
Alexis Claude-Maurice
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Alexis Claude-Maurice's performance-implied value at EUR 4.1M-11.8M, above the estimated acquisition range of EUR 5.1M-13.2M. Its 24-month market value projection is EUR 5.3M-12.3M. Context-adjusted goal contributions are 1.14x the positional average in the league (2108 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: 57
What drives the score. Not a black box: each component and its level.
| Performance | High | 75.6th pct among MID peers (age-neutral) |
| Age | Unfavorable | 28.1 years |
| Acquisition cost | Very favorable | est. €6.8M vs market €15.0M |
| Expected appreciation | Very low | -47% 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 | 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
- 2108 (69% of available)
- Goals + assists / 90
- 0.38
- Context-adjusted G+A / 90
- 0.46
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 76 (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)
- 1421
- Opponent strength
- 1488
- Possession, role
- Data unavailable
League strength 1.00 = average club of the big-five leagues. Elo includes continental matches.
Potential
- Development
- Low
- Trajectory
- stable
- Breakout probability
- Age > 23
- Resale range (24m)
- €5.3M – €12.3M
Historical comparables (8): median 2-year value change -32% (IQR -56% to -2%).
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 | FC Augsburg | Bundesliga | AM | 29 | 2108 | 69% | 5 | 4 | 0.38 | 0.46 | 1488 | 1421 | 0.94 |
| 2024/25 | FC Augsburg | Bundesliga | AM | 28 | 2125 | 69% | 9 | 3 | 0.51 | 0.51 | 1498 | 1404 | 0.94 |
| 2023/24 | OGC Nice | Ligue 1 | AM | 18 | 495 | 16% | 0 | 0 | 0.00 | 0.21 | 1436 | 1511 | 0.87 |
| 2022/23 | RC Lens | Ligue 1 | AM | 20 | 594 | 17% | 5 | 3 | 1.21 | 0.52 | 1419 | 1626 | 0.82 |
| 2022/23 | OGC Nice | Ligue 1 | AM | 2 | 63 | 2% | 0 | 0 | 0.00 | 0.37 | 1525 | 1519 | 0.82 |
| 2021/22 | OGC Nice | Ligue 1 | AM | 10 | 200 | 6% | 0 | 2 | 0.90 | 0.43 | 1405 | 1493 | 0.86 |
| 2020/21 | OGC Nice | Ligue 1 | AM | 30 | 1908 | 56% | 4 | 5 | 0.42 | 0.44 | 1432 | 1398 | 0.75 |
| 2019/20 | OGC Nice | Ligue 1 | LW | 22 | 1633 | 65% | 1 | 1 | 0.11 | 0.22 | 1424 | 1456 | 0.82 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Dfb Pokal | FC Augsburg | 1 | 13 | 0 | 0 | — |
| 2024/25 | Dfb Pokal | FC Augsburg | 3 | 215 | 1 | 0 | — |
| 2022/23 | Uefa Conference League Qualifying | OGC Nice | 1 | 77 | 1 | 0 | 1522 |
| 2020/21 | Uefa Europa League | OGC Nice | 3 | 175 | 1 | 0 | 1479 |
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 |
|---|---|---|---|---|
| Fredy Guarín Serie A · 2013 | 27 | €18.0M | €12.0M | fell |
| Bryan Ruiz Premier League · 2013 | 28 | €13.0M | €5.0M | fell |
| Senad Lulic Serie A · 2014 | 28 | €10.0M | €9.5M | flat |
| Adem Ljajic Serie A · 2018 | 27 | €13.0M | €9.0M | fell |
| Hernanes Serie A · 2014 | 29 | €22.0M | €8.0M | fell |
| Badou Ndiaye Super Lig · 2018 | 28 | €15.0M | €6.8M | fell |
| Santi Comesaña Laliga · 2023 | 27 | €7.5M | €8.0M | flat |
| Mattia Zaccagni Serie A · 2021 | 26 | €15.0M | €30.0M | rose |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 30 Aug 2024 | Nice | Augsburg | Free / loan | €3.5M |
| 30 Jun 2023 | Lens | Nice | Free / loan | €4.5M |
| 31 Aug 2022 | Nice | Lens | Free / loan | €6.0M |
| 29 Aug 2019 | FC Lorient | Nice | €13.0M | €7.5M |
| 1 Jul 2016 | Lorient B | FC Lorient | Unknown | Data unavailable |
| 21 Dec 2015 | FC Lorient U19 | Lorient B | Unknown | Data unavailable |
| 1 Jul 2015 | FC Lorient U17 | FC Lorient U19 | Unknown | Data unavailable |
| 1 Jul 2014 | US Torcy U17 | FC Lorient U17 | Free / loan | Data unavailable |
| 1 Jul 2013 | US Torcy Yth. | US Torcy 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.