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2026/27 Season

Football Statistics

Goals for/against per game, attack–defence differential, and market indicators for every club across Europe's top five leagues in 2026/27. Same season window as our predictions. No registration required.

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All season rates are free to access. Read how we use attacking and defensive rates in the model.

96 teams with data
5
Leagues
96
Teams Tracked
4
Max Matches Played
2026/27
Season
5.00
Highest GF/game
0.00
Lowest GA/game
85%
Top BTTS Indicator
85%
Top Over 2.5 Indicator
4
Match Window
Column Key:
GF/g = Goals for per game  •  GA/g = Goals against per game  •  Diff = GF/g − GA/g  •  SoT = Est. shots on target/game  •  Poss = Est. possession  •  BTTS% / O2.5% / CS% = market indicators from scoring rates
2026/27 Rates

Premier League Statistics

# Club MP GF/g GA/g Diff SoT Poss BTTS% O2.5% CS%
4
CHE
Chelsea
2 3.50 2.50 +1.00 9.5 60% 85% 85% 60%
9
BRI
Brighton
2 3.50 2.00 +1.50 9.5 61% 85% 85% 36%
1
MCI
Manchester City
2 3.00 1.00 +2.00 8.5 60% 81% 85% 60%
10
MNU
Manchester United
2 2.50 2.00 +0.50 7.5 55% 85% 85% 36%
2
ARS
Arsenal
2 2.00 0.00 +2.00 6.4 56% 59% 64% 60%
5
BRE
Brentford
2 2.00 0.50 +1.50 6.4 55% 64% 73% 36%
6
NEW
Newcastle
2 2.00 1.00 +1.00 6.4 54% 69% 82% 36%
12
IPS
Ipswich
2 2.00 3.00 -1.00 6.4 50% 85% 85% 36%
13
LIV
Liverpool
2 2.00 2.00 +0.00 6.4 52% 79% 85% 8%
3
HUL
Hull City
2 1.50 0.00 +1.50 5.4 53% 53% 55% 60%
7
EVE
Everton
2 1.50 0.50 +1.00 5.4 52% 58% 64% 36%
8
LEE
Leeds
2 1.00 0.50 +0.50 4.3 49% 52% 55% 36%
11
SUN
Sunderland
2 1.00 1.00 +0.00 4.3 48% 57% 64% 36%
14
BOU
Bournemouth
2 1.00 1.50 -0.50 4.3 47% 62% 73% 8%
15
NOT
Nottingham Forest
2 1.00 1.50 -0.50 4.3 47% 62% 73% 8%
16
FUL
Fulham
2 1.00 2.00 -1.00 4.3 46% 67% 82% 8%
18
CRY
Crystal Palace
2 0.50 3.00 -2.50 3.3 41% 71% 85% 8%
17
COV
Coventry
2 0.00 2.00 -2.00 2.5 40% 55% 64% 8%
19
AVL
Aston Villa
2 0.00 2.50 -2.50 2.5 39% 60% 73% 8%
20
TOT
Tottenham
2 0.00 2.50 -2.50 2.5 39% 60% 73% 8%

GF/g and GA/g are season goals for/against divided by matches played (2026/27). Sorted by GF/g descending. Finished previous-season tables are never shown.

# Club MP GF/g GA/g Diff SoT Poss BTTS% O2.5% CS%
1
BAR
Barcelona
3 4.00 0.67 +3.33 9.5 67% 85% 85% 60%
2
RMA
Real Madrid
3 3.33 0.67 +2.66 9.2 63% 82% 85% 60%
3
ATM
Atletico Madrid
3 2.33 1.00 +1.33 7.1 56% 73% 85% 45%
6
SEV
Sevilla
3 2.00 1.67 +0.33 6.4 53% 76% 85% 45%
4
ALA
Alaves
3 1.67 0.33 +1.34 5.7 53% 58% 64% 45%
8
DEP
Deportivo La Coruna
3 1.67 1.00 +0.67 5.7 52% 65% 76% 26%
9
LEV
Levante
3 1.67 1.67 +0.00 5.7 51% 72% 85% 26%
10
RAC
Racing Santander
3 1.67 1.67 +0.00 5.7 51% 72% 85% 26%
12
ESP
Espanyol
3 1.67 1.33 +0.34 5.7 51% 68% 82% 26%
7
BET
Real Betis
3 1.33 1.67 -0.34 5 49% 68% 82% 45%
15
VIL
Villarreal
3 1.33 1.67 -0.34 5 49% 68% 82% 8%
18
RAY
Rayo Vallecano
3 1.33 2.67 -1.34 5 47% 78% 85% 8%
5
OSA
Osasuna
3 1.00 0.33 +0.67 4.3 49% 50% 52% 45%
13
ATH
Athletic Club
3 1.00 1.67 -0.67 4.3 47% 64% 76% 26%
19
ELC
Elche
3 1.00 3.00 -2.00 4.3 44% 77% 85% 8%
11
RSO
Real Sociedad
4 0.75 1.50 -0.75 3.8 46% 59% 69% 22%
14
GET
Getafe
3 0.33 1.33 -1.00 2.9 43% 52% 58% 26%
17
VAL
Valencia
3 0.33 1.33 -1.00 2.9 43% 52% 58% 8%
20
MAL
Malaga
3 0.33 2.33 -2.00 2.9 41% 62% 76% 8%
16
CEL
Celta Vigo
4 0.25 1.00 -0.75 2.7 44% 48% 51% 8%

GF/g and GA/g are season goals for/against divided by matches played (2026/27). Sorted by GF/g descending. Finished previous-season tables are never shown.

# Club MP GF/g GA/g Diff SoT Poss BTTS% O2.5% CS%
1
ROM
AS Roma
2 4.00 0.00 +4.00 9.5 68% 83% 85% 60%
2
INT
Inter
2 2.50 0.50 +2.00 7.5 58% 70% 82% 60%
3
MIL
AC Milan
2 2.00 0.50 +1.50 6.4 55% 64% 73% 60%
7
UDI
Udinese
2 2.00 1.50 +0.50 6.4 53% 74% 85% 36%
4
JUV
Juventus
2 1.50 0.00 +1.50 5.4 53% 53% 55% 60%
5
ATA
Atalanta
2 1.50 0.50 +1.00 5.4 52% 58% 64% 60%
8
COM
Como
2 1.50 1.00 +0.50 5.4 51% 63% 73% 36%
9
FRO
Frosinone
2 1.50 0.50 +1.00 5.4 52% 58% 64% 36%
10
NAP
Napoli
2 1.50 1.00 +0.50 5.4 51% 63% 73% 36%
11
SAS
Sassuolo
2 1.50 1.50 +0.00 5.4 50% 68% 82% 36%
18
MON
Monza
2 1.50 3.50 -2.00 5.4 46% 85% 85% 8%
6
LAZ
Lazio
2 1.00 0.00 +1.00 4.3 50% 47% 46% 60%
13
LEC
Lecce
2 1.00 2.00 -1.00 4.3 46% 67% 82% 36%
14
TOR
Torino
2 1.00 2.00 -1.00 4.3 46% 67% 82% 8%
12
CAG
Cagliari
2 0.50 0.50 +0.00 3.3 46% 46% 46% 36%
15
BOL
Bologna
2 0.00 1.00 -1.00 2.5 42% 45% 46% 8%
16
GEN
Genoa
2 0.00 1.50 -1.50 2.5 41% 50% 55% 8%
17
PAR
Parma
2 0.00 1.50 -1.50 2.5 41% 50% 55% 8%
19
VEN
Venezia
2 0.00 2.00 -2.00 2.5 40% 55% 64% 8%
20
FIO
Fiorentina
2 0.00 3.50 -3.50 2.5 38% 70% 85% 8%

GF/g and GA/g are season goals for/against divided by matches played (2026/27). Sorted by GF/g descending. Finished previous-season tables are never shown.

# Club MP GF/g GA/g Diff SoT Poss BTTS% O2.5% CS%
1
BAY
Bayern München
1 5.00 1.00 +4.00 9.5 68% 85% 85% 60%
2
SCF
SC Freiburg
1 4.00 1.00 +3.00 9.5 66% 85% 85% 60%
3
FCA
FC Augsburg
1 3.00 0.00 +3.00 8.5 62% 71% 82% 60%
4
RBL
RB Leipzig
1 3.00 0.00 +3.00 8.5 62% 71% 82% 60%
6
SVE
SV Elversberg
1 3.00 2.00 +1.00 8.5 58% 85% 85% 60%
7
FCK
1. FC Köln
1 3.00 2.00 +1.00 8.5 58% 85% 85% 60%
8
FRA
Eintracht Frankfurt
1 3.00 3.00 +0.00 8.5 56% 85% 85% 8%
9
UNI
Union Berlin
1 3.00 3.00 +0.00 8.5 56% 85% 85% 8%
5
DOR
Borussia Dortmund
1 2.00 0.00 +2.00 6.4 56% 59% 64% 60%
12
HOF
1899 Hoffenheim
1 2.00 3.00 -1.00 6.4 50% 85% 85% 8%
13
LEV
Bayer Leverkusen
1 2.00 3.00 -1.00 6.4 50% 85% 85% 8%
15
WER
Werder Bremen
1 1.00 4.00 -3.00 4.3 42% 85% 85% 8%
18
STU
VfB Stuttgart
1 1.00 5.00 -4.00 4.3 40% 85% 85% 8%
10
FSV
FSV Mainz 05
1 0.00 0.00 +0.00 2.5 44% 35% 30% 8%
11
SCP
SC Paderborn 07
1 0.00 0.00 +0.00 2.5 44% 35% 30% 8%
14
HAM
Hamburger SV
1 0.00 2.00 -2.00 2.5 40% 55% 64% 8%
16
BOR
Borussia Mönchengladbach
1 0.00 3.00 -3.00 2.5 38% 65% 82% 8%
17
FCS
FC Schalke 04
1 0.00 3.00 -3.00 2.5 38% 65% 82% 8%

GF/g and GA/g are season goals for/against divided by matches played (2026/27). Sorted by GF/g descending. Finished previous-season tables are never shown.

# Club MP GF/g GA/g Diff SoT Poss BTTS% O2.5% CS%
7
LEN
Lens
2 3.00 2.00 +1.00 8.5 58% 85% 85% 36%
5
REN
Rennes
2 2.50 2.00 +0.50 7.5 55% 85% 85% 36%
8
MAR
Marseille
2 2.00 1.00 +1.00 6.4 54% 69% 82% 36%
11
STA
Stade Brestois 29
2 2.00 2.00 +0.00 6.4 52% 79% 85% 8%
12
PSG
Paris Saint Germain
2 2.00 2.00 +0.00 6.4 52% 79% 85% 8%
13
LEM
Le Mans
2 2.00 2.50 -0.50 6.4 51% 84% 85% 8%
1
LIL
Lille
3 1.67 0.67 +1.00 5.7 53% 62% 70% 45%
2
MON
Monaco
2 1.50 0.00 +1.50 5.4 53% 53% 55% 60%
3
PAR
Paris FC
2 1.50 0.00 +1.50 5.4 53% 53% 55% 36%
4
LYO
Lyon
2 1.50 0.50 +1.00 5.4 52% 58% 64% 36%
9
ANG
Angers
2 1.50 1.50 +0.00 5.4 50% 68% 82% 36%
18
AUX
Auxerre
2 1.50 4.00 -2.50 5.4 45% 85% 85% 8%
6
EST
Estac Troyes
2 1.00 0.50 +0.50 4.3 49% 52% 55% 36%
10
STR
Strasbourg
2 1.00 2.50 -1.50 4.3 45% 72% 85% 36%
16
TOU
Toulouse
3 0.67 1.67 -1.00 3.6 45% 60% 70% 8%
14
LOR
Lorient
2 0.50 1.00 -0.50 3.3 45% 51% 55% 8%
15
LEH
Le Havre
2 0.50 1.00 -0.50 3.3 45% 51% 55% 8%
17
NIC
Nice
2 0.00 1.50 -1.50 2.5 41% 50% 55% 8%

GF/g and GA/g are season goals for/against divided by matches played (2026/27). Sorted by GF/g descending. Finished previous-season tables are never shown.

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 →