Brøndby IF
Brøndby IF are 5th in the Superliga after 10 matches in the 2026/2027 season. They have won 5 matches, scored 17 goals and conceded 17.
They average 1.70 goals per match and have kept a clean sheet in 20% of their league matches.
- Competition
- Superliga (Denmark)
- Season
- 2026/2027
- Position
- 5 of 12Based on completed matches
- Team Strength
- 52.0FootyCabin rating, 0–100
- Founded
- 1964
- Form
- Win
- Loss
- Loss
- Loss
- Loss
- Win
Team intelligence
What stands out
- High Volume / Average ConversionMore shots than the league average, with an average scoring rate.
- Possession & TerritoryMore possession and more corners than most teams in the league.
- Both teams scoredBoth teams scored in 60% of league matches.
Season summary
Calculated from completed matches only. Scheduled matches are never counted.
- Matches played
- 10
- Wins
- 5
- Draws
- 1
- Losses
- 4
- Goals scored
- 17
- Goals conceded
- 17
- Goal difference
- 0
- Points
- 16
1.60 per match
Efficiency Rates
Success rates for passing, shooting, dribbling, duels and defending.
| Statistic | Rate |
|---|---|
| Pass accuracy | 93.4% |
| Shots on target rate | 19.6% |
| Dribble success | 50.5% |
| Duel win rate | 48.1% |
| Aerial win rate | 81.7% |
| Tackle success | 53.1% |
0–100% scale
Team performance
Team totals built from recorded player statistics in 10 completed matches.
| Statistic | Total | Per match | Matches with data |
|---|---|---|---|
| Shots | 102 | 10.20 | 10 |
| Shots on target | 20 | 2.86 | 7 |
| Passes | 2,791 | 279.10 | 10 |
| Accurate passes | 2,606 | 289.56 | 9 |
| Passes into the final third | 355 | 39.44 | 9 |
| Key passes | 65 | 8.13 | 8 |
| Chances created | 70 | 7.00 | 10 |
| Successful dribbles | 51 | 6.38 | 8 |
| Tackles | 98 | 9.80 | 10 |
| Interceptions | 81 | 9.00 | 9 |
| Clearances | 140 | 15.56 | 9 |
| Ball recoveries | 265 | 29.44 | 9 |
| Duels | 601 | 66.78 | 9 |
| Duels won | 289 | 32.11 | 9 |
| Aerial duels | 93 | 15.50 | 6 |
| Aerial duels won | 76 | 8.44 | 9 |
| Goalkeeper saves | 21 | 3.00 | 7 |
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
Possession & Creation
Keeps the ball more than most league teams and turns that possession into chances.
Style summary: Possession & Attack. A descriptive summary of the profile below, not a rating.
- Possession79
Possession is above the league average. (54.2%, 10 fixtures)
- Attacking output79
Attacking output is above the league average. (15.10 per match, 10 fixtures)
- Chance creation88
Chance creation is well above the league average. (12.00 per match, 10 fixtures)
- Defensive activity83
Defensive activity is well above the league average. (80.00 per match, 10 fixtures)
- Ball security71
Ball security is above the league average. (84.7%, 10 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: 79High-attacking output teams: 1.65 points / matchLow-attacking output teams: 0.95 points / match
This team is in the league's high-attacking output group.
High-attacking output teams average 0.70 more points per match than low-attacking output teams.
- Chance creationTeam score: 88High-chance creation teams: 1.65 points / matchLow-chance creation teams: 0.95 points / match
This team is in the league's high-chance creation group.
High-chance creation teams average 0.70 more points per match than low-chance creation teams.
- Ball securityTeam score: 71High-ball security teams: 1.60 points / matchLow-ball security teams: 1.10 points / match
This team is in the league's high-ball security group.
High-ball security teams average 0.50 more points per match than low-ball security teams.
Possession profile
Territory context
Possession & Territory
More possession and more corners than most teams in the league.
- Possession:
- 79 / 100
- Corners:
- 79 / 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
- 54.2%
- Home
- 55.5%
- Away
- 52.3%
Based on 10 of 10 completed matches.
Recent results
Latest completed matches, newest first.
| Date | Opponent | Venue | Score | Result | Competition |
|---|---|---|---|---|---|
| 11 Oct 2026 | Lyngby Boldklub | Home | 5–2 | Win | Superliga |
| 20 Sept 2026 | FC København | Home | 0–1 | Loss | Superliga |
| 14 Sept 2026 | FC Midtjylland | Away | 1–4 | Loss | Superliga |
| 06 Sept 2026 | Randers FC | Home | 0–3 | Loss | Superliga |
| 30 Aug 2026 | Nordsjælland | Away | 1–3 | Loss | Superliga |
| 24 Aug 2026 | Silkeborg IF | Home | 3–1 | Win | Superliga |
| 17 Aug 2026 | Sønderjyske Fodbold | Home | 3–2 | Win | Superliga |
| 09 Aug 2026 | Horsens | Away | 2–0 | Win | Superliga |
| 02 Aug 2026 | Viborg FF | Home | 1–0 | Win | Superliga |
| 25 Jul 2026 | AGF | Away | 1–1 | Draw | Superliga |
Home and away
Home and away records this season.
| Split | P | W | D | L | GF | GA | GD | Pts |
|---|---|---|---|---|---|---|---|---|
| Home | 6 | 4 | 0 | 2 | 12 | 9 | 3 | 12 |
| Away | 4 | 1 | 1 | 2 | 5 | 8 | -3 | 4 |
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.
- 1Bartosz SliszView player
Defensive midfielder
Impact 70.7·Defensive Activity 91.9
Possession Midfielder
Best category: Defensive Activity
Squad
Players used this season, ordered by minutes played. Impact Score is shown once a player has enough match data.
| Player | Role | |||||
|---|---|---|---|---|---|---|
| Mads Frøkjaer-Jensen | Attacking midfielder | 10 | 856 | 2 | 1 | 46.9 |
| Luis Binks | Centre back | 9 | 810 | 1 | 2 | 65.5 |
| Patrick Pentz | Goalkeeper | 9 | 810 | — | — | 60.8 |
| Bartosz Slisz | Defensive midfielder | 9 | 809 | 1 | 1 | 70.7 |
| Oliver Villadsen | Full back | 10 | 807 | — | — | 66.2 |
| Max Isaac Ejdum | Defensive midfielder | 10 | 780 | 2 | 2 | 57.4 |
| Casper WintherMultiple teams | Central midfielder | 9 | 667 | 1 | — | 50.0 |
| Jordi Vanlerberghe | Centre back | 8 | 638 | 1 | — | 57.3 |
| Marcus Younis | Winger | 10 | 634 | 1 | 2 | 47.4 |
| Olti HyseniMultiple teams | Winger | 10 | 520 | 4 | 3 | 55.0 |
| Marko Divkovic | Full back | 7 | 466 | — | 2 | 63.8 |
| Filip Bundgaard Kristensen | Winger | 9 | 450 | — | — | 33.4 |
| Mats Köhlert | Full back | 7 | 439 | — | 1 | 53.4 |
| Oskar Fenger | Striker | 9 | 362 | 2 | 1 | 31.2 |
| Sho Fukuda | Winger | 8 | 327 | — | 2 | Sample too small |
| Frederik Alves | Centre back | 5 | 270 | — | — | Sample too small |
| Patrick Mortensen | Striker | 7 | 269 | 1 | — | Sample too small |
| Jacob Brøchner Ambæk | Striker | 6 | 206 | 2 | — | Sample too small |
| Raphael Canut | Centre back | 3 | 116 | — | — | Sample too small |
| William Sonne-Schmidt | Goalkeeper | 1 | 90 | — | — | Sample too small |
| Mathias Jensen | Role not established | 2 | 69 | — | — | Sample too small |
| Daniel Wass | Role not established | 6 | 58 | — | — | Sample too small |
| Christopher Charl Olivier | Role not established | 3 | 54 | — | — | 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.
Goalkeeper
Goalkeeper
Centre back
- View player
- Jordi VanlerbergheView player
Impact 57.3·Defensive Activity 96.6
Full back
- Oliver VilladsenView player
Impact 66.2·Defensive Activity 81.3
- View player
- View player
Defensive midfielder
Central midfielder
Attacking midfielder
- Mads Frøkjaer-JensenView player
Impact 46.9·Attacking Threat 87.5
Winger
- View player
- Marcus YounisView player
Impact 47.4·Ball Security 55.4
- View player
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
- 1Bartosz SliszDefensive midfielderPossession Midfielder70.7/100
- 2Oliver VilladsenFull backArchetype not available66.2/100
- 3Luis BinksCentre backAerial Defender65.5/100
Squad archetype profile
The most common playing styles in the squad this season.
- Aerial Defender111%
- Attacking Full-Back111%
- Box-to-Box Midfielder111%
- Creative Midfielder111%
- Direct Winger111%
- Distribution-Focused Goalkeeper111%
- Inside Forward111%
- Possession Midfielder111%
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.
- 1Mads Frøkjaer-Jensen856minutes
- 2Luis Binks810minutes
- 3Patrick Pentz810minutes
- 4Bartosz Slisz809minutes
- 5Oliver Villadsen807minutes
Most goals
Season totals from imported match data.
- 1Olti Hyseni4goals
- 2Mads Frøkjaer-Jensen2goals
- 3Max Isaac Ejdum2goals
- 4Oskar Fenger2goals
- 5Jacob Brøchner Ambæk2goals
Most assists
Season totals from imported match data.
- 1Olti Hyseni3assists
- 2Luis Binks2assists
- 3Max Isaac Ejdum2assists
- 4Marcus Younis2assists
- 5Marko Divkovic2assists
Highest Impact Score
Only players who meet the publishable sample and coverage rules.
- 1Bartosz Slisz70.7/ 100
- 2Oliver Villadsen66.2/ 100
- 3Luis Binks65.5/ 100
- 4Marko Divkovic63.8/ 100
- 5Patrick Pentz60.8/ 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.