
Paulo Dybala
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Paulo Dybala's performance-implied value at EUR 4.8M-12.7M, above the estimated acquisition range of EUR 1.8M-6.0M. Its 24-month market value projection is EUR 1.3M-3.3M. Context-adjusted goal contributions are 0.86x the positional average in the league (1356 minutes, league coefficient 0.93). Confidence is medium: no event-level data (xG, progressive actions) is available from the current free source, and injury history is unavailable.
Acquisition note: Contract end date unavailable: range widened by 15% each side.
Bargain Index: 3
What drives the score. Not a black box: each component and its level.
| Performance | High | 88.3th pct among ATT peers (age-neutral) |
| Age | Unfavorable | 32.6 years |
| Acquisition cost | Favorable | est. €3.7M vs market €5.0M |
| Expected appreciation | Very low | -59% over ~2 years (model) |
| Value gap | Very large | weak predictor on its own |
| Development | Low | |
| League translation | Big-five league | league coefficient 0.93 |
| Tactical fit | Not evaluated | Requires event/role data not available from the current free source. |
| Risk | High | |
| 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
- 1356 (40% of available)
- Goals + assists / 90
- 0.60
- Context-adjusted G+A / 90
- 0.46
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 88 (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
- 0.93 (rank 4)
- Team strength (Elo)
- 1638
- Opponent strength
- 1486
- 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)
- €1.3M – €3.3M
Historical comparables (8): median 2-year value change -69% (IQR -79% to -64%).
Risk profile
Overall: High
- ▲Age 33: resale value typically declines.
- ⚠Limited sample: 1356 league minutes last season.
- ⚠Played under 40% of available league minutes (injury data unavailable, cause unknown).
- ⓘContract end date unavailable (or stale in source).
- ⓘ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 | Associazione Sportiva Roma | Serie A | SS | 22 | 1356 | 40% | 2 | 7 | 0.60 | 0.46 | 1486 | 1638 | 0.93 |
| 2024/25 | Associazione Sportiva Roma | Serie A | SS | 24 | 1421 | 42% | 6 | 3 | 0.57 | 0.49 | 1490 | 1668 | 0.99 |
| 2023/24 | Associazione Sportiva Roma | Serie A | SS | 28 | 1974 | 58% | 13 | 9 | 1.00 | 0.78 | 1470 | 1618 | 0.98 |
| 2022/23 | Associazione Sportiva Roma | Serie A | SS | 25 | 1749 | 51% | 12 | 7 | 0.98 | 0.79 | 1433 | 1578 | 0.94 |
| 2021/22 | Juventus FC | Serie A | SS | 29 | 2072 | 61% | 10 | 5 | 0.65 | 0.46 | 1461 | 1623 | 0.89 |
| 2020/21 | Juventus FC | Serie A | SS | 20 | 1134 | 33% | 4 | 3 | 0.56 | 0.32 | 1406 | 1698 | 0.90 |
| 2019/20 | Juventus FC | Serie A | ST | 33 | 2165 | 63% | 11 | 11 | 0.91 | 0.40 | 1400 | 1643 | 0.82 |
| 2018/19 | Juventus FC | Serie A | SS | 30 | 2137 | 62% | 5 | 2 | 0.29 | 0.19 | 1438 | 1701 | 0.78 |
| 2017/18 | Juventus FC | Serie A | SS | 33 | 2356 | 69% | 22 | 5 | 1.03 | 0.49 | 1444 | 1820 | 0.86 |
| 2016/17 | Juventus FC | Serie A | SS | 31 | 2153 | 63% | 11 | 8 | 0.79 | 0.36 | 1446 | 1832 | 0.88 |
| 2015/16 | Juventus FC | Serie A | ST | 34 | 2464 | 72% | 19 | 7 | 0.95 | 0.47 | 1463 | 1808 | 0.95 |
| 2014/15 | Palermo FC | Serie A | ST | 34 | 2964 | 87% | 13 | 10 | 0.70 | 0.72 | 1473 | 1426 | 0.93 |
| 2012/13 | Palermo FC | Serie A | SS | 27 | 1252 | 37% | 3 | 0 | 0.22 | 0.44 | 1420 | 1367 | 0.88 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Uefa Europa League | Associazione Sportiva Roma | 4 | 206 | 1 | 1 | 1487 |
| 2025/26 | Italy Cup | Associazione Sportiva Roma | 1 | 32 | 0 | 0 | — |
| 2024/25 | Uefa Europa League | Associazione Sportiva Roma | 11 | 610 | 2 | 1 | 1565 |
| 2024/25 | Italy Cup | Associazione Sportiva Roma | 1 | 90 | 0 | 0 | — |
| 2023/24 | Uefa Europa League | Associazione Sportiva Roma | 9 | 607 | 2 | 1 | 1631 |
| 2023/24 | Italy Cup | Associazione Sportiva Roma | 2 | 90 | 1 | 0 | — |
| 2022/23 | Uefa Europa League | Associazione Sportiva Roma | 11 | 667 | 5 | 1 | 1581 |
| 2022/23 | Italy Cup | Associazione Sportiva Roma | 2 | 90 | 1 | 0 | — |
| 2021/22 | Uefa Champions League | Juventus FC | 5 | 256 | 3 | 1 | 1591 |
| 2021/22 | Italy Cup | Juventus FC | 4 | 241 | 2 | 0 | — |
| 2021/22 | Supercoppa Italiana | Juventus FC | 1 | 46 | 0 | 0 | 1771 |
| 2020/21 | Uefa Champions League | Juventus FC | 5 | 213 | 1 | 0 | 1601 |
| 2020/21 | Italy Cup | Juventus FC | 1 | 16 | 0 | 0 | — |
| 2019/20 | Italy Cup | Juventus FC | 4 | 345 | 2 | 1 | — |
| 2019/20 | Uefa Champions League | Juventus FC | 8 | 310 | 3 | 2 | 1601 |
| 2019/20 | Supercoppa Italiana | Juventus FC | 1 | 90 | 1 | 0 | 1539 |
| 2018/19 | Uefa Champions League | Juventus FC | 9 | 518 | 5 | 0 | 1654 |
| 2018/19 | Supercoppa Italiana | Juventus FC | 1 | 90 | 0 | 0 | 1542 |
| 2018/19 | Italy Cup | Juventus FC | 2 | 75 | 0 | 0 | — |
| 2017/18 | Uefa Champions League | Juventus FC | 8 | 661 | 1 | 0 | 1695 |
| 2017/18 | Italy Cup | Juventus FC | 4 | 271 | 1 | 2 | — |
| 2017/18 | Supercoppa Italiana | Juventus FC | 1 | 90 | 2 | 0 | 1537 |
| 2016/17 | Uefa Champions League | Juventus FC | 11 | 797 | 4 | 0 | 1682 |
| 2016/17 | Italy Cup | Juventus FC | 5 | 367 | 4 | 1 | — |
| 2016/17 | Supercoppa Italiana | Juventus FC | 1 | 53 | 0 | 0 | 1556 |
| 2015/16 | Uefa Champions League | Juventus FC | 7 | 419 | 1 | 0 | 1718 |
| 2015/16 | Italy Cup | Juventus FC | 4 | 170 | 2 | 0 | — |
| 2015/16 | Supercoppa Italiana | Juventus FC | 1 | 28 | 1 | 0 | 1586 |
| 2014/15 | Italy Cup | Palermo FC | 1 | 90 | 0 | 0 | — |
| 2012/13 | Italy Cup | Palermo FC | 1 | 32 | 0 | 0 | — |
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 |
|---|---|---|---|---|
| Josip Ilicic Serie A · 2021 | 33 | €6.0M | €300k | fell |
| Stephan El Shaarawy Serie A · 2024 | 32 | €5.0M | €2.4M | fell |
| Luis Muriel Serie A · 2023 | 32 | €5.0M | €1.2M | fell |
| Dries Mertens Serie A · 2022 | 35 | €4.0M | €1.8M | fell |
| Javier Saviola Laliga · 2013 | 32 | €3.0M | €1.0M | fell |
| Andrea Belotti Serie A · 2024 | 31 | €5.0M | €1.5M | fell |
| Felipe Caicedo Serie A · 2020 | 32 | €4.8M | €1.5M | fell |
| Sergio Floccari Serie A · 2013 | 32 | €3.5M | €500k | fell |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 20 Jul 2022 | Juventus | Roma | Free / loan | €35.0M |
| 1 Jul 2015 | US Palermo | Juventus | €41.0M | €28.0M |
| 20 Jul 2012 | Instituto ACC | US Palermo | €11.9M | €2.0M |
| 1 Jul 2011 | Instituto U19 | Instituto ACC | 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.