Nordsjælland lead the Superliga on expected points in 2026/2027, with 12.2 xG created and 5.1 conceded across their matches. Lyngby Boldklub have the biggest gap between results and underlying numbers — 3 points from chances worth 11.1 xPts. The tables here cover 35 matches and sort on every column; the full expected-points table, with qualification and relegation places applied, lives in the xG view on the Table page.
Lyngby Boldklub have the biggest shortfall in the Superliga: 3 points from chances worth 11.1 xPts, a gap of 8.1. At the other end, FC København have taken 15 points from an xPts figure of 8.9, 6.1 more than the underlying numbers justify.
Expected goals measure the quality of the chances a team creates and concedes, with every shot scored between 0 and 1 by how often shots like it are converted. Expected points come from running each finished match through a Poisson model using both sides' xG, giving a win, draw and loss probability, then awarding three points and one point against those probabilities. Underlying data is supplied by Sportmonks.
An xG table ranks clubs by the quality of the chances they create and concede rather than by the goals that happened to go in. Every shot is scored between 0 and 1 by how often shots like it are converted, and those values are summed into expected goals for (Superliga xG) and against (xGA).
Expected points. Each finished match is run through a Poisson model using both sides' xG, which produces a win, draw and loss probability; the team is then awarded three points and one point weighted by those probabilities. Summed across the season it estimates the points a club's performances were worth.
Usually a mix of clinical finishing, good goalkeeping and luck. Finishing skill is real but small and hard to sustain, so a large positive gap between points and xPts more often signals results that will drift back towards the underlying numbers than a permanently better team.
Shot-level data is supplied by Sportmonks and updates after every finished match, typically within a few hours of full-time. Different providers train their xG models on different data, so our figures will not match another site's exactly, though the ranking is generally similar.
| # | Team | Played | xG | xGA | xGD | Points | xPts | Points minus xPts |
|---|---|---|---|---|---|---|---|---|
| 1 | Nordsjælland | 6 | 13.0 | 6.4 | 6.6 | 13 | 12.1 | +0.9 |
| 2 | Lyngby Boldklub | 6 | 13.0 | 7.3 | 5.7 | 3 | 11.1 | -8.1 |
| 3 | FC Midtjylland | 6 | 9.0 | 6.3 | 2.7 | 14 | 9.9 | +4.1 |
| 4 | AGF | 6 | 10.5 | 9.1 | 1.4 | 3 | 9.6 | -6.6 |
| 5 | Viborg FF | 6 | 9.6 | 8.2 | 1.4 | 13 | 9.5 | +3.5 |
| 6 | Odense BK | 6 | 11.1 | 9.5 | 1.6 | 5 | 9.3 | -4.3 |
| 7 | FC København | 6 | 8.2 | 6.9 | 1.3 | 15 | 8.9 | +6.1 |
| 8 | Brøndby IF | 6 | 9.1 | 9.2 | 0.0 | 13 | 8.4 | +4.6 |
| 9 | Silkeborg IF | 6 | 6.2 | 10.3 | -4.1 | 5 | 5.9 | -0.9 |
| 10 | Randers FC | 6 | 5.1 | 9.6 | -4.5 | 7 | 5.4 | +1.6 |
| 11 | Sønderjyske Fodbold | 6 | 5.4 | 10.4 | -5.0 | 1 | 5.3 | -4.3 |
| 12 | Horsens | 6 | 6.1 | 13.2 | -7.1 | 7 | 4.4 | +2.6 |