Badredine Bouanani
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Badredine Bouanani's performance-implied value at EUR 3.0M-9.7M, below the estimated acquisition range of EUR 7.0M-17.7M. Its 24-month market value projection is EUR 4.0M-18.9M. Context-adjusted goal contributions are 0.52x the positional average in the league (551 minutes, league coefficient 0.94). Confidence is low: no event-level data (xG, progressive actions) is available from the current free source, and injury history is unavailable.
Bargain Index: not assigned
What drives the score. Not a black box: each component and its level.
Insufficient sample (< 900 league minutes)
| Performance | Average | 45.8th pct among ATT peers (age-neutral) |
| Age | Favorable | 21.6 years |
| Acquisition cost | Unfavorable | est. €11.8M 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 19% |
| 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 | Very High | |
| Data confidence | Low |
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 901 evaluated ATT players with 900+ minutes.
Performance (last season, league)
- Minutes
- 551 (18% of available)
- Goals + assists / 90
- 0.00
- Context-adjusted G+A / 90
- 0.19
- 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
- 0.94 (rank 3)
- Team strength (Elo)
- 1531
- Opponent strength
- 1395
- 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
- 19%
- Resale range (24m)
- €4.0M – €18.9M
Trajectory drivers: minutes share down 18 pts; changed club; relative output down 39% vs positional peers.
Historical comparables (8): median 2-year value change +44% (IQR -30% to +139%).
Risk profile
Overall: Very High
- ▲Small sample: 551 league minutes last season.
- ▲Projection range among the widest 10% of evaluated players.
- ⚠Played under 40% of available league minutes (injury data unavailable, cause unknown).
- ⚠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 | VfB Stuttgart | Bundesliga | RW | 14 | 458 | 15% | 0 | 0 | 0.00 | 0.19 | 1395 | 1567 | 0.94 |
| 2025/26 | OGC Nice | Ligue 1 | RW | 2 | 93 | 3% | 0 | 0 | 0.00 | 0.29 | 1430 | 1358 | 0.88 |
| 2024/25 | OGC Nice | Ligue 1 | RW | 26 | 1094 | 36% | 3 | 3 | 0.49 | 0.37 | 1433 | 1521 | 0.88 |
| 2023/24 | FC Lorient | Ligue 1 | RW | 11 | 439 | 14% | 1 | 0 | 0.21 | 0.49 | 1480 | 1335 | 0.87 |
| 2023/24 | OGC Nice | Ligue 1 | RW | 7 | 156 | 5% | 0 | 0 | 0.00 | 0.32 | 1441 | 1511 | 0.87 |
| 2022/23 | OGC Nice | Ligue 1 | RW | 19 | 862 | 25% | 0 | 4 | 0.42 | 0.30 | 1399 | 1519 | 0.82 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Uefa Europa League | VfB Stuttgart | 10 | 460 | 2 | 1 | 1424 |
| 2025/26 | Uefa Champions League Qualifying | OGC Nice | 2 | 152 | 0 | 0 | 1638 |
| 2025/26 | Dfb Pokal | VfB Stuttgart | 4 | 84 | 0 | 1 | — |
| 2024/25 | Uefa Europa League | OGC Nice | 8 | 538 | 2 | 0 | 1532 |
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 |
|---|---|---|---|---|
| Luis Henrique Ligue 1 · 2024 | 23 | €8.0M | €22.0M | rose |
| Callum Hudson-Odoi Bundesliga · 2023 | 23 | €15.0M | €25.0M | rose |
| Abde Ezzalzouli Laliga · 2024 | 23 | €9.0M | €40.0M | rose |
| Sofiane Diop Ligue 1 · 2024 | 24 | €12.0M | €15.0M | rose |
| Miroslav Stoch Super Lig · 2013 | 24 | €8.0M | €5.5M | fell |
| Felix Afena-Gyan Serie A · 2022 | 19 | €6.0M | €4.2M | fell |
| Moise Kean Serie A · 2024 | 24 | €14.0M | €32.0M | rose |
| Jens Petter Hauge Serie A · 2021 | 22 | €9.5M | €2.5M | fell |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 31 Aug 2025 | Nice | Stuttgart | €15.0M | €7.0M |
| 30 Jun 2024 | FC Lorient | Nice | Free / loan | €5.0M |
| 31 Jan 2024 | Nice | FC Lorient | Free / loan | €6.0M |
| 7 Jul 2022 | LOSC Lille B | Nice | Free / loan | Data unavailable |
| 1 Jul 2021 | LOSC Lille U19 | LOSC Lille B | Unknown | Data unavailable |
| 1 Jul 2020 | LOSC Lille U17 | LOSC Lille U19 | Unknown | Data unavailable |
| 1 Jul 2019 | LOSC Lille Yth. | LOSC Lille 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.