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

Sunday, 01/02/2026 at 20:45

Full time

Match report · Ligue 1

RC Strasbourg Home 2.27 xG · 9 shots

Paris Saint-Germain Away 1.13 xG · 13 shots

12 The result went against the chances

Goals

22' Senny Mayulu Paris Saint-Germain · 0.17 xG chance 0–1
27' Guéla Doué RC Strasbourg · 0.43 xG chance 1–1
81' Nuno Mendes Paris Saint-Germain · 0.25 xG chance 1–2

The shots behind it

RC Strasbourg Paris Saint-Germain

Shots: 9; 13
On target: 4; 4
Inside the box: 9; 10
xG per shot: 0.25; 0.09
Open play xG: 1.31; 0.95
Set-piece xG: 0.16; 0.18
Penalties: 1; 0

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: 1.48 for RC Strasbourg.

Shot map

Both teams shown attacking the same goal for comparison.

All shots

22 shots · 3.42 xG

Hover, focus or tap a shot to read it.

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

Recent form

Last 6 · xG per match

RC Strasbourg

1.17 xG created 1.30 xGA

L 0.80 created, 1.05 conceded against Stade Brestois
L 0.05 created, 0.50 conceded against Toulouse
D 0.69 created, 0.53 conceded against Lorient
D 1.35 created, 2.75 conceded against Nice
W 1.12 created, 1.08 conceded against Metz
W 3.00 created, 1.86 conceded against Lille

Paris Saint-Germain

1.77 xG created 0.64 xGA

L 1.33 created, 0.52 conceded against AS Monaco
W 2.23 created, 0.24 conceded against Stade Rennais
W 1.85 created, 0.62 conceded against Metz
W 1.71 created, 1.01 conceded against Paris FC
W 1.40 created, 1.14 conceded against Lille
W 2.07 created, 0.30 conceded against Auxerre

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

Head to head

RC Strasbourg: 0 won · 1 drawn · 0 lost

Paris Saint-Germain 3:3 RC Strasbourg 17/10/2025 xG 2.67 – 2.15

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.