#TeamPGxG/90+/-
1FC København243747.741.99-10.7
2AGF244746.341.93+0.7
3FC Midtjylland245942.561.77+16.4
4Viborg FF243937.331.56+1.7
5Nordsjælland244036.51.52+3.5
6Odense BK243936.271.51+2.7
7Brøndby IF243136.21.51-5.2
8Sønderjyske Fodbold243535.91.5-0.9
9Randers FC242535.131.46-10.1
10Fredericia243228.671.19+3.3
11Silkeborg IF242827.991.170
12Vejle Boldklub242826.681.11+1.3
#TeamPGAxGA/90+/-
1AGF242427.351.14-3.4
2FC Midtjylland242532.171.34-7.2
3Brøndby IF242332.571.36-9.6
4FC København243833.221.38+4.8
5Odense BK244833.571.4+14.4
6Nordsjælland243933.621.4+5.4
7Randers FC243034.051.42-4.1
8Sønderjyske Fodbold243136.081.5-5.1
9Viborg FF243637.241.55-1.2
10Vejle Boldklub244738.221.59+8.8
11Silkeborg IF244644.031.83+2
12Fredericia245355.192.3-2.2
#TeamPPTSxPTS/90+/-
1AGF245244.361.85+7.6
2FC København242940.211.68-11.2
3FC Midtjylland244739.421.64+7.6
4Brøndby IF243535.371.47-0.4
5Odense BK243135.21.47-4.2
6Nordsjælland243734.971.46+2
7Sønderjyske Fodbold243733.831.41+3.2
8Viborg FF243733.541.4+3.5
9Randers FC242933.421.39-4.4
10Vejle Boldklub241625.781.07-9.8
11Silkeborg IF242323.951-0.9
12Fredericia242720.230.84+6.8
#TeamPxGxGAxGD/90
1AGF2446.3427.3518.990.79
2FC København2447.7433.2214.520.61
3FC Midtjylland2442.5632.1710.390.43
4Brøndby IF2436.232.573.630.15
5Nordsjælland2436.533.622.880.12
6Odense BK2436.2733.572.70.11
7Randers FC2435.1334.051.080.05
8Viborg FF2437.3337.240.090
9Sønderjyske Fodbold2435.936.08-0.18-0.01
10Vejle Boldklub2426.6838.22-11.54-0.48
11Silkeborg IF2427.9944.03-16.04-0.67
12Fredericia2428.6755.19-26.52-1.11
#TeamPGnpxGxG/90
1FC København24374347.741.99
2FC Midtjylland245940.9842.561.77
3AGF244740.0246.341.93
4Nordsjælland244034.9236.51.52
5Brøndby IF243134.6236.21.51
6Viborg FF243934.1737.331.56
7Randers FC242532.7635.131.46
8Sønderjyske Fodbold243532.7435.91.5
9Odense BK243932.3236.271.51
10Fredericia243227.8828.671.19
11Silkeborg IF242825.6227.991.17
12Vejle Boldklub242825.126.681.11
#TeamPGxGoTxG/90
1AGF244752.346.341.93
2FC Midtjylland245949.7442.561.77
3Nordsjælland244045.1536.51.52
4FC København243744.7147.741.99
5Odense BK243940.8536.271.51
6Viborg FF243939.7737.331.56
7Sønderjyske Fodbold243536.4535.91.5
8Brøndby IF243136.3536.21.51
9Vejle Boldklub242832.8726.681.11
10Fredericia243230.7628.671.19
11Silkeborg IF242830.4727.991.17
12Randers FC242528.7935.131.46
Upcoming Fixtures (Next 14 Days)
Show xG:

Showing home xG for home teams, away xG for away teams Showing overall xG for all teams

No upcoming fixtures available.

Recent Results with xG
xG
Sun, Mar 22
xG
1.05
Viborg FF
1 - 1
FC Midtjylland
1.47
0.74
AGF
0 - 0
Brøndby IF
0.64
4.98
FC København
1 - 2
Fredericia
1.01
1.57
Nordsjælland
2 - 0
Sønderjyske Fodbold
0.94
1.05
Randers FC
0 - 3
Silkeborg IF
1.14
xG
Fri, Mar 20
xG
0.51
Vejle Boldklub
1 - 1
Odense BK
1.34
xG
Mon, Mar 16
xG
1.95
Silkeborg IF
1 - 1
Vejle Boldklub
1.06
xG
Sun, Mar 15
xG
0.9
Brøndby IF
0 - 1
Viborg FF
3.04
1.38
Sønderjyske Fodbold
1 - 1
AGF
1.85
0.92
FC Midtjylland
0 - 1
Nordsjælland
0.73
1.76
Odense BK
2 - 1
FC København
1.03
xG
Fri, Mar 13
xG
0.79
Fredericia
0 - 3
Randers FC
1.31
xG
Sun, Mar 1
xG
2.05
Viborg FF
2 - 1
Nordsjælland
1.32
1.38
FC Midtjylland
0 - 0
Brøndby IF
0.71
1.78
Fredericia
2 - 1
Silkeborg IF
0.98
2.77
FC København
1 - 2
Randers FC
2.08
1.37
Sønderjyske Fodbold
1 - 0
Odense BK
0.73
1.06
Vejle Boldklub
1 - 2
AGF
1.64
xG
Mon, Feb 23
xG
0.84
Brøndby IF
0 - 0
Sønderjyske Fodbold
1.69
xG
Sun, Feb 22
xG
1.86
AGF
5 - 2
Viborg FF
1.18
0.82
Silkeborg IF
0 - 4
FC Midtjylland
1.86
2.53
Randers FC
1 - 2
Fredericia
1.96
xG
Sat, Feb 21
xG
2.27
Odense BK
2 - 2
FC København
2.2
xG
Fri, Feb 20
xG
1.56
Nordsjælland
3 - 3
Vejle Boldklub
1.32
xG
Mon, Feb 16
xG
2.22
Sønderjyske Fodbold
2 - 1
Silkeborg IF
0.7
xG
Sun, Feb 15
xG
1.15
Viborg FF
1 - 0
Brøndby IF
0.65
2.17
Odense BK
1 - 4
FC Midtjylland
3.46
0.96
Fredericia
1 - 1
AGF
2.42
xG
Sat, Feb 14
xG
1.31
FC København
1 - 2
Nordsjælland
2.21
xG
Fri, Feb 13
xG
1.38
Randers FC
2 - 0
Vejle Boldklub
1.44
xG
Mon, Feb 9
xG
2.13
AGF
2 - 1
Odense BK
0.47
3.18
Vejle Boldklub
2 - 3
Fredericia
2.25
xG
Sun, Feb 8
xG
1.36
Brøndby IF
0 - 0
Randers FC
1.06
2.1
FC Midtjylland
2 - 1
FC København
1.6
1.38
Nordsjælland
2 - 1
Sønderjyske Fodbold
1.13
0.77
Silkeborg IF
0 - 1
Viborg FF
1.98
xG
Mon, Dec 8
xG
1.57
Vejle Boldklub
2 - 1
Brøndby IF
1.59
xG
Sun, Dec 7
xG
2.19
FC København
0 - 2
Sønderjyske Fodbold
1.47
1.66
Randers FC
1 - 2
AGF
0.89
1.09
Viborg FF
3 - 3
FC Midtjylland
1.73
3.28
Nordsjælland
5 - 0
Silkeborg IF
1.32
xG
Fri, Dec 5
xG
0.91
Fredericia
1 - 3
Odense BK
2.1
xG
Mon, Dec 1
xG
2.21
Brøndby IF
1 - 3
Fredericia
1.38
xG
Sun, Nov 30
xG
2.21
Odense BK
3 - 0
Vejle Boldklub
0.85
2.65
FC Midtjylland
6 - 0
Nordsjælland
0.32
1.04
AGF
2 - 0
FC København
1.15
1.21
Silkeborg IF
0 - 0
Randers FC
0.94
xG
Fri, Nov 28
xG
1.37
Sønderjyske Fodbold
2 - 2
Viborg FF
2.64
xG
Mon, Nov 24
xG
1.42
Randers FC
0 - 0
Odense BK
1.63
xG
Sun, Nov 23
xG
1.92
Sønderjyske Fodbold
2 - 1
FC Midtjylland
0.65

Download This Data as CSV

Get full access to xG, xGA, xPTS, and 30+ metrics for every team. Export to CSV and power your own analysis.

50+ Leagues 30+ Metrics Updated Daily

Superliga xG Table 2025/26

The Superliga xG table for 2025/26 tracks expected goals data for all 12 teams. This includes xG (expected goals), xGA (expected goals against), xPTS (expected points), npxG (non-penalty xG), xGoT (expected goals on target), and the goals vs xG overperformance metric.

Who has the best attack?

FC København top the xG charts with 47.74 expected goals from 24 games (1.99/90). With 37 goals scored, they are underperforming by 10.7.

Who has the best defence?

AGF have the tightest defence by xGA, conceding just 27.35 expected goals (1.14/90). Their actual goals conceded stands at 24.

Biggest overperformer

FC Midtjylland are the biggest overperformers in Superliga, scoring 59 goals from an xG of just 42.56 — a difference of +16.4. This could indicate clinical finishing or luck that may not be sustainable over the full season.

Biggest underperformer

FC København are the most wasteful in front of goal, scoring 37 from an xG of 47.74 (diff: -10.7). Regression towards their xG would suggest improvement is likely.

Understanding the xG metrics

  • xG (Expected Goals): The total expected goals a team should have scored based on the quality of their chances.
  • xGA (Expected Goals Against): How many goals a team should have conceded — lower is better.
  • xPTS (Expected Points): How many league points a team deserves based on xG performance.
  • npxG (Non-Penalty xG): xG excluding penalties, giving a truer picture of open-play chance creation.
  • xGoT (xG on Target): Expected goals from shots that were on target only.
  • +/- (Overperformance): The difference between actual goals and xG. Positive = overperforming, negative = underperforming.

Data is updated daily, powered by advanced xG models covering 50+ competitions. Learn more about how xG works.

Data last updated: 2026-04-03 19:06:03