
Romano Schmid
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Romano Schmid's performance-implied value at EUR 5.6M-26.5M, above the estimated acquisition range of EUR 5.5M-13.0M. Its 24-month market value projection is EUR 7.2M-21.2M. Context-adjusted goal contributions are 1.00x the positional average in the league (2993 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: 89
What drives the score. Not a black box: each component and its level.
| Performance | High | 82.4th pct among MID peers (age-neutral) |
| Age | Neutral | 26.4 years |
| Acquisition cost | Very favorable | est. €7.3M vs market €15.0M |
| Expected appreciation | Low | -21% over ~2 years (model) |
| Value gap | Large | 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 1163 evaluated MID players with 900+ minutes.
Performance (last season, league)
- Minutes
- 2993 (98% of available)
- Goals + assists / 90
- 0.36
- Context-adjusted G+A / 90
- 0.40
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 82 (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)
- 1378
- Opponent strength
- 1490
- 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)
- €7.2M – €21.2M
Trajectory drivers: team strength down (-104 Elo).
Historical comparables (8): median 2-year value change -19% (IQR -53% to +29%).
Risk profile
Overall: Low
- ⚠Contract ends in 12 months: cheaper, but competition and wage demands likely.
- ⓘ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 | SV Werder Bremen | Bundesliga | AM | 34 | 2993 | 98% | 4 | 8 | 0.36 | 0.40 | 1490 | 1378 | 0.94 |
| 2024/25 | SV Werder Bremen | Bundesliga | AM | 32 | 2846 | 93% | 5 | 5 | 0.32 | 0.32 | 1490 | 1483 | 0.94 |
| 2023/24 | SV Werder Bremen | Bundesliga | AM | 33 | 2615 | 85% | 4 | 7 | 0.38 | 0.41 | 1523 | 1459 | 1.01 |
| 2022/23 | SV Werder Bremen | Bundesliga | AM | 27 | 1520 | 50% | 1 | 3 | 0.24 | 0.31 | 1549 | 1393 | 1.04 |
| 2020/21 | SV Werder Bremen | Bundesliga | AM | 22 | 1181 | 39% | 0 | 4 | 0.30 | 0.41 | 1549 | 1384 | 1.06 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | World Cup | Austria | 3 | 206 | 1 | 0 | — |
| 2025/26 | Dfb Pokal | SV Werder Bremen | 1 | 90 | 0 | 0 | — |
| 2024/25 | Dfb Pokal | SV Werder Bremen | 3 | 270 | 0 | 1 | — |
| 2023/24 | Dfb Pokal | SV Werder Bremen | 1 | 90 | 0 | 0 | — |
| 2022/23 | Dfb Pokal | SV Werder Bremen | 2 | 154 | 1 | 0 | — |
| 2020/21 | Dfb Pokal | SV Werder Bremen | 3 | 180 | 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 |
|---|---|---|---|---|
| Moussa Sissoko Premier League · 2016 | 27 | €13.0M | €18.0M | rose |
| Diego Laxalt Serie A · 2017 | 24 | €7.5M | €12.0M | rose |
| Angelo Fulgini Ligue 1 · 2022 | 26 | €12.0M | €7.0M | fell |
| Stijn Spierings Ligue 1 · 2023 | 27 | €6.0M | €2.0M | fell |
| Răzvan Marin Serie A · 2022 | 26 | €12.0M | €2.7M | fell |
| Christian Günter Bundesliga · 2020 | 27 | €9.5M | €12.0M | rose |
| Jordan Veretout Serie A · 2018 | 25 | €18.0M | €20.0M | flat |
| Ivelin Popov Premier Liga · 2015 | 28 | €9.5M | €5.0M | fell |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 31 Jul 2020 | Wolfsberger AC | Werder Bremen | Free / loan | €2.0M |
| 5 Feb 2019 | Werder Bremen | Wolfsberger AC | Free / loan | €800k |
| 3 Jan 2019 | Salzburg | Werder Bremen | €1.0M | €800k |
| 19 Aug 2017 | Sturm Graz | Salzburg | €600k | €350k |
| 1 Jul 2016 | Sturm Graz II | Sturm Graz | Unknown | Data unavailable |
| 27 Jan 2016 | Stmk.-Sturm U18 | Sturm Graz II | Unknown | Data unavailable |
| 1 Jul 2015 | Stmk.-Sturm U16 | Stmk.-Sturm U18 | Unknown | Data unavailable |
| 1 Jul 2014 | Stmk.-Sturm U15 | Stmk.-Sturm U16 | Unknown | Data unavailable |
| 1 Jul 2013 | Sturm Graz Yth | Stmk.-Sturm U15 | Unknown | Data unavailable |
| 1 Jul 2009 | Vasoldsberg J. | Sturm Graz Yth | 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.