Paris FC 2:1 Paris Saint-Germain: xG & match report · Ligue 1

Sunday, 17/05/2026 at 21:00

Full time

Match report · Ligue 1

Paris FC Home 2.20 xG · 17 shots

Paris Saint-Germain Away 0.61 xG · 9 shots

21 The scoreline reflected the chances

Goals

50' Bradley Barcola Paris Saint-Germain · 0.28 xG chance 0–1
76' Alimami Gory Paris FC · 0.40 xG chance 1–1
90' Alimami Gory Paris FC · 0.85 xG chance 2–1

The shots behind it

Paris FC Paris Saint-Germain

Shots: 17; 9
On target: 9; 2
Inside the box: 15; 6
xG per shot: 0.12; 0.07
Open play xG: 1.33; 0.57
Set-piece xG: 0.76; 0.05
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: 2.13 for Paris FC and 0.62 for Paris Saint-Germain.

Shot map

Both teams shown attacking the same goal for comparison.

All shots

26 shots · 2.71 xG

Hover, focus or tap a shot to read it.

Paris FC
Paris Saint-Germain
Filled = goal
Dot area = xG (the smallest chances drawn at a minimum size)

Recent form

Last 6 · xG per match

Paris FC

1.59 xG created 1.46 xGA

D 1.04 created, 1.18 conceded against Lorient
W 2.61 created, 2.31 conceded against AS Monaco
W 1.74 created, 1.01 conceded against Metz
L 1.06 created, 1.71 conceded against Lille
W 1.86 created, 0.79 conceded against Stade Brestois
L 1.20 created, 1.77 conceded against Stade Rennais

Paris Saint-Germain

2.20 xG created 1.04 xGA

L 3.12 created, 0.62 conceded against Olympique Lyonnais
W 2.17 created, 0.89 conceded against Nantes
W 2.78 created, 0.70 conceded against Angers
D 2.42 created, 0.96 conceded against Lorient
W 1.49 created, 0.17 conceded against Stade Brestois
W 1.22 created, 2.87 conceded against RC Lens

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

Head to head

Paris FC: 0 won · 0 drawn · 1 lost

Paris Saint-Germain 2:1 Paris FC 04/01/2026 xG 1.71 – 1.01

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.