
Joshua Kimmich
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Joshua Kimmich's performance-implied value at EUR 21.1M-57.2M, above the estimated acquisition range of EUR 19.8M-39.5M. Its 24-month market value projection is EUR 8.6M-19.0M. Context-adjusted goal contributions are 1.13x the positional average in the league (2282 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.
Bargain Index: 0
What drives the score. Not a black box: each component and its level.
| Performance | Elite | 99.8th pct among MID peers (age-neutral) |
| Age | Unfavorable | 31.4 years |
| Acquisition cost | Favorable | est. €27.5M vs market €35.0M |
| Expected appreciation | Very low | -66% over ~2 years (model) |
| Value gap | Small | 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 | 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 1163 evaluated MID players with 900+ minutes.
Performance (last season, league)
- Minutes
- 2282 (75% of available)
- Goals + assists / 90
- 0.39
- Context-adjusted G+A / 90
- 0.14
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 100 (Elite)
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)
- 1871
- Opponent strength
- 1473
- Possession, role
- Data unavailable
League strength 1.00 = average club of the big-five leagues. Elo includes continental matches.
Potential
- Development
- Low
- Trajectory
- declining
- Breakout probability
- Age > 23
- Resale range (24m)
- €8.6M – €19.0M
Trajectory drivers: minutes share down 18 pts; team strength up (+99 Elo).
Historical comparables (8): median 2-year value change -57% (IQR -65% to -43%).
Risk profile
Overall: Moderate
- ⚠Age 31: resale value typically declines.
- ⚠Declining trajectory versus previous season.
- ⓘ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 | Bayern Munich | Bundesliga | DM | 29 | 2282 | 75% | 2 | 8 | 0.39 | 0.14 | 1473 | 1871 | 0.94 |
| 2024/25 | Bayern Munich | Bundesliga | DM | 33 | 2847 | 93% | 3 | 7 | 0.32 | 0.16 | 1484 | 1772 | 0.94 |
| 2023/24 | Bayern Munich | Bundesliga | DM | 28 | 2192 | 72% | 1 | 7 | 0.33 | 0.14 | 1491 | 1715 | 1.01 |
| 2022/23 | Bayern Munich | Bundesliga | DM | 33 | 2814 | 92% | 5 | 6 | 0.35 | 0.13 | 1512 | 1817 | 1.04 |
| 2021/22 | Bayern Munich | Bundesliga | DM | 28 | 2478 | 81% | 3 | 12 | 0.54 | 0.16 | 1496 | 1847 | 1.05 |
| 2020/21 | Bayern Munich | Bundesliga | DM | 27 | 2196 | 72% | 4 | 10 | 0.57 | 0.17 | 1512 | 1898 | 1.06 |
| 2019/20 | Bayern Munich | Bundesliga | DM | 33 | 2821 | 92% | 4 | 9 | 0.41 | 0.18 | 1517 | 1892 | 1.06 |
| 2018/19 | Bayern Munich | Bundesliga | RB | 34 | 3060 | 100% | 2 | 14 | 0.47 | 0.15 | 1496 | 1839 | 1.05 |
| 2017/18 | Bayern Munich | Bundesliga | RB | 29 | 2333 | 76% | 1 | 12 | 0.50 | 0.18 | 1496 | 1863 | 1.04 |
| 2016/17 | Bayern Munich | Bundesliga | CM | 27 | 1542 | 50% | 6 | 1 | 0.41 | 0.15 | 1496 | 1855 | 1.06 |
| 2015/16 | Bayern Munich | Bundesliga | CB | 23 | 1423 | 47% | 0 | 2 | 0.13 | 0.05 | 1509 | 1853 | 1.02 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Uefa Champions League | Bayern Munich | 13 | 1161 | 0 | 2 | 1716 |
| 2025/26 | Dfb Pokal | Bayern Munich | 5 | 450 | 0 | 3 | — |
| 2025/26 | World Cup | Germany | 3 | 233 | 0 | 2 | — |
| 2025/26 | Franz Beckenbauer Supercup | Bayern Munich | 1 | 90 | 0 | 0 | 1531 |
| 2024/25 | Uefa Champions League | Bayern Munich | 14 | 1260 | 0 | 5 | 1647 |
| 2024/25 | Dfb Pokal | Bayern Munich | 3 | 270 | 0 | 0 | — |
| 2023/24 | Uefa Champions League | Bayern Munich | 12 | 1080 | 1 | 2 | 1663 |
| 2023/24 | Dfb Pokal | Bayern Munich | 2 | 153 | 0 | 1 | — |
| 2023/24 | Franz Beckenbauer Supercup | Bayern Munich | 1 | 78 | 0 | 0 | 1685 |
| 2022/23 | Uefa Champions League | Bayern Munich | 9 | 810 | 1 | 3 | 1737 |
| 2022/23 | Dfb Pokal | Bayern Munich | 4 | 338 | 1 | 2 | — |
| 2022/23 | Franz Beckenbauer Supercup | Bayern Munich | 1 | 90 | 0 | 0 | 1663 |
| 2021/22 | Uefa Champions League | Bayern Munich | 8 | 702 | 0 | 0 | 1661 |
| 2021/22 | Dfb Pokal | Bayern Munich | 2 | 135 | 0 | 0 | — |
| 2021/22 | Franz Beckenbauer Supercup | Bayern Munich | 1 | 90 | 0 | 0 | 1713 |
| 2020/21 | Uefa Champions League | Bayern Munich | 7 | 617 | 1 | 4 | 1654 |
| 2020/21 | Dfb Pokal | Bayern Munich | 1 | 120 | 0 | 0 | — |
| 2020/21 | Uefa Super Cup | Bayern Munich | 1 | 120 | 0 | 0 | 1722 |
| 2020/21 | Franz Beckenbauer Supercup | Bayern Munich | 1 | 90 | 1 | 0 | 1687 |
| 2019/20 | Uefa Champions League | Bayern Munich | 11 | 903 | 2 | 4 | 1667 |
| 2019/20 | Dfb Pokal | Bayern Munich | 6 | 540 | 1 | 4 | — |
| 2019/20 | Franz Beckenbauer Supercup | Bayern Munich | 1 | 90 | 0 | 0 | 1683 |
| 2018/19 | Uefa Champions League | Bayern Munich | 7 | 630 | 0 | 2 | 1639 |
| 2018/19 | Dfb Pokal | Bayern Munich | 6 | 501 | 0 | 2 | — |
| 2018/19 | Franz Beckenbauer Supercup | Bayern Munich | 1 | 90 | 0 | 1 | 1479 |
| 2017/18 | Uefa Champions League | Bayern Munich | 11 | 897 | 4 | 3 | 1693 |
| 2017/18 | Dfb Pokal | Bayern Munich | 6 | 570 | 1 | 1 | — |
| 2017/18 | Franz Beckenbauer Supercup | Bayern Munich | 1 | 90 | 0 | 1 | 1705 |
| 2016/17 | Uefa Champions League | Bayern Munich | 8 | 320 | 3 | 0 | 1668 |
| 2016/17 | Dfb Pokal | Bayern Munich | 4 | 211 | 0 | 1 | — |
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 |
|---|---|---|---|---|
| Casemiro Laliga · 2022 | 30 | €40.0M | €20.0M | fell |
| Radja Nainggolan Serie A · 2018 | 30 | €45.0M | €16.0M | fell |
| Ivan Rakitic Laliga · 2017 | 29 | €45.0M | €40.0M | flat |
| Bastian Schweinsteiger Bundesliga · 2013 | 29 | €40.0M | €22.0M | fell |
| Marcelo Brozović Serie A · 2021 | 29 | €40.0M | €25.0M | fell |
| Sami Khedira Serie A · 2018 | 31 | €26.0M | €5.5M | fell |
| Sergio Busquets Laliga · 2018 | 30 | €80.0M | €28.0M | fell |
| Yaya Touré Premier League · 2015 | 32 | €22.0M | €8.0M | fell |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 2 Jul 2015 | Stuttgart | Bayern Munich | €9.5M | €5.0M |
| 1 Jul 2015 | Leipzig | Stuttgart | €1.5M | €5.0M |
| 5 Jul 2013 | Stuttgart U19 | Leipzig | €500k | Data unavailable |
| 1 Jul 2012 | Stuttgart U17 | Stuttgart U19 | Unknown | Data unavailable |
| 1 Jul 2010 | Stuttgart Yth. | Stuttgart U17 | Unknown | Data unavailable |
| 1 Jul 2007 | Bösingen Yth. | Stuttgart 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.