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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
3.20
Highest xG/game
0.75
Lowest xGA/game
93%
Top BTTS Rate
84%
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
38 3.20 0.75 +2.45 13 55% 72% 70% 31%
2
MCI
Manchester City
38 3.20 0.97 +2.23 13 55% 71% 69% 34%
3
MNU
Manchester United
38 3.20 1.38 +1.82 13 55% 60% 61% 37%
4
AVL
Aston Villa
38 3.20 1.35 +1.85 13 55% 54% 57% 32%
5
LIV
Liverpool
38 3.20 1.46 +1.74 13 55% 55% 58% 34%
6
BOU
Bournemouth
38 2.93 1.49 +1.44 12.3 54% 52% 56% 47%
8
BRI
Brighton
38 2.77 1.27 +1.50 11.9 53% 53% 57% 37%
10
CHE
Chelsea
38 2.72 1.44 +1.28 11.8 53% 53% 57% 35%
9
BRE
Brentford
38 2.71 1.44 +1.27 11.8 53% 52% 56% 37%
7
Sun
Sunderland
38 2.58 1.33 +1.25 11.5 53% 47% 53% 38%
11
FUL
Fulham
38 2.52 1.41 +1.11 11.3 53% 48% 54% 31%
12
NEW
Newcastle
38 2.41 1.52 +0.89 11 52% 49% 54% 31%
13
EVE
Everton
38 2.39 1.38 +1.01 11 52% 49% 54% 35%
14
Lee
Leeds
38 2.21 1.55 +0.66 10.5 52% 47% 53% 41%
16
NOT
Nottingham Forest
38 2.14 1.41 +0.73 10.4 51% 49% 54% 37%
15
CRY
Crystal Palace
38 2.05 1.41 +0.64 10.1 51% 45% 52% 38%
17
TOT
Tottenham
38 1.87 1.58 +0.29 9.7 51% 46% 52% 37%
18
WHU
West Ham
38 1.57 1.80 -0.23 8.9 50% 41% 49% 34%
19
BUR
Burnley
38 0.70 2.07 -1.37 6.8 47% 32% 43% 35%
20
WOL
Wolves
38 0.70 1.88 -1.18 6.8 47% 30% 41% 37%

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
38 3.20 0.99 +2.21 13 55% 80% 75% 22%
2
RMA
Real Madrid
38 3.20 0.97 +2.23 13 55% 71% 69% 28%
3
VIL
Villarreal
38 3.20 1.27 +1.93 13 55% 63% 64% 29%
4
ATM
Atletico Madrid
38 3.20 1.22 +1.98 13 55% 59% 61% 29%
5
BET
Real Betis
38 3.20 1.33 +1.87 13 55% 56% 59% 43%
6
CEL
Celta Vigo
38 2.80 1.33 +1.47 12 53% 53% 57% 38%
8
Ray
Rayo Vallecano
38 2.44 1.22 +1.22 11.1 52% 49% 54% 41%
7
GET
Getafe
38 2.43 1.05 +1.38 11.1 52% 47% 53% 29%
9
VAL
Valencia
38 2.27 1.52 +0.75 10.7 52% 46% 52% 35%
10
RSO
Real Sociedad
38 2.26 1.69 +0.57 10.7 52% 49% 54% 40%
11
Esp
Espanyol
38 2.06 1.52 +0.54 10.2 51% 44% 51% 35%
15
Elc
Elche
38 1.99 1.58 +0.41 10 51% 46% 52% 40%
17
OSA
Osasuna
38 1.98 1.38 +0.60 10 51% 47% 53% 34%
12
ATH
Athletic Club
38 1.95 1.60 +0.35 9.9 51% 43% 50% 29%
14
ALA
Alaves
38 1.91 1.55 +0.36 9.8 51% 44% 51% 35%
18
Mal
Mallorca
38 1.90 1.58 +0.32 9.8 51% 45% 52% 34%
13
SEV
Sevilla
38 1.87 1.66 +0.21 9.7 51% 43% 50% 31%
16
Lev
Levante
38 1.82 1.69 +0.13 9.6 50% 43% 50% 34%
19
Gir
Girona
38 1.73 1.52 +0.21 9.3 50% 42% 50% 41%
20
Ovi
Oviedo
38 0.77 1.66 -0.89 6.9 47% 33% 44% 37%

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
38 3.20 0.97 +2.23 13 55% 77% 73% 29%
2
NAP
Napoli
38 3.20 0.99 +2.21 13 55% 61% 62% 31%
3
ROM
AS Roma
38 3.20 0.86 +2.34 13 55% 64% 64% 26%
4
Com
Como
38 3.20 0.80 +2.40 13 55% 68% 67% 37%
5
MIL
AC Milan
38 3.20 0.97 +2.23 13 55% 59% 61% 35%
6
JUV
Juventus
38 3.20 0.94 +2.26 13 55% 64% 64% 38%
7
ATA
Atalanta
38 3.20 0.99 +2.21 13 55% 58% 60% 41%
8
BOL
Bologna
38 2.86 1.27 +1.59 12.2 54% 52% 56% 32%
9
LAZ
Lazio
38 2.72 1.11 +1.61 11.8 53% 51% 55% 38%
10
Udi
Udinese
38 2.44 1.33 +1.11 11.1 52% 49% 54% 32%
11
Sas
Sassuolo
38 2.37 1.38 +0.99 10.9 52% 48% 54% 31%
15
FIO
Fiorentina
38 1.92 1.38 +0.54 9.8 51% 46% 52% 43%
13
Par
Parma
38 1.89 1.27 +0.62 9.7 51% 41% 49% 38%
14
Cag
Cagliari
38 1.89 1.46 +0.43 9.7 51% 44% 51% 35%
12
TOR
Torino
38 1.87 1.74 +0.13 9.7 51% 41% 49% 34%
16
GEN
Genoa
38 1.85 1.41 +0.44 9.6 51% 45% 52% 37%
17
Lec
Lecce
38 1.46 1.38 +0.08 8.7 49% 39% 48% 32%
18
Cre
Cremonese
38 1.20 1.58 -0.38 8 49% 38% 47% 35%
19
Hel
Hellas Verona
38 0.70 1.69 -0.99 6.8 47% 32% 43% 38%
20
Pis
Pisa
38 0.70 1.96 -1.26 6.8 47% 28% 40% 38%

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
34 3.20 1.11 +2.09 13 55% 93% 84% 28%
2
Bor
Borussia Dortmund
34 3.20 1.05 +2.15 13 55% 68% 67% 31%
3
RBL
RB Leipzig
34 3.20 1.45 +1.75 13 55% 60% 61% 28%
4
STU
VfB Stuttgart
34 3.20 1.51 +1.69 13 55% 61% 62% 32%
5
189
1899 Hoffenheim
34 3.20 1.61 +1.59 13 55% 57% 59% 31%
6
LEV
Bayer Leverkusen
34 3.20 1.45 +1.75 13 55% 61% 62% 32%
7
SC
SC Freiburg
34 2.23 1.76 +0.47 10.6 52% 47% 53% 32%
8
FRA
Eintracht Frankfurt
34 2.12 2.01 +0.11 10.3 51% 48% 54% 37%
9
FC
FC Augsburg
34 1.83 1.88 -0.05 9.6 50% 42% 50% 31%
10
FSV
FSV Mainz 05
34 1.82 1.64 +0.18 9.6 50% 46% 52% 35%
12
Bor
Borussia Mönchengladbach
34 1.68 1.64 +0.04 9.2 50% 45% 51% 37%
11
Uni
Union Berlin
34 1.67 1.79 -0.12 9.2 50% 43% 50% 34%
13
Ham
Hamburger SV
34 1.62 1.67 -0.05 9.1 50% 43% 50% 37%
14
1.
1. FC Köln
34 1.32 1.95 -0.63 8.3 49% 43% 50% 37%
15
Wer
Werder Bremen
34 1.14 1.85 -0.71 7.9 48% 39% 47% 32%
16
VfL
VfL Wolfsburg
34 0.97 2.13 -1.16 7.4 48% 38% 47% 32%
17
1.
1. FC Heidenheim
34 0.70 2.22 -1.52 6.8 47% 35% 45% 32%
18
FC
FC St. Pauli
34 0.70 1.85 -1.15 6.8 47% 35% 45% 32%

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
Par
Paris Saint Germain
34 3.20 0.90 +2.30 13 55% 73% 70% 26%
2
LEN
Lens
34 3.20 1.08 +2.12 13 55% 66% 65% 26%
3
LIL
Lille
34 3.20 1.14 +2.06 13 55% 58% 60% 31%
4
LYO
Lyon
34 3.20 1.24 +1.96 13 55% 57% 59% 29%
5
MAR
Marseille
34 3.20 1.39 +1.81 13 55% 59% 61% 28%
6
REN
Rennes
34 3.13 1.54 +1.59 12.8 54% 55% 58% 32%
8
STR
Strasbourg
34 2.87 1.45 +1.42 12.2 54% 56% 59% 32%
7
MON
Monaco
34 2.82 1.67 +1.15 12.1 53% 53% 57% 29%
10
Tou
Toulouse
33 2.22 1.46 +0.76 10.6 52% 51% 55% 32%
9
Lor
Lorient
34 2.19 1.58 +0.61 10.5 52% 49% 54% 38%
11
Par
Paris FC
34 2.14 1.54 +0.60 10.4 51% 49% 54% 37%
12
Sta
Stade Brestois 29
34 1.71 1.70 +0.01 9.3 50% 44% 51% 34%
14
Le
Le Havre
34 1.51 1.36 +0.15 8.8 50% 44% 51% 41%
15
Aux
Auxerre
34 1.50 1.36 +0.14 8.8 50% 45% 52% 35%
13
Ang
Angers
34 1.42 1.48 -0.06 8.6 49% 41% 49% 34%
16
NIC
Nice
34 1.14 1.85 -0.71 7.9 48% 39% 47% 37%
17
Nan
Nantes
33 0.70 1.65 -0.95 6.8 47% 39% 47% 32%
18
Met
Metz
34 0.70 2.35 -1.65 6.8 47% 28% 40% 32%

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 →