Benjamin Stambouli
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Benjamin Stambouli's performance-implied value at EUR 0.1M-0.8M, above the estimated acquisition range of EUR 0.1M-0.3M. Its 24-month market value projection is EUR 0.2M-0.3M. Context-adjusted goal contributions are 0.79x the positional average in the league (960 minutes, league coefficient 0.88). 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: not assigned
What drives the score. Not a black box: each component and its level.
Age above 33 (outside validated pool)
| Performance | Average | 46.2th pct among MID peers (age-neutral) |
| Age | Unfavorable | 35.9 years |
| Acquisition cost | Favorable | est. €166k vs market €250k |
| Expected appreciation | Neutral | -3% over ~2 years (model) |
| Value gap | Large | weak predictor on its own |
| Development | Low | |
| League translation | Big-five league | league coefficient 0.88 |
| 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
- 960 (31% of available)
- Goals + assists / 90
- 0.00
- Context-adjusted G+A / 90
- 0.10
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 46 (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
- 0.88 (rank 5)
- Team strength (Elo)
- 1225
- 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
- insufficient
- Breakout probability
- Age > 23
- Resale range (24m)
- €157k – €256k
Historical comparables (8): median 2-year value change -59% (IQR -76% to +0%).
Risk profile
Overall: High
- ▲Age 36: resale value typically declines.
- ⚠Limited sample: 960 league minutes last season.
- ⚠No continental-competition minutes last season.
- ⚠Played under 40% of available league minutes (injury data unavailable, cause unknown).
- ⓘ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 | FC Metz | Ligue 1 | DM | 19 | 960 | 31% | 0 | 0 | 0.00 | 0.10 | 1473 | 1225 | 0.88 |
| 2023/24 | Adana Demirspor | Super Lig | DM | 20 | 1382 | 40% | 1 | 0 | 0.07 | 0.07 | 1255 | 1250 | 0.45 |
| 2023/24 | Stade Reims | Ligue 1 | DM | 7 | 286 | 9% | 0 | 1 | 0.31 | 0.20 | 1451 | 1419 | 0.87 |
| 2022/23 | Adana Demirspor | Super Lig | DM | 30 | 2114 | 65% | 1 | 5 | 0.26 | 0.20 | 1307 | 1410 | 0.50 |
| 2021/22 | Adana Demirspor | Super Lig | DM | 32 | 2452 | 72% | 2 | 4 | 0.22 | 0.17 | 1249 | 1273 | 0.42 |
| 2020/21 | FC Schalke 04 | Bundesliga | DM | 24 | 1956 | 64% | 0 | 2 | 0.09 | 0.12 | 1549 | 1303 | 1.06 |
| 2019/20 | FC Schalke 04 | Bundesliga | CB | 9 | 810 | 26% | 0 | 0 | 0.00 | 0.03 | 1546 | 1415 | 1.06 |
| 2018/19 | FC Schalke 04 | Bundesliga | CB | 21 | 1763 | 58% | 0 | 2 | 0.10 | 0.08 | 1488 | 1482 | 1.05 |
| 2017/18 | FC Schalke 04 | Bundesliga | CB | 28 | 2194 | 72% | 0 | 2 | 0.08 | 0.06 | 1498 | 1618 | 1.04 |
| 2016/17 | FC Schalke 04 | Bundesliga | DM | 23 | 1294 | 42% | 0 | 0 | 0.00 | 0.04 | 1575 | 1556 | 1.06 |
| 2015/16 | Paris Saint-Germain | Ligue 1 | DM | 27 | 1503 | 44% | 0 | 0 | 0.00 | 0.02 | 1390 | 1748 | 0.78 |
| 2014/15 | Tottenham Hotspur | Premier League | DM | 12 | 453 | 13% | 0 | 0 | 0.00 | 0.06 | 1506 | 1576 | 1.06 |
| 2014/15 | Montpellier HSC | Ligue 1 | DM | 2 | 180 | 5% | 0 | 0 | 0.00 | 0.14 | 1452 | 1434 | 0.80 |
| 2013/14 | Montpellier HSC | Ligue 1 | DM | 37 | 3330 | 97% | 2 | 1 | 0.08 | 0.11 | 1479 | 1372 | 0.79 |
| 2012/13 | Montpellier HSC | Ligue 1 | DM | 21 | 1687 | 49% | 1 | 1 | 0.11 | 0.13 | 1459 | 1431 | 0.88 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2023/24 | Uefa Conference League Qualifying | Adana Demirspor | 6 | 555 | 1 | 0 | 1439 |
| 2020/21 | Dfb Pokal | FC Schalke 04 | 3 | 255 | 0 | 0 | — |
| 2019/20 | Dfb Pokal | FC Schalke 04 | 1 | 90 | 0 | 0 | — |
| 2018/19 | Uefa Champions League | FC Schalke 04 | 5 | 431 | 0 | 0 | 1616 |
| 2018/19 | Dfb Pokal | FC Schalke 04 | 1 | 90 | 0 | 0 | — |
| 2017/18 | Dfb Pokal | FC Schalke 04 | 4 | 315 | 0 | 0 | — |
| 2016/17 | Uefa Europa League | FC Schalke 04 | 11 | 659 | 0 | 0 | 1553 |
| 2016/17 | Dfb Pokal | FC Schalke 04 | 3 | 270 | 0 | 0 | — |
| 2016/17 | Trophee Des Champions | Paris Saint-Germain | 1 | 90 | 0 | 0 | 1533 |
| 2015/16 | Uefa Champions League | Paris Saint-Germain | 2 | 111 | 0 | 0 | 1595 |
| 2015/16 | Trophee Des Champions | Paris Saint-Germain | 1 | 20 | 0 | 0 | 1581 |
| 2014/15 | Uefa Europa League | Tottenham Hotspur | 6 | 496 | 1 | 0 | 1466 |
| 2014/15 | Fa Cup | Tottenham Hotspur | 2 | 135 | 0 | 0 | — |
| 2012/13 | Uefa Champions League | Montpellier HSC | 4 | 237 | 0 | 0 | 1551 |
| 2012/13 | Trophee Des Champions | Montpellier HSC | 1 | 9 | 0 | 0 | 1449 |
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 |
|---|---|---|---|---|
| Cristian Molinaro Serie A · 2019 | 36 | €300k | €75k | fell |
| Frédéric Sammaritano Ligue 1 · 2021 | 35 | €300k | €200k | fell |
| Alessandro Bruno Serie A · 2017 | 34 | €100k | €200k | rose |
| Igor Semshov Premier Liga · 2014 | 36 | €300k | €300k | flat |
| Manuele Blasi Serie A · 2013 | 33 | €300k | €50k | fell |
| Dmitriy Torbinski Premier Liga · 2019 | 35 | €200k | €200k | flat |
| Mariano Izco Serie A · 2017 | 34 | €500k | €100k | fell |
| Azim Fatullaev Premier Liga · 2019 | 33 | €300k | €75k | fell |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 10 Sept 2024 | Without Club | FC Metz | Unknown | €700k |
| 1 Jul 2024 | Stade Reims | Without Club | Unknown | €700k |
| 1 Feb 2024 | Adana Demirspor | Stade Reims | Free / loan | €800k |
| 26 Jul 2021 | FC Schalke 04 | Adana Demirspor | Free / loan | €1.5M |
| 26 Aug 2016 | PSG | FC Schalke 04 | €8.0M | €7.0M |
| 21 Jul 2015 | Tottenham | PSG | €8.6M | €5.0M |
| 1 Sept 2014 | Montpellier | Tottenham | €5.9M | €5.0M |
| 1 Jul 2010 | Montpellier B | Montpellier | Unknown | Data unavailable |
| 1 Jul 2009 | Montpellier U19 | Montpellier B | Unknown | Data unavailable |
| 1 Jul 2007 | Montpellier U17 | Montpellier U19 | Unknown | Data unavailable |
| 1 Jul 2005 | Montpellier For | Montpellier U17 | 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.