient
W 2.56 created, 1.31 conceded against Le Havre

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

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.