Kamil Grabara
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Kamil Grabara's performance-implied value at EUR 3.6M-12.4M, below the estimated acquisition range of EUR 6.6M-14.3M. Its 24-month market value projection is EUR 5.1M-13.5M. Confidence is medium: no event-level data (xG, progressive actions) is available from the current free source, and injury history is unavailable.
Bargain Index: 16
What drives the score. Not a black box: each component and its level.
| Performance | High | 77.1th pct among GK peers (age-neutral) |
| Age | Neutral | 27.5 years |
| Acquisition cost | Favorable | est. €10.3M vs market €12.0M |
| Expected appreciation | Very low | -38% over ~2 years (model) |
| Value gap | Very negative | weak predictor on its own |
| Development | Low | |
| League translation | Big-five league | league coefficient 0.94 |
| Tactical fit | Not evaluated | Requires event/role data not available from the current free source. |
| Risk | Low | |
| Data confidence | Medium |
Bargain Index = percentile (among all evaluated players) of expected 2-year value relative to estimated cost. See methodology and backtests.
Market value history
Market value ≠ transfer fee ≠ acquisition cost.
Profile vs positional peers
Percentiles among 284 evaluated GK players with 900+ minutes.
Performance (last season, league)
- Minutes
- 3060 (100% of available)
- Goals + assists / 90
- 0.00
- Context-adjusted G+A / 90
- 0.00
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 77 (High)
Adjusted = shrunk toward positional baseline for small samples, corrected for team dominance over opponents, expressed relative to positional peers in the same league.
Context
- League strength
- 0.94 (rank 3)
- Team strength (Elo)
- 1372
- Opponent strength
- 1493
- Possession, role
- Data unavailable
League strength 1.00 = average club of the big-five leagues. Elo includes continental matches.
Potential
- Development
- Low
- Trajectory
- improving
- Breakout probability
- Age > 23
- Resale range (24m)
- €5.1M – €13.5M
Trajectory drivers: minutes share up 15 pts; team strength down (-66 Elo).
Historical comparables (8): median 2-year value change -13% (IQR -42% to +8%).
Risk profile
Overall: Low
- ⓘInjury history unavailable from current data source.
League translation
What happened to players who moved from this league to the big-five leagues (observed, not a forecast).
Already playing in a big-five league.
Output is relative to positional peers in each league. Movers are a selected group (clubs buy players who fit), so treat this as context, not a guarantee.
Season-by-season (domestic league)
Context-adjusted values are model outputs.
| Season | Club | League | Pos | Apps | Min | Min share | G | A | G+A/90 | Adj. G+A/90 | Opp. Elo | Team Elo | League str. |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2025/26 | VfL Wolfsburg | Bundesliga | GK | 34 | 3060 | 100% | 0 | 0 | 0.00 | 0.00 | 1493 | 1372 | 0.94 |
| 2024/25 | VfL Wolfsburg | Bundesliga | GK | 29 | 2586 | 85% | 0 | 0 | 0.00 | 0.00 | 1504 | 1438 | 0.94 |
| 2023/24 | FC Copenhagen | Superliga | GK | 21 | 1890 | 95% | 0 | 0 | 0.00 | 0.00 | 1281 | 1517 | 0.48 |
| 2021/22 | FC Copenhagen | Superliga | GK | 22 | 1980 | 100% | 0 | 0 | 0.00 | 0.00 | 1251 | 1516 | 0.45 |
| 2020/21 | Aarhus GF | Superliga | GK | 19 | 1710 | 86% | 0 | 0 | 0.00 | 0.00 | 1294 | 1335 | 0.43 |
| 2018/19 | Aarhus GF | Superliga | GK | 6 | 540 | 23% | 0 | 0 | 0.00 | 0.00 | 1315 | 1221 | 0.44 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Dfb Pokal | VfL Wolfsburg | 1 | 90 | 0 | 0 | — |
| 2024/25 | Dfb Pokal | VfL Wolfsburg | 3 | 300 | 0 | 0 | — |
| 2023/24 | Uefa Champions League | FC Copenhagen | 8 | 720 | 0 | 0 | 1733 |
| 2023/24 | Uefa Champions League Qualifying | FC Copenhagen | 6 | 570 | 0 | 0 | 1463 |
| 2023/24 | Oddset Pokalen | FC Copenhagen | 4 | 360 | 0 | 0 | — |
| 2021/22 | Uefa Conference League Qualifying | FC Copenhagen | 6 | 540 | 0 | 0 | 1340 |
| 2020/21 | Oddset Pokalen | Aarhus GF | 6 | 570 | 0 | 0 | — |
Small continental samples are shown for context only and are not over-weighted.
Historical comparables
Most similar profiles 2+ years ago (same position group) and what happened next. Chosen by similarity only — failures included.
| Player (then) | Age | Value then | ~2y later | Outcome |
|---|---|---|---|---|
| Álvaro Valles Laliga · 2024 | 27 | €12.0M | €7.0M | fell |
| Andrea Consigli Serie A · 2014 | 27 | €8.0M | €7.0M | flat |
| Alessio Cragno Serie A · 2022 | 28 | €10.0M | €1.5M | fell |
| Juan Musso Serie A · 2020 | 26 | €12.0M | €18.0M | rose |
| Predrag Rajković Ligue 1 · 2022 | 27 | €9.0M | €10.0M | flat |
| Alexander Schwolow Bundesliga · 2019 | 27 | €9.0M | €5.0M | fell |
| Benoît Costil Ligue 1 · 2013 | 26 | €7.5M | €8.0M | flat |
| Ron-Robert Zieler Bundesliga · 2016 | 27 | €8.0M | €7.0M | flat |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 1 Jul 2024 | Copenhagen | Wolfsburg | €13.5M | €12.0M |
| 3 Jul 2021 | Liverpool U23 | Copenhagen | €6.2M | €2.5M |
| 30 Jun 2021 | Aarhus GF | Liverpool U23 | Free / loan | €2.5M |
| 28 Sept 2020 | Liverpool U23 | Aarhus GF | Free / loan | €4.5M |
| 30 Jun 2020 | Huddersfield | Liverpool U23 | Free / loan | €4.5M |
| 15 Jul 2019 | Liverpool U23 | Huddersfield | Free / loan | €400k |
| 30 Jun 2019 | Aarhus GF | Liverpool U23 | Free / loan | €400k |
| 6 Jan 2019 | Liverpool U23 | Aarhus GF | Free / loan | €100k |
| 1 Jul 2017 | Liverpool U18 | Liverpool U23 | Unknown | €100k |
| 15 Jan 2016 | Ruch Chorzow | Liverpool U18 | €330k | €100k |
| 1 Jul 2015 | Ruch Chorzow II | Ruch Chorzow | Unknown | Data unavailable |
| 1 Jul 2014 | Chorzów Youth | Ruch Chorzow II | Unknown | Data unavailable |
MoneyballAI identifies statistical opportunities from available data. A player flagged as a potential bargain is not guaranteed to succeed, to transfer, to rise in value, or to generate resale profit. Market values, fees and contracts come from third-party sources; ranges are model estimates with stated confidence.