Tom Rothe
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Tom Rothe's performance-implied value at EUR 2.8M-7.9M, below the estimated acquisition range of EUR 6.0M-16.1M. Its 24-month market value projection is EUR 4.9M-21.0M. Context-adjusted goal contributions are 1.04x the positional average in the league (1024 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: Contract end date unavailable: range widened by 15% each side.
Bargain Index: 54
What drives the score. Not a black box: each component and its level.
| Performance | Average | 48.3th pct among MID peers (age-neutral) |
| Age | Favorable | 21.7 years |
| Acquisition cost | Neutral | est. €10.5M vs market €10.0M |
| Expected appreciation | Neutral | +9% over ~2 years (model) |
| Value gap | Very negative | weak predictor on its own |
| Development | Moderate | breakout probability 24% |
| 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 | High | |
| 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
- 1024 (34% of available)
- Goals + assists / 90
- 0.18
- Context-adjusted G+A / 90
- 0.23
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 48 (Average)
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)
- 1392
- Opponent strength
- 1511
- Possession, role
- Data unavailable
League strength 1.00 = average club of the big-five leagues. Elo includes continental matches.
Potential
- Development
- Moderate
- Trajectory
- declining
- Breakout probability
- 24%
- Resale range (24m)
- €4.9M – €21.0M
Trajectory drivers: minutes share down 21 pts; relative output down 33% vs positional peers.
Historical comparables (8): median 2-year value change -19% (IQR -56% to +31%).
Risk profile
Overall: High
- ▲Projection range among the widest 10% of evaluated players.
- ⚠Limited sample: 1024 league minutes last season.
- ⚠Played under 40% of available league minutes (injury data unavailable, cause unknown).
- ⚠Declining trajectory versus previous season.
- ⓘContract end date unavailable (or stale in source).
- ⓘ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 | 1.FC Union Berlin | Bundesliga | LM | 21 | 1024 | 33% | 2 | 0 | 0.18 | 0.23 | 1511 | 1392 | 0.94 |
| 2024/25 | 1.FC Union Berlin | Bundesliga | LM | 26 | 1672 | 55% | 3 | 4 | 0.38 | 0.34 | 1482 | 1394 | 0.94 |
| 2022/23 | Borussia Dortmund | Bundesliga | LB | 2 | 24 | 1% | 0 | 1 | 3.75 | 0.16 | 1487 | 1691 | 1.04 |
| 2021/22 | Borussia Dortmund | Bundesliga | LM | 2 | 94 | 3% | 1 | 0 | 0.96 | 0.22 | 1466 | 1643 | 1.05 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Dfb Pokal | 1.FC Union Berlin | 3 | 293 | 0 | 0 | — |
| 2024/25 | Dfb Pokal | 1.FC Union Berlin | 1 | 34 | 0 | 0 | — |
| 2022/23 | Uefa Champions League | Borussia Dortmund | 3 | 59 | 0 | 0 | 1544 |
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 |
|---|---|---|---|---|
| Joan González Serie A · 2024 | 22 | €4.5M | €800k | fell |
| Adil Aouchiche Ligue 1 · 2022 | 20 | €6.0M | €2.2M | fell |
| Tommaso Baldanzi Serie A · 2024 | 21 | €15.0M | €8.5M | fell |
| Alfred Duncan Serie A · 2015 | 22 | €5.0M | €8.5M | rose |
| Yann M'Vila Ligue 1 · 2013 | 23 | €15.0M | €7.0M | fell |
| Josha Vagnoman Bundesliga · 2023 | 23 | €8.0M | €10.0M | rose |
| Dion Lopy Ligue 1 · 2023 | 21 | €4.0M | €6.0M | rose |
| Bruno Fernandes Serie A · 2015 | 21 | €6.5M | €7.5M | flat |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 7 Aug 2024 | Dortmund | Union Berlin | €5.0M | €8.0M |
| 30 Jun 2024 | Holstein Kiel | Dortmund | Free / loan | €8.0M |
| 1 Jul 2023 | Dortmund | Holstein Kiel | Free / loan | €3.5M |
| 1 Jul 2022 | B. Dortmund U19 | Dortmund | Unknown | €1.2M |
| 1 Jul 2021 | St. Pauli U17 | B. Dortmund U19 | Free / loan | Data unavailable |
| 1 Jul 2020 | St. Pauli Yth. | St. Pauli U17 | Unknown | Data unavailable |
| 1 Jul 2018 | Nienstedt. Yth. | St. Pauli Yth. | Free / loan | Data unavailable |
| 1 Jul 2016 | Büdel. TSV Yth. | Nienstedt. Yth. | Free / loan | Data unavailable |
| 1 Jul 2012 | Rendsburg Yth. | Büdel. TSV 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.