xgEdge

Expected goals

AGF expected goals (xG) 2026/2027

Superliga (Denmark) · after 9 matches · updated 1 Oct

AGF's attacking and defensive expected goals in Superliga (Denmark) 2026/2027, compared with the results they produced and with the rest of the competition.

AGF xG and xGA per match

Every match ↓
Attack
1.60 xG per match
=4/12
Attack (xG per match) across Superliga (Denmark), best first
Rank Club xG per match
#1 FC Nordsjælland 2.35
#2 Lyngby 1.85
#3 FC København 1.62
=4 AGF 1.60
=4 Viborg FF 1.60
#6 Odense Boldklub 1.55
#7 FC Midtjylland 1.44
#8 Brøndby IF 1.22
#9 Silkeborg IF 1.10
#10 AC Horsens 1.09
#11 Randers FC 1.06
#12 Sønderjyske Fodbold 1.01
League avg
1.46
Total
14.43 9 matches
Defence
1.56 xGA per match
#8/12
Defence (xGA per match) across Superliga (Denmark), best first
Rank Club xGA per match
#1 FC Midtjylland 1.11
#2 FC København 1.16
#3 Viborg FF 1.17
#4 Lyngby 1.36
#5 FC Nordsjælland 1.43
#6 Silkeborg IF 1.47
#7 Brøndby IF 1.54
#8 AGF 1.56
#9 AC Horsens 1.57
#10 Randers FC 1.65
#11 Odense Boldklub 1.68
#12 Sønderjyske Fodbold 1.81
League avg
1.46
Total
14.04 9 matches
xG difference
+0.04 xGD per match
#6/12
xG difference (xGD per match) across Superliga (Denmark), best first
Rank Club xGD per match
#1 FC Nordsjælland +0.93
#2 Lyngby +0.48
#3 FC København +0.46
#4 Viborg FF +0.43
#5 FC Midtjylland +0.33
#6 AGF +0.04
#7 Odense Boldklub -0.13
#8 Brøndby IF -0.32
#9 Silkeborg IF -0.36
#10 AC Horsens -0.48
#11 Randers FC -0.59
#12 Sønderjyske Fodbold -0.80
League avg
0.00
Total
+0.39 9 matches
Expected points Model — Model output — computed from each match's xG, not a result. How xPts works →
1.49 xPts per match
#6/12
Expected points (xPts per match) across Superliga (Denmark), best first
Rank Club xPts per match
#1 FC Nordsjælland 1.90
#2 FC København 1.71
#3 Viborg FF 1.70
#4 FC Midtjylland 1.61
#5 Lyngby 1.61
#6 AGF 1.49
#7 Odense Boldklub 1.30
#8 Silkeborg IF 1.22
#9 Brøndby IF 1.18
#10 AC Horsens 1.05
#11 Randers FC 0.99
#12 Sønderjyske Fodbold 0.82
League avg
1.38
Total
13.37 vs 5 actual pts

Early-season figures: after 9 matches, per-match rates can move quickly.

What the xG says

AGF's underlying numbers sit close to the Superliga (Denmark) average. They rank #6 for xG difference at +0.04 per match, built on elite shot volume rather than low chance quality. Their 11 goals are 3.43 below 14.43 xG, while 5 points are 8.37 below 13.37 xPts. After only 9 matches, those gaps should still be read cautiously.

Actual vs expected

Measure Actual Expected Difference Reading
Goals vs xG Includes 2.08 xG from penalties
11 14.43 -3.43 scored 3.43 fewer than xG within normal variance
Goals conceded vs xGA
17 14.04 +2.96 conceded 2.96 more than xGA within normal variance
Points vs xPts Model — Model output — computed from each match's xG, not a result. How xPts works →
5 13.37 -8.37 8.37 points below xPts far outside normal variance

Select a row to chart it across the season.

Goals minus xG, match by match

AGF are 3.43 goals below their xG after 9 matches. The gap was widest at -4.42, against FC Nordsjælland on Sun 13/09.

Goals
11
xG
14.43
Gap
-3.43
Sat 25/07 Sat 01/08 Fri 14/08 Sun 23/08 Sun 30/08 Wed 02/09 Sat 05/09 Sun 13/09 Sun 20/09 -5 -4 -3 -2 -1 0 +1 -0.91 -0.26 -1.18 -1.06 -2.03 -3.24 -3.16 -4.42 -3.43 -0.91 +0.65 -0.92 +0.12 -0.97 -1.21 +0.08 -1.26 +0.99 Running gap goals − xG Each match goals − xG
AGF: Goals vs xG, the gap after every match with xG
Date Opponent Goals xG Match gap Running gap
Sat 25/07 Brøndby IF 1 1.91 -0.91 -0.91
Sat 01/08 Lyngby 2 1.35 +0.65 -0.26
Fri 14/08 Viborg FF 1 1.92 -0.92 -1.18
Sun 23/08 Odense Boldklub 2 1.88 +0.12 -1.06
Sun 30/08 Randers FC 1 1.97 -0.97 -2.03
Wed 02/09 FC Midtjylland 0 1.21 -1.21 -3.24
Sat 05/09 Silkeborg IF 2 1.92 +0.08 -3.16
Sun 13/09 FC Nordsjælland 0 1.26 -1.26 -4.42
Sun 20/09 AC Horsens 2 1.01 +0.99 -3.43

Goals vs xG ranking → Expected points ranking → Compare with every club in Europe →

AGF xG trend

Current form +0.35 npxGD per match

The last 6 matches with xG.

Out-created the opponent in 4 of 9 matches. The worst was against Lyngby on Sat 01/08 (-1.50).

npxG · last 6
1.50
npxGA · last 6
1.14
-2 -1 0 +1 +2 -0.09 Sat 25/07 -1.50 Sat 01/08 +1.06 Fri 14/08 +1.07 Sun 23/08 +0.85 Sun 30/08 -0.32 Wed 02/09 +1.71 Sat 05/09 -1.13 Sun 13/09 -0.06 Sun 20/09 +0.18 season avg
AGF: 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
Sat 25/07 Brøndby IF 0.83 0.92 -0.09 -0.09
Sat 01/08 Lyngby 0.64 2.14 -1.50 -0.80
Fri 14/08 Viborg FF 1.90 0.84 +1.06 -0.18
Sun 23/08 Odense Boldklub 1.88 0.81 +1.07 +0.14
Sun 30/08 Randers FC 1.69 0.84 +0.85 +0.28
Wed 02/09 FC Midtjylland 1.08 1.40 -0.32 +0.18
Sat 05/09 Silkeborg IF 2.09 0.38 +1.71 +0.40
Sun 13/09 FC Nordsjælland 1.29 2.42 -1.13 +0.21
Sun 20/09 AC Horsens 0.95 1.01 -0.06 +0.18

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 — 1.37 npxG and 1.20 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 7 hardest of 12 in Superliga (Denmark)
−0.01 xG vs league average
Over 9 league matches
Last 5
tied number 10 hardest of 12 in Superliga (Denmark)
−0.06 xG vs league average
Over 5 league matches
Opponents behind the figures

Season so far

−0.01 xG vs league average · over 9 matches · number 7 hardest of 12

  1. AC Horsens Away −0.22
  2. FC Nordsjælland Away +0.41
  3. Silkeborg IF Home −0.30
  4. FC Midtjylland Home +0.09
  5. Randers FC Away −0.27
  6. Odense Boldklub Home −0.04
  7. Viborg FF Away +0.16
  8. Lyngby Away 0.00
  9. Brøndby IF Home +0.05

Last 5

−0.06 xG vs league average · over 5 matches · tied number 10 hardest of 12

  1. AC Horsens Away −0.22
  2. FC Nordsjælland Away +0.41
  3. Silkeborg IF Home −0.30
  4. FC Midtjylland Home +0.09
  5. Randers FC Away −0.27

League schedule strength → How this is calculated →

AGF shots and chance quality

High volume, low quality. AGF take 16.8 shots a match (league 13.9) at 0.08 npxG a shot (league 0.10), #2 in Superliga (Denmark) for volume and #10 for quality. 66% of their shots come from inside the box (league 64%), and set pieces produce 23% of their npxG (league 25%).

Attack

Shot volume
16.8 shots per match
#2/12
Shot volume (shots per match) across Superliga (Denmark), best first
Rank Club shots per match
#1 FC Nordsjælland 17.6
#2 AGF 16.8
#3 Odense Boldklub 15.3
#4 Brøndby IF 15.2
#5 FC København 15.0
#6 Lyngby 14.8
#7 FC Midtjylland 14.2
#8 Viborg FF 13.6
#9 Sønderjyske Fodbold 11.6
#10 Silkeborg IF 11.4
#11 AC Horsens 11.2
#12 Randers FC 9.9
League avg
13.9
Total
151 shots from 9 matches
Chance quality
0.08 npxG per shot
#10/12
Chance quality (npxG per shot) across Superliga (Denmark), best first
Rank Club npxG per shot
#1 FC Nordsjælland 0.13
#2 Viborg FF 0.12
#3 Randers FC 0.10
#4 FC København 0.10
#5 Lyngby 0.10
#6 FC Midtjylland 0.10
#7 Odense Boldklub 0.09
#8 AC Horsens 0.08
#9 Silkeborg IF 0.08
#10 AGF 0.08
#11 Sønderjyske Fodbold 0.08
#12 Brøndby IF 0.08
League avg
0.10
Total
12.35 npxG from 151 shots

Defence

Shots allowed
13.7 shots per match
=8/12
Shots allowed (shots per match) across Superliga (Denmark), best first
Rank Club shots per match
#1 FC København 11.9
#2 Silkeborg IF 12.4
#3 Brøndby IF 12.6
=4 FC Midtjylland 12.9
=4 Lyngby 12.9
#6 FC Nordsjælland 13.3
#7 Odense Boldklub 13.6
=8 AGF 13.7
=8 Viborg FF 13.7
#10 AC Horsens 15.0
#11 Randers FC 16.4
#12 Sønderjyske Fodbold 18.2
League avg
13.9
Total
123 shots allowed from 9 matches
Chance quality allowed
0.09 npxGA per shot
#3/12
Chance quality allowed (npxGA per shot) across Superliga (Denmark), best first
Rank Club npxGA per shot
#1 Viborg FF 0.08
#2 FC Midtjylland 0.08
#3 AGF 0.09
#4 FC Nordsjælland 0.09
#5 FC København 0.09
#6 Randers FC 0.09
#7 Lyngby 0.10
#8 Sønderjyske Fodbold 0.10
#9 AC Horsens 0.10
#10 Brøndby IF 0.11
#11 Odense Boldklub 0.11
#12 Silkeborg IF 0.12
League avg
0.10
Total
10.76 npxGA from 123 shots

Shot profile

Shot location

66% inside the box

League avg 64%

From 99 of 151 shots over 9 matches

Early-season figure: after 9 matches, the share can move quickly.

Shots allowed, location

64% allowed inside the box

League avg 64%

From 79 of 123 shots allowed over 9 matches

Early-season figure: after 9 matches, the share can move quickly.

Where the npxG comes from

77% open play · 23% set pieces

League avg 25% set pieces

From 2.8 of 12.3 npxG over 9 matches

Early-season figure: after 9 matches, the share can move quickly.

Where the npxG allowed comes from

79% open play · 21% set pieces

League avg 25% set pieces

From 2.3 of 10.7 npxG allowed over 9 matches

Early-season figure: after 9 matches, the share can move quickly.

How the shot figures are made →

AGF home and away xG

AGF per-match figures at home and away
Measure Home Away
Matches 4 5
xG / match 1.73 1.50
xGA / match 1.14 1.90
xGD / match +0.59 -0.39
xPts / match Model — Model output — computed from each match's xG, not a result. How xPts works → 1.82 1.22

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

Every AGF match by xG

Window
Season Last 10 Last 5
Venue
All Home Away

Away this season

Matches
5
xG / match
1.50
xGA / match
1.90
xGD / match
-0.39
Points
2 of 15
  1. Sun 20/09 AC Horsens A xG 1.01 xGA 1.19 xGD -0.18
  2. Sun 13/09 FC Nordsjælland A xG 1.26 xGA 2.79 xGD -1.53
  3. Sun 30/08 Randers FC A xG 1.97 xGA 1.10 xGD +0.87
  4. Fri 14/08 Viborg FF A Best underlying xG 1.92 xGA 1.03 xGD +0.89
  5. Sat 01/08 Lyngby A Weakest underlying xG 1.35 P xGA 3.37 P xGD -2.02

Newest first. The dot is xG and the ring is xGA, on one scale from 0 to 3.37. 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 →

AGF in Superliga (Denmark)

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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