Hibernian
Hibernian are 10th in the Premiership after 8 matches in the 2026/2027 season. They have won 2 matches, scored 8 goals and conceded 12.
They average 1.00 goals per match and have kept a clean sheet in 0% of their league matches.
- Competition
- Premiership (Scotland)
- Season
- 2026/2027
- Position
- 10 of 12Based on completed matches
- Team Strength
- 34.2FootyCabin rating, 0–100
- Founded
- 1875
- Form
- Win
- Loss
- Loss
- Loss
- Draw
- Loss
Team intelligence
What stands out
- High Volume / Low ConversionMore shots than the league average, but a lower scoring rate.
- Possession & TerritoryMore possession and more corners than most teams in the league.
- Both teams scoredBoth teams scored in 75% of league matches.
Season summary
Calculated from completed matches only. Scheduled matches are never counted.
- Matches played
- 8
- Wins
- 2
- Draws
- 1
- Losses
- 5
- Goals scored
- 8
- Goals conceded
- 12
- Goal difference
- -4
- Points
- 7
0.88 per match
Efficiency Rates
Success rates for passing, shooting, dribbling, duels and defending.
| Statistic | Rate |
|---|---|
| Pass accuracy | 77.8% |
| Shots on target rate | 25.0% |
| Dribble success | 58.5% |
| Duel win rate | 50.2% |
| Aerial win rate | 80.7% |
| Tackle success | 56.9% |
0–100% scale
Team performance
Team totals built from recorded player statistics in 8 completed matches.
| Statistic | Total | Per match | Matches with data |
|---|---|---|---|
| Shots | 96 | 13.71 | 7 |
| Shots on target | 24 | 3.43 | 7 |
| Passes | 3,014 | 376.75 | 8 |
| Accurate passes | 2,346 | 293.25 | 8 |
| Passes into the final third | 387 | 55.29 | 7 |
| Key passes | 67 | 9.57 | 7 |
| Chances created | 68 | 9.71 | 7 |
| Successful dribbles | 38 | 5.43 | 7 |
| Tackles | 109 | 15.57 | 7 |
| Interceptions | 51 | 7.29 | 7 |
| Clearances | 138 | 19.71 | 7 |
| Ball recoveries | 233 | 33.29 | 7 |
| Duels | 640 | 80.00 | 8 |
| Duels won | 321 | 40.13 | 8 |
| Aerial duels | 135 | 19.29 | 7 |
| Aerial duels won | 109 | 15.57 | 7 |
| Goalkeeper saves | 24 | 3.43 | 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.
- Possession63
Possession is above the league average. (50.6%, 8 fixtures)
- Attacking output71
Attacking output is above the league average. (16.63 per match, 8 fixtures)
- Chance creation63
Chance creation is above the league average. (12.00 per match, 8 fixtures)
- Defensive activity21
Defensive activity is below the league average. (68.38 per match, 8 fixtures)
- Ball security79
Ball security is above the league average. (82.0%, 8 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: 1.97 points / matchLow-attacking output teams: 0.92 points / match
This team is in the league's high-attacking output group.
High-attacking output teams average 1.05 more points per match than low-attacking output teams.
- Chance creationTeam score: 63High-chance creation teams: 2.10 points / matchLow-chance creation teams: 1.14 points / match
This team sits between the league's high and low chance creation groups.
High-chance creation teams average 0.96 more points per match than low-chance creation teams.
- PossessionTeam score: 63High-possession teams: 2.00 points / matchLow-possession teams: 1.04 points / match
This team sits between the league's high and low possession groups.
High-possession teams average 0.96 more points per match than low-possession teams.
Possession profile
Territory context
Possession & Territory
More possession and more corners than most teams in the league.
- Possession:
- 63 / 100
- Corners:
- 71 / 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
- 52.5%
- Away
- 48.8%
Based on 8 of 8 completed matches.
Recent results
Latest completed matches, newest first.
| Date | Opponent | Venue | Score | Result | Competition |
|---|---|---|---|---|---|
| 10 Oct 2026 | Dundee United | Away | 0–1 | Loss | Premiership |
| 19 Sept 2026 | Aberdeen | Home | 1–1 | Draw | Premiership |
| 15 Sept 2026 | Kilmarnock | Home | 0–1 | Loss | Premiership |
| 06 Sept 2026 | St. Johnstone | Away | 1–2 | Loss | Premiership |
| 03 Sept 2026 | Hearts | Home | 1–3 | Loss | Premiership |
| 30 Aug 2026 | Dundee | Away | 2–1 | Win | Premiership |
| 09 Aug 2026 | Rangers | Away | 2–1 | Win | Premiership |
| 02 Aug 2026 | Motherwell | Home | 1–2 | Loss | Premiership |
Home and away
Home and away records this season.
| Split | P | W | D | L | GF | GA | GD | Pts |
|---|---|---|---|---|---|---|---|---|
| Home | 4 | 0 | 1 | 3 | 3 | 7 | -4 | 1 |
| Away | 4 | 2 | 0 | 2 | 5 | 5 | 0 | 6 |
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.
Squad
Players used this season, ordered by minutes played. Impact Score is shown once a player has enough match data.
| Player | Role | |||||
|---|---|---|---|---|---|---|
| Jason Kerr | Centre back | 8 | 720 | — | — | 60.5 |
| Raphael Sallinger | Goalkeeper | 8 | 720 | — | — | 49.2 |
| Josh Mulligan | Defensive midfielder | 8 | 705 | — | 1 | 39.9 |
| Felix Passlack | Full back | 8 | 644 | — | 1 | 45.3 |
| Miguel Chaiwa | Defensive midfielder | 8 | 496 | — | 1 | 38.4 |
| Adam Mayor | Winger | 6 | 464 | 1 | — | 39.2 |
| Nathan Lowe | Striker | 8 | 436 | 1 | 1 | 49.7 |
| Martin Boyle | Winger | 7 | 415 | 3 | — | 42.2 |
| Grant Hanley | Centre back | 5 | 413 | — | 1 | 73.5 |
| Callum Wright | Attacking midfielder | 7 | 411 | 2 | — | 47.1 |
| Jamie McGrath | Winger | 4 | 303 | — | — | Sample too small |
| Jordan Obita | Full back | 4 | 299 | — | — | Sample too small |
| Jack Iredale | Centre back | 4 | 291 | — | — | Sample too small |
| Ante Suto | Striker | 8 | 272 | — | — | Sample too small |
| Jacob Devaney | Defensive midfielder | 5 | 262 | — | — | Sample too small |
| Owen Elding | Winger | 5 | 254 | — | — | Sample too small |
| Thibault Klidjé | Striker | 6 | 212 | — | — | Sample too small |
| Josh CampbellMultiple teams | Winger | 3 | 186 | 1 | — | Sample too small |
| Warren O'Hora | Centre back | 2 | 180 | — | — | Sample too small |
| Kanayo Megwa | Full back | 3 | 113 | — | — | Sample too small |
| Marko Ivezic | Centre back | 1 | 90 | — | — | Sample too small |
| Rabbi Matondo | Role not established | 1 | 36 | — | — | Sample too small |
| Rudi Molotnikov | Role not established | 1 | 30 | — | — | Sample too small |
| Nicky Cadden | Role not established | 2 | 27 | — | — | Sample too small |
| Joe Newell | Role not established | 2 | 20 | — | — | Sample too small |
| Azeem Abdullah | Role not established | 1 | 17 | — | — | 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
- Grant HanleyView player
Impact 73.5·Ball Security 98.0
- Jason KerrView player
Impact 60.5·Defensive Activity 73.4
Defensive midfielder
- View player
- Miguel ChaiwaView player
Impact 38.4·Defensive Reliability 52.8
Attacking midfielder
Winger
- Martin BoyleView player
Impact 42.2·Attacking Threat 17.5
- Adam MayorView player
Impact 39.2·Defensive Activity 83.3
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
- 1Grant HanleyCentre backArchetype not available73.5/100
- 2Jason KerrCentre backArchetype not available60.5/100
- 3Nathan LoweStrikerCreative Forward49.7/100
Squad archetype profile
The most common playing styles in the squad this season.
Not enough players in this squad have a published archetype this season to show a meaningful distribution.
Player contributions
Team leaders for minutes, goals, assists and Impact Score this season.
Most minutes
All completed fixtures this season.
- 1Raphael Sallinger720minutes
- 2Jason Kerr720minutes
- 3Josh Mulligan705minutes
- 4Felix Passlack644minutes
- 5Miguel Chaiwa496minutes
Most goals
Season totals from imported match data.
- 1Martin Boyle3goals
- 2Callum Wright2goals
- 3Adam Mayor1goals
- 4Nathan Lowe1goals
- 5Josh Campbell1goals
Most assists
Season totals from imported match data.
- 1Josh Mulligan1assists
- 2Felix Passlack1assists
- 3Miguel Chaiwa1assists
- 4Nathan Lowe1assists
- 5Grant Hanley1assists
Highest Impact Score
Only players who meet the publishable sample and coverage rules.
- 1Grant Hanley73.5/ 100
- 2Jason Kerr60.5/ 100
- 3Nathan Lowe49.7/ 100
- 4Raphael Sallinger49.2/ 100
- 5Callum Wright47.1/ 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.