Pisa 3:1 Cagliari: xG & match report · Serie A

Sunday, 15/03/2026 at 15:00

Full time

Match report · Serie A

Pisa Home 2.47 xG · 10 shots

Cagliari Away 1.31 xG · 14 shots

31 The scoreline reflected the chances

Goals

9' Stefano Moreo (pen.) Pisa · 0.82 xG chance 1–0
52' Antonio Caracciolo Pisa · 0.10 xG chance 2–0
54' Antonio Caracciolo Pisa · 0.87 xG chance 3–0
67' Leonardo Pavoletti Cagliari · 0.16 xG chance 3–1

The shots behind it

Pisa Cagliari

Shots: 10; 14
On target: 6; 4
Inside the box: 8; 9
xG per shot: 0.24; 0.10
Open play xG: 0.57; 1.15
Set-piece xG: 1.05; 0.25
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: 1.65 for Pisa and 1.37 for Cagliari.

Shot map

Both teams shown attacking the same goal for comparison.

All shots

24 shots · 3.84 xG

Hover, focus or tap a shot to read it.

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

Recent form

Last 6 · xG per match

Pisa

0.60 xG created 1.53 xGA

L 0.79 created, 1.63 conceded against Sassuolo
D 0.82 created, 0.06 conceded against Hellas Verona
L 0.77 created, 2.35 conceded against Milan
L 0.28 created, 1.84 conceded against Fiorentina
L 0.46 created, 0.61 conceded against Bologna
L 0.45 created, 2.67 conceded against Juventus

Cagliari

0.78 xG created 0.94 xGA

W 1.68 created, 0.46 conceded against Hellas Verona
L 0.35 created, 1.33 conceded against Roma
L 1.01 created, 1.35 conceded against Lecce
D 0.67 created, 0.69 conceded against Lazio
D 0.52 created, 1.28 conceded against Parma
L 0.47 created, 0.55 conceded against Como

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

Head to head

Pisa: 0 won · 1 drawn · 0 lost

Cagliari 2:2 Pisa 21/12/2025 xG 1.43 – 2.54

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.