
Karim Adeyemi
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Karim Adeyemi's performance-implied value at EUR 13.4M-50.8M, above the estimated acquisition range of EUR 18.5M-41.7M. Its 24-month market value projection is EUR 21.0M-53.4M. Context-adjusted goal contributions are 0.95x the positional average in the league (1196 minutes, league coefficient 0.94). Confidence is medium: no event-level data (xG, progressive actions) is available from the current free source, and injury history is unavailable.
Acquisition note: Final year of contract: selling club's leverage is reduced.
Bargain Index: 71
What drives the score. Not a black box: each component and its level.
| Performance | High | 86.9th pct among ATT peers (age-neutral) |
| Age | Neutral | 24.4 years |
| Acquisition cost | Favorable | est. €24.7M vs market €40.0M |
| Expected appreciation | Low | -25% over ~2 years (model) |
| Value gap | Small | weak predictor on its own |
| Development | Moderate | |
| 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 | Moderate | |
| 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 900 evaluated ATT players with 900+ minutes.
Performance (last season, league)
- Minutes
- 1196 (39% of available)
- Goals + assists / 90
- 0.83
- Context-adjusted G+A / 90
- 0.51
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 87 (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)
- 1656
- Opponent strength
- 1493
- Possession, role
- Data unavailable
League strength 1.00 = average club of the big-five leagues. Elo includes continental matches.
Potential
- Development
- Moderate
- Trajectory
- stable
- Breakout probability
- Age > 23
- Resale range (24m)
- €21.0M – €53.4M
Trajectory drivers: role change RW -> SS.
Historical comparables (8): median 2-year value change -24% (IQR -51% to +11%).
Risk profile
Overall: Moderate
- ⚠Limited sample: 1196 league minutes last season.
- ⚠Contract ends in 12 months: cheaper, but competition and wage demands likely.
- ⚠Played under 40% of available league minutes (injury data unavailable, cause unknown).
- ⓘ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 | Borussia Dortmund | Bundesliga | SS | 28 | 1196 | 39% | 7 | 4 | 0.83 | 0.51 | 1493 | 1656 | 0.94 |
| 2024/25 | Borussia Dortmund | Bundesliga | RW | 25 | 1441 | 47% | 7 | 6 | 0.81 | 0.43 | 1483 | 1680 | 0.94 |
| 2023/24 | Borussia Dortmund | Bundesliga | LW | 21 | 911 | 30% | 3 | 1 | 0.40 | 0.24 | 1536 | 1716 | 1.01 |
| 2022/23 | Borussia Dortmund | Bundesliga | RW | 24 | 1397 | 46% | 6 | 6 | 0.77 | 0.41 | 1508 | 1691 | 1.04 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Uefa Champions League | Borussia Dortmund | 9 | 473 | 3 | 2 | 1629 |
| 2025/26 | Dfb Pokal | Borussia Dortmund | 2 | 167 | 0 | 0 | — |
| 2024/25 | Uefa Champions League | Borussia Dortmund | 10 | 691 | 5 | 2 | 1630 |
| 2024/25 | Dfb Pokal | Borussia Dortmund | 1 | 69 | 0 | 1 | — |
| 2023/24 | Uefa Champions League | Borussia Dortmund | 12 | 709 | 2 | 1 | 1722 |
| 2023/24 | Dfb Pokal | Borussia Dortmund | 1 | 90 | 0 | 0 | — |
| 2022/23 | Uefa Champions League | Borussia Dortmund | 6 | 379 | 2 | 0 | 1615 |
| 2022/23 | Dfb Pokal | Borussia Dortmund | 2 | 94 | 1 | 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 |
|---|---|---|---|---|
| Ferran Torres Laliga · 2024 | 24 | €30.0M | €50.0M | rose |
| Mikel Oyarzabal Laliga · 2023 | 26 | €40.0M | €25.0M | fell |
| João Félix Laliga · 2024 | 25 | €30.0M | €28.0M | flat |
| Ousmane Dembélé Laliga · 2023 | 26 | €60.0M | €90.0M | rose |
| Samuel Chukwueze Laliga · 2022 | 23 | €20.0M | €20.0M | flat |
| Thomas Lemar Laliga · 2022 | 27 | €40.0M | €10.0M | fell |
| Keita Baldé Ligue 1 · 2018 | 23 | €30.0M | €16.0M | fell |
| Mario Balotelli Serie A · 2013 | 23 | €30.0M | €11.0M | fell |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 1 Jul 2022 | Salzburg | Dortmund | €30.0M | €35.0M |
| 31 Dec 2019 | FC Liefering | Salzburg | Free / loan | €7.5M |
| 2 Jul 2018 | Salzburg | FC Liefering | Free / loan | €1.5M |
| 1 Jul 2018 | U'haching U19 | Salzburg | €10.1M | Data unavailable |
| 1 Jan 2018 | U'haching U17 | U'haching U19 | Unknown | Data unavailable |
| 1 Jan 2017 | U'haching Yth. | U'haching U17 | Unknown | Data unavailable |
| 1 Jul 2012 | Forstenried Jgd | U'haching Yth. | Free / loan | Data unavailable |
| 1 Jul 2011 | B. München Yth. | Forstenried Jgd | Free / loan | Data unavailable |
| 1 Jul 2010 | Forstenried Jgd | B. München Yth. | Free / loan | 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.