Chrislain Matsima
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Chrislain Matsima's performance-implied value at EUR 4.4M-17.0M, below the estimated acquisition range of EUR 16.8M-29.6M. Its 24-month market value projection is EUR 9.4M-25.8M. Confidence is medium: no event-level data (xG, progressive actions) is available from the current free source, and injury history is unavailable.
Bargain Index: 12
What drives the score. Not a black box: each component and its level.
| Performance | Above average | 64.9th pct among DEF peers (age-neutral) |
| Age | Neutral | 24.1 years |
| Acquisition cost | Neutral | est. €22.0M vs market €22.0M |
| Expected appreciation | Very low | -31% over ~2 years (model) |
| Value gap | Very negative | weak predictor on its own |
| Development | Moderate | |
| 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 | Moderate | |
| 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 1268 evaluated DEF players with 900+ minutes.
Performance (last season, league)
- Minutes
- 1490 (49% of available)
- Goals + assists / 90
- 0.12
- Context-adjusted G+A / 90
- 0.10
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 65 (Above 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)
- 1421
- Opponent strength
- 1493
- 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
- Age > 23
- Resale range (24m)
- €9.4M – €25.8M
Trajectory drivers: minutes share down 35 pts.
Historical comparables (8): median 2-year value change -13% (IQR -55% to +51%).
Risk profile
Overall: Moderate
- ⚠Limited sample: 1490 league minutes last season.
- ⚠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 | FC Augsburg | Bundesliga | CB | 18 | 1490 | 49% | 1 | 1 | 0.12 | 0.10 | 1493 | 1421 | 0.94 |
| 2024/25 | FC Augsburg | Bundesliga | CB | 30 | 2551 | 83% | 1 | 1 | 0.07 | 0.08 | 1513 | 1404 | 0.94 |
| 2023/24 | Clermont Foot 63 | Ligue 1 | CB | 14 | 1179 | 39% | 1 | 0 | 0.08 | 0.10 | 1499 | 1315 | 0.87 |
| 2023/24 | AS Monaco | Ligue 1 | CB | 6 | 297 | 10% | 0 | 1 | 0.30 | 0.11 | 1427 | 1573 | 0.87 |
| 2022/23 | AS Monaco | Ligue 1 | CB | 8 | 445 | 13% | 0 | 1 | 0.20 | 0.09 | 1425 | 1485 | 0.82 |
| 2022/23 | FC Lorient | Ligue 1 | CB | 6 | 223 | 7% | 0 | 0 | 0.00 | 0.06 | 1434 | 1396 | 0.82 |
| 2021/22 | AS Monaco | Ligue 1 | CB | 7 | 129 | 4% | 0 | 0 | 0.00 | 0.05 | 1412 | 1599 | 0.86 |
| 2020/21 | AS Monaco | Ligue 1 | CB | 9 | 349 | 10% | 0 | 0 | 0.00 | 0.05 | 1518 | 1549 | 0.75 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Dfb Pokal | FC Augsburg | 2 | 170 | 0 | 0 | — |
| 2024/25 | Dfb Pokal | FC Augsburg | 3 | 300 | 0 | 0 | — |
| 2022/23 | Uefa Europa League | AS Monaco | 2 | 71 | 0 | 0 | 1557 |
| 2021/22 | Uefa Europa League | AS Monaco | 3 | 136 | 0 | 0 | 1377 |
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 |
|---|---|---|---|---|
| Joel Matip Bundesliga · 2015 | 24 | €14.0M | €25.0M | rose |
| Antonio Rüdiger Bundesliga · 2015 | 22 | €10.0M | €25.0M | rose |
| Alidu Seidu Ligue 1 · 2024 | 24 | €9.0M | €6.0M | fell |
| Pol Lirola Ligue 1 · 2021 | 24 | €9.0M | €2.0M | fell |
| Malang Sarr Ligue 1 · 2020 | 21 | €16.0M | €8.0M | fell |
| Timo Baumgartl Bundesliga · 2019 | 23 | €9.0M | €3.0M | fell |
| Nikola Maksimović Serie A · 2016 | 25 | €7.0M | €8.0M | flat |
| John Brooks Bundesliga · 2016 | 23 | €7.0M | €10.0M | rose |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 1 Jul 2025 | Monaco | Augsburg | €5.0M | €22.0M |
| 30 Jun 2025 | Augsburg | Monaco | Free / loan | €22.0M |
| 30 Aug 2024 | Monaco | Augsburg | Free / loan | €7.0M |
| 30 Jun 2024 | Clermont Foot | Monaco | Free / loan | €7.0M |
| 1 Feb 2024 | Monaco | Clermont Foot | Free / loan | €7.0M |
| 31 Jan 2023 | FC Lorient | Monaco | Free / loan | €4.0M |
| 16 Aug 2022 | Monaco | FC Lorient | Free / loan | €5.0M |
| 1 Jul 2020 | Monaco B | Monaco | Unknown | Data unavailable |
| 1 Jul 2019 | Monaco U19 | Monaco B | Unknown | Data unavailable |
| 1 Jul 2018 | AS Monaco U17 | Monaco U19 | Unknown | Data unavailable |
| 1 Jul 2017 | Racing CFF Yth. | AS Monaco U17 | 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.