xgEdge

Expected goals

AS Monaco expected goals (xG) 2026/2027

Ligue 1 · after 5 matches · updated 1 Oct

AS Monaco's attacking and defensive expected goals in Ligue 1 2026/2027, compared with the results they produced and with the rest of the competition.

AS Monaco xG and xGA per match

Every match ↓
Attack
1.28 xG per match
#15/18
Attack (xG per match) across Ligue 1, best first
Rank Club xG per match
#1 Paris Saint-Germain 2.28
#2 RC Lens 2.27
#3 Toulouse 2.19
#4 Stade Brestois 1.94
#5 Paris FC 1.87
#6 Olympique Lyonnais 1.79
#7 Stade Rennais 1.76
#8 Le Mans 1.70
#9 Angers 1.61
#10 Olympique de Marseille 1.56
#11 Auxerre 1.41
#12 Troyes 1.40
#13 Le Havre 1.39
#14 Lille 1.39
#15 AS Monaco 1.28
#16 RC Strasbourg 1.24
#17 Lorient 1.19
#18 Nice 1.08
League avg
1.63
Total
6.42 5 matches
Defence
1.31 xGA per match
#5/18
Defence (xGA per match) across Ligue 1, best first
Rank Club xGA per match
#1 Paris FC 0.65
#2 Paris Saint-Germain 1.14
#3 Olympique Lyonnais 1.17
#4 Stade Brestois 1.19
#5 AS Monaco 1.31
#6 Lorient 1.39
#7 Angers 1.41
#8 Le Havre 1.61
#9 Toulouse 1.64
=10 Lille 1.75
=10 Nice 1.75
#12 Le Mans 1.91
#13 RC Lens 1.92
=14 RC Strasbourg 1.96
=14 Troyes 1.96
#16 Auxerre 2.05
#17 Stade Rennais 2.27
#18 Olympique de Marseille 2.28
League avg
1.63
Total
6.53 5 matches
xG difference
-0.02 xGD per match
#8/18
xG difference (xGD per match) across Ligue 1, best first
Rank Club xGD per match
#1 Paris FC +1.22
#2 Paris Saint-Germain +1.14
#3 Stade Brestois +0.75
#4 Olympique Lyonnais +0.62
#5 Toulouse +0.55
#6 RC Lens +0.35
#7 Angers +0.20
#8 AS Monaco -0.02
=9 Le Mans -0.21
=9 Lorient -0.21
#11 Le Havre -0.22
#12 Lille -0.36
#13 Stade Rennais -0.51
#14 Troyes -0.56
#15 Auxerre -0.63
#16 Nice -0.67
#17 Olympique de Marseille -0.72
#18 RC Strasbourg -0.72
League avg
0.00
Total
-0.11 5 matches
Expected points Model — Model output — computed from each match's xG, not a result. How xPts works →
1.42 xPts per match
#8/18
Expected points (xPts per match) across Ligue 1, best first
Rank Club xPts per match
#1 Paris FC 2.17
#2 Paris Saint-Germain 2.06
#3 Olympique Lyonnais 1.81
#4 Stade Brestois 1.78
#5 Toulouse 1.74
#6 RC Lens 1.49
#7 Angers 1.49
#8 AS Monaco 1.42
#9 Le Mans 1.27
#10 Lille 1.23
#11 Lorient 1.21
#12 Le Havre 1.20
#13 Auxerre 1.18
#14 Olympique de Marseille 1.09
#15 Stade Rennais 1.08
#16 Troyes 0.96
#17 Nice 0.94
#18 RC Strasbourg 0.84
League avg
1.39
Total
7.10 vs 13 actual pts

Early-season figures: after 5 matches, per-match rates can move quickly.

What the xG says

AS Monaco's underlying numbers sit close to the Ligue 1 average. They rank #8 for xG difference at -0.02 per match, built on high chance quality rather than the league's lowest shot volume. Their 8 goals are 1.58 above 6.42 xG, while 13 points are 5.90 above 7.10 xPts. After only 5 matches, those gaps should still be read cautiously.

Actual vs expected

Measure Actual Expected Difference Reading
Goals vs xG Includes 0.52 xG from penalties
8 6.42 +1.58 scored 1.58 more than xG within normal variance
Goals conceded vs xGA
3 6.53 -3.53 conceded 3.53 fewer than xGA outside normal variance
Points vs xPts Model — Model output — computed from each match's xG, not a result. How xPts works →
13 7.10 +5.90 5.90 points above xPts far outside normal variance

Select a row to chart it across the season.

Goals minus xG, match by match

AS Monaco are 1.58 goals above their xG after 5 matches.

Goals
8
xG
6.42
Gap
+1.58
Sun 23/08 Sun 30/08 Fri 04/09 Sat 12/09 Fri 18/09 -1 0 +1 +2 -0.39 -0.11 +1.38 +1.33 +1.58 -0.39 +0.28 +1.49 -0.05 +0.25 Running gap goals − xG Each match goals − xG
AS Monaco: Goals vs xG, the gap after every match with xG
Date Opponent Goals xG Match gap Running gap
Sun 23/08 Le Havre 1 1.39 -0.39 -0.39
Sun 30/08 Olympique de Marseille 2 1.72 +0.28 -0.11
Fri 04/09 Paris Saint-Germain 2 0.51 +1.49 +1.38
Sat 12/09 RC Strasbourg 1 1.05 -0.05 +1.33
Fri 18/09 RC Lens 2 1.75 +0.25 +1.58

Goals vs xG ranking → Expected points ranking →

AS Monaco xG trend

Current form -0.03 npxGD per match

All 5 matches with xG so far — the window fills at 6.

Out-created the opponent in 3 of 5 matches. The worst was against Paris Saint-Germain on Fri 04/09 (-1.67).

npxG · last 5
1.18
npxGA · last 5
1.21
-2 -1 0 +1 +0.83 Sun 23/08 +0.27 Sun 30/08 -1.67 Fri 04/09 -0.22 Sat 12/09 +0.64 Fri 18/09 -0.03 season avg
AS Monaco: non-penalty xG, xGA and their difference in each match, with the season's average so far
Date Opponent npxG npxGA npxGD Avg so far
Sun 23/08 Le Havre 1.43 0.60 +0.83 +0.83
Sun 30/08 Olympique de Marseille 1.49 1.22 +0.27 +0.55
Fri 04/09 Paris Saint-Germain 0.52 2.19 -1.67 -0.19
Sat 12/09 RC Strasbourg 0.78 1.00 -0.22 -0.20
Fri 18/09 RC Lens 1.68 1.04 +0.64 -0.03

Each bar is one match's non-penalty xG minus the non-penalty xG against; the line is that difference averaged over the season up to each match, and it finishes on the dashed season average — 1.18 npxG and 1.21 npxGA per match. Current form is the same difference over the last 6 matches with xG.

Form ranking →

Strength of schedule

Season so far
number 1 hardest of 18 in Ligue 1
+0.18 xG vs league average
Over 5 league matches
Opponents behind the figures

Season so far

+0.18 xG vs league average · over 5 matches · number 1 hardest of 18

  1. RC Lens Home +0.41
  2. RC Strasbourg Away −0.22
  3. Paris Saint-Germain Away +0.90
  4. Olympique de Marseille Home −0.04
  5. Le Havre Away −0.13

League schedule strength → How this is calculated →

AS Monaco shots and chance quality

Low volume, high quality. AS Monaco take 10.2 shots a match (league 13.9) at 0.12 npxG a shot (league 0.11), #18 in Ligue 1 for volume and #4 for quality. 59% of their shots come from inside the box (league 65%), and set pieces produce 14% of their npxG (league 18%).

Attack

Shot volume
10.2 shots per match
#18/18
Shot volume (shots per match) across Ligue 1, best first
Rank Club shots per match
#1 Paris Saint-Germain 21.2
#2 Stade Brestois 19.2
#3 Stade Rennais 16.2
#4 Le Havre 15.6
#5 Angers 15.0
=6 RC Lens 14.8
=6 Toulouse 14.8
=6 Troyes 14.8
#9 Olympique Lyonnais 13.4
=10 Olympique de Marseille 13.2
=10 Paris FC 13.2
#12 Lille 12.8
#13 Auxerre 12.0
#14 Nice 11.8
#15 RC Strasbourg 11.6
=16 Le Mans 10.4
=16 Lorient 10.4
#18 AS Monaco 10.2
League avg
13.9
Total
51 shots from 5 matches
Chance quality
0.12 npxG per shot
#4/18
Chance quality (npxG per shot) across Ligue 1, best first
Rank Club npxG per shot
#1 Le Mans 0.15
#2 Olympique Lyonnais 0.13
#3 Toulouse 0.13
#4 AS Monaco 0.12
#5 Paris FC 0.11
#6 RC Lens 0.11
#7 RC Strasbourg 0.11
#8 Angers 0.11
#9 Paris Saint-Germain 0.11
#10 Lorient 0.11
#11 Lille 0.11
#12 Olympique de Marseille 0.10
#13 Stade Rennais 0.09
#14 Nice 0.09
#15 Stade Brestois 0.09
#16 Auxerre 0.09
#17 Le Havre 0.08
#18 Troyes 0.07
League avg
0.11
Total
5.90 npxG from 51 shots

Defence

Shots allowed
15.2 shots per match
=11/18
Shots allowed (shots per match) across Ligue 1, best first
Rank Club shots per match
#1 Paris FC 9.6
#2 Paris Saint-Germain 10.0
=3 Olympique Lyonnais 11.2
=3 RC Lens 11.2
#5 Stade Brestois 11.6
#6 Nice 13.0
#7 Lorient 13.2
#8 Auxerre 13.6
#9 Troyes 13.8
#10 Le Havre 14.4
=11 AS Monaco 15.2
=11 Toulouse 15.2
#13 Stade Rennais 15.6
#14 Lille 16.0
#15 Le Mans 16.2
#16 Angers 16.4
#17 Olympique de Marseille 17.0
#18 RC Strasbourg 17.4
League avg
13.9
Total
76 shots allowed from 5 matches
Chance quality allowed
0.08 npxGA per shot
#4/18
Chance quality allowed (npxGA per shot) across Ligue 1, best first
Rank Club npxGA per shot
#1 Paris FC 0.07
#2 Angers 0.08
#3 Lorient 0.08
#4 AS Monaco 0.08
#5 Stade Brestois 0.09
#6 Le Havre 0.09
#7 RC Strasbourg 0.09
#8 Le Mans 0.09
#9 Olympique Lyonnais 0.10
#10 Toulouse 0.10
#11 Lille 0.11
#12 Paris Saint-Germain 0.11
#13 Nice 0.12
#14 Olympique de Marseille 0.12
#15 Auxerre 0.13
#16 Stade Rennais 0.13
#17 Troyes 0.15
#18 RC Lens 0.16
League avg
0.11
Total
6.05 npxGA from 76 shots

Shot profile

Shot location

59% inside the box

League avg 65%

From 30 of 51 shots over 5 matches

Early-season figure: after 5 matches, the share can move quickly.

Shots allowed, location

53% allowed inside the box

League avg 65%

From 40 of 76 shots allowed over 5 matches

Early-season figure: after 5 matches, the share can move quickly.

Where the npxG comes from

86% open play · 14% set pieces

League avg 18% set pieces

From 0.8 of 5.9 npxG over 5 matches

Early-season figure: after 5 matches, the share can move quickly.

Where the npxG allowed comes from

69% open play · 31% set pieces

League avg 18% set pieces

From 1.8 of 5.9 npxG allowed over 5 matches

Early-season figure: after 5 matches, the share can move quickly.

How the shot figures are made →

AS Monaco home and away xG

AS Monaco per-match figures at home and away
Measure Home only 2 matches with xG Away
Matches 2 3
xG / match 1.74 0.98
xGA / match 1.30 1.31
xGD / match +0.44 -0.33
xPts / match Model — Model output — computed from each match's xG, not a result. How xPts works → 1.71 1.23

Every figure divides by that half's matches with xG. A half with fewer than 3 matches with xG is muted.

Every AS Monaco match by xG

Window
Season Last 10 Last 5
Venue
All Home Away

This season

Matches
5
xG / match
1.28
xGA / match
1.31
xGD / match
-0.02
Points
13 of 15
  1. Fri 18/09 RC Lens H xG 1.75 xGA 1.19 xGD +0.56
  2. Sat 12/09 RC Strasbourg A xG 1.05 xGA 1.02 xGD +0.03
  3. Fri 04/09 Paris Saint-Germain A Against the chances xG 0.51 xGA 2.32 xGD -1.81
  4. Sun 30/08 Olympique de Marseille H xG 1.72 xGA 1.40 xGD +0.32
  5. Sun 23/08 Le Havre A Best underlying xG 1.39 xGA 0.60 xGD +0.79

Newest first. The dot is xG and the ring is xGA, on one scale from 0 to 3.00. Best and weakest underlying mark the highest and lowest xGD once 5 matches have xG. Against the chances marks a win with xGD of −1.00 or lower, or a loss with +1.00 or higher. P marks a side with at least 0.50 xG from penalties.

Every result, all competitions →

AS Monaco in Ligue 1

Attack

Defence

Overall

About the data

xG data
Provided by TheStatsAPI, and stored as published.
Derived metrics
xGD, per-match rates, rankings and rolling averages are calculated from the match data.
Model metrics
xPts is produced by our probability model.

Learn how our xG analytics work →

How the model works →

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