Radoslaw Majecki
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Radoslaw Majecki's performance-implied value at EUR 1.6M-3.8M, above the estimated acquisition range of EUR 1.2M-3.3M. Its 24-month market value projection is EUR 0.9M-3.2M. 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 | 54.6th pct among GK peers (age-neutral) |
| Age | Neutral | 26.6 years |
| Acquisition cost | Neutral | est. €2.2M vs market €2.5M |
| Expected appreciation | Very low | -29% over ~2 years (model) |
| Value gap | Small | 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 | 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 285 evaluated GK players with 900+ minutes.
Performance (last season, league)
- Minutes
- 865 (28% of available)
- Goals + assists / 90
- 0.00
- Context-adjusted G+A / 90
- 0.00
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 55 (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)
- 1407
- Opponent strength
- 1490
- Possession, role
- Data unavailable
League strength 1.00 = average club of the big-five leagues. Elo includes continental matches.
Potential
- Development
- Low
- Trajectory
- declining
- Breakout probability
- Age > 23
- Resale range (24m)
- €939k – €3.2M
Trajectory drivers: minutes share down 16 pts; changed club; team strength down (-163 Elo).
Historical comparables (8): median 2-year value change -29% (IQR -45% to +7%).
Risk profile
Overall: Very High
- ▲Small sample: 865 league minutes last season.
- ⚠No continental-competition minutes last season.
- ⚠Projection range wider than for most 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 | Stade Brestois 29 | Ligue 1 | GK | 10 | 865 | 28% | 0 | 0 | 0.00 | 0.00 | 1490 | 1407 | 0.88 |
| 2024/25 | AS Monaco | Ligue 1 | GK | 15 | 1350 | 44% | 0 | 0 | 0.00 | 0.00 | 1455 | 1571 | 0.88 |
| 2023/24 | AS Monaco | Ligue 1 | GK | 12 | 1080 | 35% | 0 | 0 | 0.00 | 0.00 | 1482 | 1573 | 0.87 |
| 2022/23 | Cercle Brugge | Jupiler Pro League | GK | 28 | 2475 | 81% | 0 | 0 | 0.00 | 0.00 | 1316 | 1373 | 0.58 |
| 2020/21 | AS Monaco | Ligue 1 | GK | 1 | 90 | 3% | 0 | 0 | 0.00 | 0.01 | 1424 | 1549 | 0.75 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2024/25 | Uefa Champions League | AS Monaco | 8 | 720 | 0 | 0 | 1657 |
| 2021/22 | Uefa Champions League Qualifying | AS Monaco | 1 | 90 | 0 | 0 | 1555 |
| 2021/22 | Uefa Europa League | AS Monaco | 1 | 90 | 0 | 0 | 1332 |
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 |
|---|---|---|---|---|
| Gianluca Curci Serie A · 2013 | 28 | €2.0M | €700k | fell |
| Álvaro Fernández Laliga · 2023 | 25 | €2.5M | €2.5M | flat |
| Wladimiro Falcone Serie A · 2022 | 27 | €3.0M | €5.0M | rose |
| Mathieu Michel Ligue 1 · 2018 | 27 | €2.0M | €650k | fell |
| Guy Ndy Assembé Ligue 1 · 2013 | 27 | €1.3M | €800k | fell |
| Iván Villar Laliga · 2024 | 27 | €1.2M | €900k | fell |
| Johan Dahlin Super Lig · 2014 | 28 | €1.5M | €1.0M | fell |
| Etrit Berisha Serie A · 2014 | 25 | €3.0M | €4.0M | rose |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 30 Jun 2026 | Stade Brestois | Monaco | Free / loan | €2.5M |
| 9 Aug 2025 | Monaco | Stade Brestois | Free / loan | €6.0M |
| 30 Jun 2023 | Cercle Brugge | Monaco | Free / loan | €2.0M |
| 20 Jul 2022 | Monaco | Cercle Brugge | Free / loan | €3.0M |
| 30 Jun 2020 | Legia Warszawa | Monaco | Free / loan | €4.5M |
| 30 Jan 2020 | Monaco | Legia Warszawa | Free / loan | €5.0M |
| 29 Jan 2020 | Legia Warszawa | Monaco | €7.0M | €5.0M |
| 30 Jun 2018 | Stal Mielec | Legia Warszawa | Free / loan | €200k |
| 19 Jul 2017 | Legia Warszawa | Stal Mielec | Free / loan | €150k |
| 1 Jul 2016 | Legia II | Legia Warszawa | Unknown | €100k |
| 10 Feb 2016 | Legia U19 | Legia II | Unknown | Data unavailable |
| 1 Jul 2014 | KSZO U19 | Legia U19 | 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.