Mason Greenwood
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Mason Greenwood's performance-implied value at EUR 26.5M-71.8M, below the estimated acquisition range of EUR 40.8M-67.2M. Its 24-month market value projection is EUR 24.9M-57.8M. Context-adjusted goal contributions are 1.39x the positional average in the league (2471 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.
Bargain Index: 11
What drives the score. Not a black box: each component and its level.
| Performance | Elite | 93th pct among ATT peers (age-neutral) |
| Age | Neutral | 24.7 years |
| Acquisition cost | Neutral | est. €54.8M vs market €55.0M |
| Expected appreciation | Very low | -33% over ~2 years (model) |
| Value gap | Very negative | weak predictor on its own |
| Development | Moderate | |
| 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 | 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 900 evaluated ATT players with 900+ minutes.
Performance (last season, league)
- Minutes
- 2471 (81% of available)
- Goals + assists / 90
- 0.84
- Context-adjusted G+A / 90
- 0.55
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 93 (Elite)
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)
- 1504
- Opponent strength
- 1454
- Possession, role
- Data unavailable
League strength 1.00 = average club of the big-five leagues. Elo includes continental matches.
Potential
- Development
- Moderate
- Trajectory
- stable
- Breakout probability
- Age > 23
- Resale range (24m)
- €24.9M – €57.8M
Historical comparables (8): median 2-year value change -31% (IQR -62% to -15%).
Risk profile
Overall: Low
- ⓘ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 | Olympique Marseille | Ligue 1 | RW | 32 | 2471 | 81% | 16 | 7 | 0.84 | 0.55 | 1454 | 1504 | 0.88 |
| 2024/25 | Olympique Marseille | Ligue 1 | RW | 34 | 2818 | 92% | 21 | 6 | 0.86 | 0.51 | 1426 | 1557 | 0.88 |
| 2023/24 | Getafe CF | Laliga | RW | 33 | 2668 | 78% | 8 | 6 | 0.47 | 0.57 | 1473 | 1415 | 1.00 |
| 2021/22 | Manchester United | Premier League | RW | 18 | 1278 | 37% | 5 | 1 | 0.42 | 0.29 | 1550 | 1609 | 1.17 |
| 2020/21 | Manchester United | Premier League | RW | 31 | 1826 | 53% | 7 | 2 | 0.44 | 0.29 | 1538 | 1741 | 1.19 |
| 2019/20 | Manchester United | Premier League | RW | 31 | 1313 | 38% | 10 | 1 | 0.75 | 0.44 | 1536 | 1720 | 1.14 |
| 2018/19 | Manchester United | Premier League | RW | 2 | 105 | 3% | 0 | 0 | 0.00 | 0.20 | 1365 | 1669 | 1.22 |
| 2018/19 | Arsenal FC | Premier League | RW | 1 | 10 | 0% | 0 | 0 | 0.00 | 0.48 | 1760 | 1733 | 1.22 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Uefa Champions League | Olympique Marseille | 8 | 671 | 3 | 1 | 1631 |
| 2025/26 | Trophee Des Champions | Olympique Marseille | 1 | 90 | 1 | 0 | 1832 |
| 2023/24 | Copa Del Rey | Getafe CF | 3 | 240 | 2 | 0 | — |
| 2021/22 | Uefa Champions League | Manchester United | 4 | 304 | 1 | 1 | 1636 |
| 2021/22 | Fa Cup | Manchester United | 1 | 90 | 0 | 0 | — |
| 2020/21 | Uefa Europa League | Manchester United | 9 | 710 | 1 | 0 | 1592 |
| 2020/21 | Fa Cup | Manchester United | 4 | 311 | 2 | 1 | — |
| 2020/21 | Uefa Champions League | Manchester United | 5 | 209 | 1 | 2 | 1659 |
| 2019/20 | Uefa Europa League | Manchester United | 9 | 640 | 5 | 2 | 1537 |
| 2019/20 | Fa Cup | Manchester United | 5 | 335 | 1 | 0 | — |
| 2018/19 | Uefa Champions League | Paris Saint-Germain | 1 | 3 | 0 | 0 | 1732 |
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 |
|---|---|---|---|---|
| Florian Thauvin Ligue 1 · 2019 | 26 | €45.0M | €17.0M | fell |
| Mauro Icardi Serie A · 2018 | 25 | €95.0M | €60.0M | fell |
| Randal Kolo Muani Bundesliga · 2023 | 25 | €80.0M | €30.0M | fell |
| Alexandre Lacazette Ligue 1 · 2015 | 24 | €30.0M | €40.0M | rose |
| Edinson Cavani Serie A · 2013 | 26 | €55.0M | €42.0M | fell |
| Krzysztof Piatek Serie A · 2019 | 24 | €40.0M | €15.0M | fell |
| Dušan Vlahović Serie A · 2022 | 22 | €85.0M | €65.0M | fell |
| Andrea Belotti Serie A · 2017 | 24 | €30.0M | €35.0M | flat |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 18 Jul 2024 | Man Utd | Marseille | €26.0M | €25.0M |
| 30 Jun 2024 | Getafe | Man Utd | Free / loan | €25.0M |
| 1 Sept 2023 | Man Utd | Getafe | Free / loan | €5.0M |
| 1 Jul 2019 | Man Utd U18 | Man Utd | Unknown | Data unavailable |
| 1 Jul 2017 | Man Utd Youth | Man Utd U18 | 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.