FC København
FC København are 1st in the Superliga after 9 matches in the 2026/2027 season. They have won 8 matches, scored 23 goals and conceded 8.
They average 2.56 goals per match and have kept a clean sheet in 56% of their league matches.
- Competition
- Superliga (Denmark)
- Season
- 2026/2027
- Position
- 1 of 12Based on completed matches
- Team Strength
- 84.4FootyCabin rating, 0–100
- Founded
- 1992
- Form
- Loss
- Win
- Win
- Win
- Win
- Win
Team intelligence
What stands out
- High Volume / High ConversionMore shots and a higher scoring rate than the league average.
- Limited TerritoryAverage possession, but fewer corners than most teams in the league.
- Clean sheetsClean sheet in 56% of league matches.
- Goals scored2.56 scored per match in league matches.
Season summary
Calculated from completed matches only. Scheduled matches are never counted.
- Matches played
- 9
- Wins
- 8
- Draws
- 0
- Losses
- 1
- Goals scored
- 23
- Goals conceded
- 8
- Goal difference
- +15
- Points
- 24
2.67 per match
Efficiency Rates
Success rates for passing, shooting, dribbling, duels and defending.
| Statistic | Rate |
|---|---|
| Pass accuracy | 95.0% |
| Shots on target rate | 30.5% |
| Dribble success | 42.6% |
| Duel win rate | 43.3% |
| Aerial win rate | 81.7% |
| Tackle success | 67.7% |
0–100% scale
Team performance
Team totals built from recorded player statistics in 9 completed matches.
| Statistic | Total | Per match | Matches with data |
|---|---|---|---|
| Shots | 95 | 11.88 | 8 |
| Shots on target | 29 | 4.14 | 7 |
| Passes | 2,730 | 341.25 | 8 |
| Accurate passes | 2,594 | 324.25 | 8 |
| Passes into the final third | 294 | 32.67 | 9 |
| Key passes | 65 | 8.13 | 8 |
| Chances created | 72 | 9.00 | 8 |
| Successful dribbles | 43 | 7.17 | 6 |
| Tackles | 96 | 12.00 | 8 |
| Interceptions | 40 | 5.00 | 8 |
| Clearances | 133 | 16.63 | 8 |
| Ball recoveries | 294 | 36.75 | 8 |
| Duels | 575 | 71.88 | 8 |
| Duels won | 249 | 31.13 | 8 |
| Aerial duels | 104 | 14.86 | 7 |
| Aerial duels won | 85 | 10.63 | 8 |
| Goalkeeper saves | 9 | 2.25 | 4 |
These are calculated from player data rather than official team totals. A dash or "not available" means no value was recorded. It never means zero.
How this team plays
See how this team's playing style compares with the rest of the league. Higher scores mean the team shows more of that style, not that it is better.
Team style
Attacking Combination
Creates chances and attempts shots at a rate above most league teams.
Style summary: Attack-oriented. A descriptive summary of the profile below, not a rating.
- Possession54
Possession is around the league average. (50.6%, 9 fixtures)
- Attacking output71
Attacking output is above the league average. (15.00 per match, 9 fixtures)
- Chance creation71
Chance creation is above the league average. (11.67 per match, 9 fixtures)
- Defensive activity29
Defensive activity is below the league average. (73.33 per match, 9 fixtures)
- Ball security63
Ball security is above the league average. (84.8%, 9 fixtures)
Scores run from 0 to 100 and compare this team with the 12 teams in the same league and season. Higher means more of that characteristic, not better.
Style context
Shows how this team's playing-style characteristics relate to league performance patterns this season.
This is descriptive context, not evidence that a playing style causes better or worse results.
- Attacking outputTeam score: 71High-attacking output teams: 1.62 points / matchLow-attacking output teams: 1.00 points / match
This team is in the league's high-attacking output group.
High-attacking output teams average 0.62 more points per match than low-attacking output teams.
- Chance creationTeam score: 71High-chance creation teams: 1.62 points / matchLow-chance creation teams: 1.00 points / match
This team is in the league's high-chance creation group.
High-chance creation teams average 0.62 more points per match than low-chance creation teams.
- Ball securityTeam score: 63High-ball security teams: 1.53 points / matchLow-ball security teams: 1.14 points / match
This team sits between the league's high and low ball security groups.
High-ball security teams average 0.39 more points per match than low-ball security teams.
Possession profile
Territory context
Limited Territory
Average possession, but fewer corners than most teams in the league.
- Possession:
- 54 / 100
- Corners:
- 38 / 100
Scores run from 0 to 100 and compare this team with the rest of the league. Higher means more of that characteristic, not better performance.
- Average possession
- 50.6%
- Home
- 52.8%
- Away
- 48.8%
Based on 9 of 9 completed matches.
Recent results
Latest completed matches, newest first.
| Date | Opponent | Venue | Score | Result | Competition |
|---|---|---|---|---|---|
| 20 Sept 2026 | Brøndby IF | Away | 1–0 | Win | Superliga |
| 11 Sept 2026 | Horsens | Home | 2–0 | Win | Superliga |
| 06 Sept 2026 | Odense BK | Away | 5–0 | Win | Superliga |
| 03 Sept 2026 | Nordsjælland | Home | 2–0 | Win | Superliga |
| 31 Aug 2026 | Sønderjyske Fodbold | Home | 3–1 | Win | Superliga |
| 23 Aug 2026 | Viborg FF | Away | 0–4 | Loss | Superliga |
| 16 Aug 2026 | Randers FC | Away | 4–0 | Win | Superliga |
| 02 Aug 2026 | Silkeborg IF | Away | 3–1 | Win | Superliga |
| 26 Jul 2026 | Lyngby Boldklub | Home | 3–2 | Win | Superliga |
Home and away
Home and away records this season.
| Split | P | W | D | L | GF | GA | GD | Pts |
|---|---|---|---|---|---|---|---|---|
| Home | 4 | 4 | 0 | 0 | 10 | 3 | 7 | 12 |
| Away | 5 | 4 | 0 | 1 | 13 | 5 | 8 | 12 |
Attack & defence
How the team has performed in attack and defence across completed league matches this season.
Attack
Defence
Match pattern
Standout players
The team's leading players by FootyCabin Impact Score this season. Players are shown once they have enough match data.
- 2Mohamed ElyounoussiView player
Attacking midfielder
Impact 69.6·Attacking Threat 96.4
Creative Winger
Best category: Attacking Threat
- 3Thomas DelaneyView player
Defensive midfielder
Impact 64.1·Defensive Reliability 96.9
Best category: Defensive Reliability
Squad
Players used this season, ordered by minutes played. Impact Score is shown once a player has enough match data.
| Player | Role | |||||
|---|---|---|---|---|---|---|
| Felix Beijmo | Centre back | 9 | 810 | 1 | 1 | 52.7 |
| Mohamed Elyounoussi | Attacking midfielder | 8 | 703 | 6 | 2 | 69.6 |
| Robert | Winger | 9 | 614 | 1 | 1 | 41.6 |
| William Clem | Defensive midfielder | 9 | 588 | — | 1 | 59.2 |
| Alex Král | Defensive midfielder | 9 | 570 | 1 | 2 | 30.6 |
| Munashe GaranangaMultiple teams | Centre back | 7 | 567 | — | — | 52.3 |
| Marcos López | Full back | 7 | 503 | 1 | 1 | 62.8 |
| Mads Emil Madsen | Defensive midfielder | 7 | 461 | 2 | 1 | 40.0 |
| Asger Sörensen | Centre back | 6 | 452 | 1 | — | 43.9 |
| Diant Ramaj | Goalkeeper | 5 | 450 | — | — | 74.2 |
| Junnosuke Suzuki | Full back | 9 | 447 | — | 2 | 52.1 |
| Birger Meling | Full back | 7 | 407 | 4 | 1 | 54.1 |
| Thomas Delaney | Defensive midfielder | 8 | 405 | — | 1 | 64.1 |
| Gabriel Pereira | Centre back | 5 | 367 | — | — | 53.2 |
| Ákos Markgráf | Centre back | 4 | 360 | — | — | Sample too small |
| Viktor Dadason | Striker | 6 | 320 | 1 | — | Sample too small |
| Andreas Cornelius | Striker | 5 | 250 | 1 | — | Sample too small |
| Dominik Kotarski | Goalkeeper | 3 | 234 | — | — | Sample too small |
| Geovanni Vianney Ndjee | Striker | 6 | 228 | — | — | Sample too small |
| Youssoufa Moukoko | Attacking midfielder | 2 | 180 | — | — | Sample too small |
| Thapelo Maseko | Winger | 4 | 176 | 2 | — | Sample too small |
| Rúnar Alex Rúnarsson | Goalkeeper | 2 | 126 | — | — | Sample too small |
| Marvin Nasnas | Role not established | 7 | 125 | 1 | 1 | Sample too small |
| Jordan Larsson | Winger | 1 | 69 | — | 1 | Sample too small |
| Maher Carrizo | Role not established | 2 | 28 | 1 | — | Sample too small |
| Hunor Németh | Role not established | 1 | 11 | — | — | Sample too small |
Appearances and minutes are from completed matches. Players who have played for more than one club this season are marked.
Squad by role
Players grouped by position. Impact data is shown only when there is enough match data.
Centre back
Full back
Defensive midfielder
- Thomas DelaneyView player
Impact 64.1·Defensive Reliability 96.9
- William ClemView player
Impact 59.2·Ball Security 78.3
- View player
Attacking midfielder
Team impact leaders
The team's highest Impact Scores this season, alongside each player's playing style. Playing style describes how they play, not how good they are. How this is built
- 1Diant RamajGoalkeeperArchetype not available74.2/100
- 2Mohamed ElyounoussiAttacking midfielderCreative Winger69.6/100
- 3Thomas DelaneyDefensive midfielderArchetype not available64.1/100
Squad archetype profile
The most common playing styles in the squad this season.
- Wide Distributor222%
- Aerial Defender111%
- Ball-Playing Defender111%
- Conservative Distributor111%
- Creative Midfielder111%
- Creative Winger111%
- Defensive Full-Back111%
- Inside Forward111%
Based on 9 players with enough data for a playing-style classification.
Player contributions
Team leaders for minutes, goals, assists and Impact Score this season.
Most minutes
All completed fixtures this season.
- 1Felix Beijmo810minutes
- 2Mohamed Elyounoussi703minutes
- 3Robert614minutes
- 4William Clem588minutes
- 5Alex Král570minutes
Most goals
Season totals from imported match data.
- 1Mohamed Elyounoussi6goals
- 2Birger Meling4goals
- 3Mads Emil Madsen2goals
- 4Thapelo Maseko2goals
- 5Felix Beijmo1goals
Most assists
Season totals from imported match data.
- 1Mohamed Elyounoussi2assists
- 2Alex Král2assists
- 3Junnosuke Suzuki2assists
- 4Felix Beijmo1assists
- 5Robert1assists
Highest Impact Score
Only players who meet the publishable sample and coverage rules.
- 1Diant Ramaj74.2/ 100
- 2Mohamed Elyounoussi69.6/ 100
- 3Thomas Delaney64.1/ 100
- 4Marcos López62.8/ 100
- 5William Clem59.2/ 100
Methodology
Data source
Match, lineup, event and player statistics come from Sportmonks and are stored per fixture. Only completed fixtures with recorded minutes are aggregated. Announced lineups and future fixtures are excluded.
Per 90 minutes
A per-90 value scales a season total to a full match: total × 90 ÷ minutes played. It is not calculated when minutes are missing or zero.
Missing data
The provider omits some statistics instead of sending a zero. A missing value is shown as "not available" and never converted to 0, so rates and percentiles are only produced where the underlying fields genuinely exist.
Impact Score
The Football Performance Lab Impact Score is an experimental in-house model that combines role-relative percentile families with explicit weights. It is not an official rating and not a measure of transfer value.
Minimum samples
Values are calculated internally from 180 minutes, but a player is only shown publicly with a ranked Impact Score from 360 minutes and 5 appearances, with at least 90% metric coverage and an established role. A single appearance contributes a match impact observation from 30 minutes.