Lazio 3:3 Torino: xG & match report · Serie A

Saturday, 04/10/2025 at 15:00

Full time

Match report · Serie A

Lazio Home 1.35 xG · 9 shots

Torino Away 1.76 xG · 16 shots

33 Torino had the better chances, but it finished level

Goals

16' Giovanni Simeone Torino · 0.52 xG chance 0–1
24' Matteo Cancellieri Lazio · 0.14 xG chance 1–1
40' Matteo Cancellieri Lazio · 0.15 xG chance 2–1
73' Che Adams Torino · 0.38 xG chance 2–2
90' Danilo Cataldi (pen.) Lazio · 0.82 xG chance – Scored in the same minute as another goal, so the score after it is not shown.
90' Saúl Coco Torino · 0.18 xG chance – Scored in the same minute as another goal, so the score after it is not shown.

The shots behind it

Lazio Torino

Shots: 9; 16
On target: 4; 8
Inside the box: 4; 10
xG per shot: 0.14; 0.11
Open play xG: 0.41; 1.60
Set-piece xG: 0.05; 0.23
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: 0.46 for Lazio and 1.78 for Torino.

Shot map

Both teams shown attacking the same goal for comparison.

All shots

25 shots · 3.11 xG

Hover, focus or tap a shot to read it.

Lazio
Torino
Filled = goal
Dot area = xG (the smallest chances drawn at a minimum size)

Recent form

Last 6 · xG per match

Lazio

1.39 xG created 1.25 xGA

L 0.21 created, 1.54 conceded against Como
W 3.85 created, 0.77 conceded against Hellas Verona
L 0.76 created, 1.16 conceded against Sassuolo
L 1.04 created, 1.16 conceded against Roma
W 1.07 created, 1.63 conceded against Genoa

Torino

0.91 xG created 1.49 xGA

L 0.94 created, 1.59 conceded against Inter
D 1.02 created, 1.74 conceded against Fiorentina
W 0.65 created, 1.14 conceded against Roma
L 1.20 created, 1.64 conceded against Atalanta
L 0.76 created, 1.34 conceded against Parma

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.