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Statistical Database

Football xG Statistics

Expected goals, xGA, shots on target, possession, BTTS rate and over/under rate for every team across Europe's top five leagues. Powered by the same data that drives xGaura's daily predictions. No registration required.

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All xG data is free to access. Read how we calculate and use xG in our model.

5 Leagues
5
Leagues
98
Teams
38
Match Window
xG
Primary Metric
2.93
Highest xG/game
0.70
Lowest xGA/game
72%
Top BTTS Rate
70%
Top Over 2.5 Rate
38
Match Window
Column Key:
xG = Exp. Goals For  •  xGA = Exp. Goals Against  •  Diff = xG − xGA  •  SoT = Shots on Target/game  •  Poss = Avg Possession  •  BTTS% = Both Teams Score rate  •  O2.5% = Over 2.5 Goals rate  •  CS% = Clean Sheet rate
xG Database

Premier League xG Statistics

# Club MP xG xGA Diff SoT Poss BTTS% O2.5% CS%
1
ARS
Arsenal
19 2.75 0.70 +2.05 11.9 53% 63% 63% 25%
2
MCI
Manchester City
18 2.52 0.99 +1.53 11.3 53% 63% 64% 22%
3
AVL
Aston Villa
19 2.09 1.27 +0.82 10.2 51% 54% 57% 25%
5
CHE
Chelsea
19 1.72 1.16 +0.56 9.3 50% 56% 59% 29%
4
LIV
Liverpool
18 1.68 1.52 +0.16 9.2 50% 52% 56% 23%
6
MNU
Manchester United
19 1.58 1.60 -0.02 9 50% 52% 56% 29%
7
Sun
Sunderland
18 1.44 1.05 +0.39 8.6 49% 51% 56% 31%
8
EVE
Everton
19 1.40 1.11 +0.29 8.5 49% 50% 55% 26%
9
BRE
Brentford
18 1.34 1.52 -0.18 8.4 49% 51% 56% 23%
10
NEW
Newcastle
19 1.34 1.33 +0.01 8.4 49% 51% 56% 28%
13
TOT
Tottenham
18 1.33 1.34 -0.01 8.3 49% 52% 56% 26%
11
CRY
Crystal Palace
18 1.32 1.17 +0.15 8.3 49% 51% 55% 28%
12
FUL
Fulham
18 1.28 1.52 -0.24 8.2 49% 50% 55% 23%
14
BRI
Brighton
19 1.27 1.49 -0.22 8.2 49% 51% 55% 31%
15
BOU
Bournemouth
19 1.03 1.93 -0.90 7.6 48% 47% 53% 32%
16
Lee
Leeds
18 0.86 1.87 -1.01 7.2 48% 47% 53% 28%
17
NOT
Nottingham Forest
19 0.70 1.66 -0.96 6.8 47% 44% 51% 25%
18
WHU
West Ham
19 0.70 2.10 -1.40 6.8 47% 42% 49% 28%
19
BUR
Burnley
19 0.70 2.04 -1.34 6.8 47% 42% 49% 25%
20
WOL
Wolves
19 0.70 2.21 -1.51 6.8 47% 36% 45% 25%

xG figures = rolling 38-match average. Sorted by xG/game descending. Last updated: today 08:00 UTC.

# Club MP xG xGA Diff SoT Poss BTTS% O2.5% CS%
1
BAR
Barcelona
18 2.92 1.17 +1.75 12.3 54% 66% 65% 22%
2
RMA
Real Madrid
18 2.50 0.93 +1.57 11.3 53% 60% 62% 25%
3
ATM
Atletico Madrid
18 2.19 0.93 +1.26 10.5 52% 59% 61% 26%
4
VIL
Villarreal
16 2.07 0.98 +1.09 10.2 51% 58% 60% 23%
5
Esp
Espanyol
17 1.75 1.05 +0.70 9.4 50% 53% 57% 25%
6
BET
Real Betis
17 1.60 1.17 +0.43 9 50% 55% 58% 31%
7
CEL
Celta Vigo
17 1.17 1.17 +0.00 7.9 49% 51% 55% 32%
9
Elc
Elche
17 1.16 1.24 -0.08 7.9 48% 52% 56% 31%
8
ATH
Athletic Club
18 0.99 1.40 -0.41 7.5 48% 46% 52% 23%
10
SEV
Sevilla
17 0.96 1.61 -0.65 7.4 48% 49% 54% 23%
12
OSA
Osasuna
17 0.84 1.24 -0.40 7.1 48% 49% 54% 25%
11
GET
Getafe
17 0.82 1.36 -0.54 7.1 47% 46% 52% 23%
13
Mal
Mallorca
17 0.80 1.48 -0.68 7 47% 48% 53% 29%
14
ALA
Alaves
17 0.78 1.24 -0.46 7 47% 47% 53% 25%
16
RSO
Real Sociedad
17 0.77 1.54 -0.77 6.9 47% 48% 54% 28%
15
Ray
Rayo Vallecano
17 0.76 1.24 -0.48 6.9 47% 47% 53% 29%
17
VAL
Valencia
17 0.70 1.61 -0.91 6.8 47% 45% 52% 31%
18
Gir
Girona
17 0.70 2.04 -1.34 6.8 47% 41% 49% 29%
19
Ovi
Oviedo
17 0.70 1.61 -0.91 6.8 47% 41% 49% 28%
20
Lev
Levante
16 0.70 1.90 -1.20 6.8 47% 44% 51% 26%

xG figures = rolling 38-match average. Sorted by xG/game descending. Last updated: today 08:00 UTC.

# Club MP xG xGA Diff SoT Poss BTTS% O2.5% CS%
1
Int
Inter
16 2.22 0.92 +1.30 10.6 52% 61% 62% 20%
2
MIL
AC Milan
16 2.03 0.85 +1.18 10.1 51% 57% 60% 28%
3
NAP
Napoli
16 1.92 0.85 +1.07 9.8 51% 56% 59% 22%
4
ROM
AS Roma
17 1.83 0.70 +1.13 9.6 50% 55% 58% 20%
5
JUV
Juventus
17 1.76 0.93 +0.83 9.4 50% 54% 58% 28%
6
Com
Como
16 1.55 0.79 +0.76 8.9 50% 55% 58% 29%
7
BOL
Bologna
16 1.50 0.92 +0.58 8.8 50% 55% 58% 28%
8
LAZ
Lazio
17 1.32 0.74 +0.58 8.3 49% 53% 57% 29%
9
Sas
Sassuolo
17 1.12 1.30 -0.18 7.8 48% 51% 55% 26%
10
ATA
Atalanta
17 1.12 1.17 -0.05 7.8 48% 51% 55% 31%
12
Cre
Cremonese
17 1.01 1.24 -0.23 7.5 48% 49% 54% 29%
11
Udi
Udinese
17 0.90 1.73 -0.83 7.3 48% 45% 52% 26%
14
Cag
Cagliari
17 0.80 1.48 -0.68 7 47% 48% 53% 29%
13
TOR
Torino
17 0.78 1.73 -0.95 7 47% 45% 51% 28%
15
Par
Parma
16 0.71 1.18 -0.47 6.8 47% 47% 53% 28%
16
Lec
Lecce
16 0.70 1.44 -0.74 6.8 47% 45% 51% 26%
17
GEN
Genoa
17 0.70 1.67 -0.97 6.8 47% 45% 52% 28%
18
Ver
Verona
16 0.70 1.64 -0.94 6.8 47% 44% 51% 29%
19
Pis
Pisa
17 0.70 1.48 -0.78 6.8 47% 44% 51% 32%
20
FIO
Fiorentina
17 0.70 1.73 -1.03 6.8 47% 45% 51% 29%

xG figures = rolling 38-match average. Sorted by xG/game descending. Last updated: today 08:00 UTC.

# Club MP xG xGA Diff SoT Poss BTTS% O2.5% CS%
1
Bay
Bayern München
15 2.93 0.77 +2.16 12.3 54% 72% 70% 23%
2
Bor
Borussia Dortmund
15 1.88 0.84 +1.04 9.7 51% 57% 60% 28%
3
LEV
Bayer Leverkusen
15 1.71 1.40 +0.31 9.3 50% 57% 59% 23%
4
RBL
RB Leipzig
15 1.67 1.33 +0.34 9.2 50% 56% 59% 23%
5
189
1899 Hoffenheim
15 1.53 1.40 +0.13 8.8 50% 55% 58% 25%
6
STU
VfB Stuttgart
15 1.36 1.54 -0.18 8.4 49% 52% 56% 23%
7
FRA
Eintracht Frankfurt
15 1.25 2.10 -0.85 8.1 49% 50% 55% 26%
8
Uni
Union Berlin
15 0.99 1.61 -0.62 7.5 48% 49% 54% 25%
9
SC
SC Freiburg
15 0.98 1.82 -0.84 7.5 48% 50% 55% 28%
11
1.
1. FC Köln
15 0.76 1.68 -0.92 6.9 47% 49% 54% 26%
10
Wer
Werder Bremen
15 0.70 1.96 -1.26 6.8 47% 45% 52% 28%
12
Bor
Borussia Mönchengladbach
15 0.70 1.68 -0.98 6.8 47% 47% 53% 26%
13
Ham
Hamburger SV
15 0.70 1.75 -1.05 6.8 47% 46% 52% 26%
14
VfL
VfL Wolfsburg
15 0.70 1.96 -1.26 6.8 47% 48% 53% 25%
15
FC
FC Augsburg
15 0.70 1.96 -1.26 6.8 47% 45% 51% 23%
16
FC
FC St. Pauli
15 0.70 1.82 -1.12 6.8 47% 44% 51% 25%
17
1.
1. FC Heidenheim
15 0.70 2.38 -1.68 6.8 47% 40% 48% 23%
18
FSV
FSV Mainz 05
15 0.70 1.82 -1.12 6.8 47% 44% 51% 28%

xG figures = rolling 38-match average. Sorted by xG/game descending. Last updated: today 08:00 UTC.

# Club MP xG xGA Diff SoT Poss BTTS% O2.5% CS%
2
Par
Paris Saint Germain
16 2.22 0.92 +1.30 10.6 52% 61% 62% 25%
1
LEN
Lens
16 2.15 0.85 +1.30 10.4 51% 58% 60% 22%
3
MAR
Marseille
16 2.02 0.98 +1.04 10.1 51% 61% 62% 23%
4
LIL
Lille
16 1.86 1.31 +0.55 9.7 51% 57% 59% 23%
5
LYO
Lyon
16 1.47 1.05 +0.42 8.7 49% 53% 57% 25%
6
REN
Rennes
16 1.41 1.58 -0.17 8.5 49% 52% 56% 29%
7
STR
Strasbourg
16 1.25 1.31 -0.06 8.1 49% 53% 57% 23%
8
Tou
Toulouse
16 1.25 1.25 +0.00 8.1 49% 53% 57% 28%
9
MON
Monaco
16 1.13 1.77 -0.64 7.8 48% 50% 55% 23%
10
Ang
Angers
16 1.08 1.18 -0.10 7.7 48% 50% 55% 26%
11
Sta
Stade Brestois 29
16 0.83 1.77 -0.94 7.1 47% 47% 53% 26%
12
Lor
Lorient
16 0.72 1.84 -1.12 6.8 47% 46% 52% 29%
13
NIC
Nice
16 0.70 1.90 -1.20 6.8 47% 45% 52% 23%
14
Par
Paris FC
16 0.70 1.90 -1.20 6.8 47% 46% 52% 26%
15
Le
Le Havre
16 0.70 1.44 -0.74 6.8 47% 46% 52% 29%
16
Aux
Auxerre
16 0.70 1.64 -0.94 6.8 47% 45% 51% 25%
17
Nan
Nantes
16 0.70 1.84 -1.14 6.8 47% 43% 50% 28%
18
Met
Metz
16 0.70 2.43 -1.73 6.8 47% 40% 48% 23%

xG figures = rolling 38-match average. Sorted by xG/game descending. Last updated: today 08:00 UTC.

About xG Statistics

Understanding Football xG Statistics

Focus: Football xG Statistics & Expected Goals Data

What Is xG and Why Is It the Most Useful Football Statistic?

Expected goals (xG) is a statistical measure that assigns a probability to each shot, representing the likelihood of it resulting in a goal based on shot quality rather than outcomes. A shot from six yards centrally might have an xG of 0.75. A long-range effort from outside the box might have an xG of 0.04. Summing all shots in a match gives each team's total xG — a measure of how many goals they deserved based on the chances they created.

Why is xG more useful than actual goals? Because goals contain random variance. An exceptional save, a shot hitting the post, a goalkeeper's positioning error — these are low-probability events that affect whether a goal is scored but carry no information about the quality of the chance itself. Over a season, teams tend to score roughly in line with their accumulated xG. Teams consistently outperforming their xG are likely finishing well above the sustainable rate and will regress. Teams underperforming are likely to improve.

How to Read the xG Statistics Table

xG (Expected Goals For) — how many goals per game a team is expected to score based on the quality of chances they create. The teams at the top of this column are the most dangerous attacking sides in the league. xGA (Expected Goals Against) — how many goals per game a team is expected to concede based on the quality of chances their opponents create against them. Lower is better. Diff (xG − xGA) — the net xG differential. A positive differential indicates a team creating significantly better chances than they allow. This is the most reliable single indicator of a team's true quality. BTTS% — the percentage of a team's matches in which both teams scored. High BTTS% teams make strong candidates for BTTS Yes markets. O2.5% — the percentage of matches in which over 2.5 goals were scored. High O2.5% teams are good candidates for over markets. CS% — clean sheet percentage, useful for BTTS No and under markets.

Using xG Data for Football Predictions

xG data is most useful when it reveals a gap between actual results and expected performance. A team sitting mid-table with the third-best xG differential in the league is likely underperforming and worth backing. A team in the top four with a negative xG differential has likely been scoring from poor chances or benefiting from opponents' poor finishing — a fragile position that may not hold. Cross-reference the xG table with the points standings and the value bet index to find markets where the bookmaker's price does not reflect the underlying statistical reality.

All xG figures are rolling 38-match averages, updated daily. For the full Poisson model output using these xG inputs, see the mathematical predictions page. For tips derived from the model, see today's predictions. Bet responsibly. 18+ only.

Related

Use the Data

Model

Mathematical Predictions

Full Poisson scoreline matrices and 1X2 probabilities for today's fixtures, built from the xG data on this page.

Standings

League Tables with xG

Full league standings with xG and xGA columns — see which teams are over or underperforming their expected results.

Edge

Value Bet Index

Markets where the model's probability exceeds the bookmaker's implied price. Built from the xG inputs above.

Updated dailyView value bets →