Josip Brekalo
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Josip Brekalo's performance-implied value at EUR 0.8M-2.3M, above the estimated acquisition range of EUR 0.7M-2.0M. Its 24-month market value projection is EUR 0.9M-2.5M. Context-adjusted goal contributions are 0.96x the positional average in the league (483 minutes, league coefficient 0.95). Confidence is low: 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: not assigned
What drives the score. Not a black box: each component and its level.
Insufficient sample (< 900 league minutes)
| Performance | Average | 36.6th pct among ATT peers (age-neutral) |
| Age | Unfavorable | 28 years |
| Acquisition cost | Very favorable | est. €953k vs market €2.5M |
| Expected appreciation | Very low | -41% over ~2 years (model) |
| Value gap | Large | weak predictor on its own |
| Development | Low | |
| League translation | Big-five league | league coefficient 0.95 |
| Tactical fit | Not evaluated | Requires event/role data not available from the current free source. |
| Risk | 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 901 evaluated ATT players with 900+ minutes.
Performance (last season, league)
- Minutes
- 483 (14% of available)
- Goals + assists / 90
- 0.00
- Context-adjusted G+A / 90
- 0.39
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 37 (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
- 0.95 (rank 2)
- Team strength (Elo)
- 1294
- Opponent strength
- 1460
- 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)
- €865k – €2.5M
Trajectory drivers: minutes share down 27 pts; changed club; league level up (+233 Elo).
Historical comparables (8): median 2-year value change -54% (IQR -63% to +12%).
Risk profile
Overall: High
- ▲Small sample: 483 league minutes last season.
- ⚠Contract ends in 12 months: cheaper, but competition and wage demands likely.
- ⚠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 | Real Oviedo | Laliga | LW | 14 | 483 | 14% | 0 | 0 | 0.00 | 0.39 | 1460 | 1294 | 0.95 |
| 2024/25 | Kasimpasa | Super Lig | LW | 23 | 1317 | 41% | 4 | 2 | 0.41 | 0.43 | 1291 | 1268 | 0.39 |
| 2023/24 | ACF Fiorentina | Serie A | LW | 11 | 654 | 19% | 1 | 0 | 0.14 | 0.24 | 1449 | 1583 | 0.98 |
| 2022/23 | VfL Wolfsburg | Bundesliga | LW | 6 | 269 | 9% | 0 | 1 | 0.33 | 0.39 | 1546 | 1525 | 1.04 |
| 2022/23 | ACF Fiorentina | Serie A | LW | 6 | 227 | 7% | 0 | 0 | 0.00 | 0.24 | 1395 | 1597 | 0.94 |
| 2021/22 | Torino FC | Serie A | SS | 32 | 2293 | 67% | 7 | 2 | 0.35 | 0.58 | 1504 | 1423 | 0.89 |
| 2021/22 | VfL Wolfsburg | Bundesliga | LW | 1 | 20 | 1% | 0 | 1 | 4.50 | 0.37 | 1432 | 1495 | 1.05 |
| 2020/21 | VfL Wolfsburg | Bundesliga | LW | 29 | 1824 | 60% | 7 | 3 | 0.49 | 0.37 | 1524 | 1613 | 1.06 |
| 2019/20 | VfL Wolfsburg | Bundesliga | LW | 30 | 1676 | 55% | 3 | 4 | 0.38 | 0.34 | 1517 | 1562 | 1.06 |
| 2018/19 | VfL Wolfsburg | Bundesliga | LW | 25 | 1414 | 46% | 3 | 3 | 0.38 | 0.40 | 1522 | 1542 | 1.05 |
| 2017/18 | VfL Wolfsburg | Bundesliga | LW | 13 | 834 | 27% | 3 | 1 | 0.43 | 0.47 | 1496 | 1434 | 1.04 |
| 2017/18 | VfB Stuttgart | Bundesliga | LW | 14 | 726 | 24% | 1 | 1 | 0.25 | 0.44 | 1488 | 1506 | 1.04 |
| 2016/17 | VfL Wolfsburg | Bundesliga | LW | 4 | 76 | 2% | 0 | 0 | 0.00 | 0.34 | 1523 | 1490 | 1.06 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Copa Del Rey | Real Oviedo | 1 | 56 | 1 | 0 | — |
| 2025/26 | Dfb Pokal | Hertha BSC | 1 | 40 | 0 | 0 | — |
| 2023/24 | Supercoppa Italiana | ACF Fiorentina | 1 | 57 | 0 | 0 | 1630 |
| 2023/24 | Uefa Conference League Qualifying | ACF Fiorentina | 1 | 57 | 0 | 0 | 1455 |
| 2023/24 | Italy Cup | ACF Fiorentina | 1 | 46 | 0 | 0 | — |
| 2022/23 | Dfb Pokal | VfL Wolfsburg | 1 | 45 | 0 | 1 | — |
| 2022/23 | Italy Cup | ACF Fiorentina | 1 | 5 | 0 | 0 | — |
| 2021/22 | Dfb Pokal | VfL Wolfsburg | 1 | 74 | 1 | 0 | — |
| 2021/22 | Italy Cup | Torino FC | 1 | 70 | 0 | 0 | — |
| 2020/21 | Uefa Europa League Qualifying | VfL Wolfsburg | 2 | 153 | 0 | 1 | 1364 |
| 2020/21 | Dfb Pokal | VfL Wolfsburg | 2 | 64 | 0 | 0 | — |
| 2019/20 | Uefa Europa League | VfL Wolfsburg | 9 | 704 | 3 | 3 | 1527 |
| 2019/20 | Dfb Pokal | VfL Wolfsburg | 2 | 119 | 1 | 0 | — |
| 2018/19 | Dfb Pokal | VfL Wolfsburg | 2 | 114 | 0 | 1 | — |
| 2017/18 | Dfb Pokal | VfB Stuttgart | 3 | 228 | 1 | 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 |
|---|---|---|---|---|
| Lacina Traore Ligue 1 · 2018 | 28 | €2.5M | €725k | fell |
| Antonino Ragusa Serie A · 2018 | 28 | €1.5M | €800k | fell |
| Anthony Le Tallec Ligue 1 · 2014 | 30 | €1.8M | €700k | fell |
| Mohammed Abdellaoue Bundesliga · 2014 | 29 | €3.0M | €600k | fell |
| Marko Pjaca Serie A · 2023 | 28 | €1.7M | €2.7M | rose |
| Gonçalo Paciência Bundesliga · 2021 | 27 | €5.0M | €2.0M | fell |
| Gaëtan Courtet Ligue 1 · 2015 | 26 | €1.5M | €1.5M | flat |
| Ádám Szalai Bundesliga · 2016 | 29 | €1.5M | €3.0M | rose |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 2 Feb 2026 | Real Oviedo | Hertha BSC | Free / loan | €2.5M |
| 21 Aug 2025 | Fiorentina | Real Oviedo | Free / loan | €3.3M |
| 30 Jun 2025 | Kasimpasa | Fiorentina | Free / loan | €3.3M |
| 6 Sept 2024 | Fiorentina | Kasimpasa | Free / loan | €3.5M |
| 30 Jun 2024 | Hajduk Split | Fiorentina | Free / loan | €3.5M |
| 29 Jan 2024 | Fiorentina | Hajduk Split | Free / loan | €4.5M |
| 28 Jan 2023 | Wolfsburg | Fiorentina | €1.7M | €7.5M |
| 30 Jun 2022 | Torino | Wolfsburg | Free / loan | €15.0M |
| 31 Aug 2021 | Wolfsburg | Torino | Free / loan | €12.0M |
| 31 Dec 2017 | Stuttgart | Wolfsburg | Free / loan | €3.5M |
| 31 Jan 2017 | Wolfsburg | Stuttgart | Free / loan | €4.0M |
| 1 Jul 2016 | Dinamo Zagreb | Wolfsburg | €10.0M | €1.0M |
| 11 Jan 2016 | Din. Zagreb II | Dinamo Zagreb | Unknown | Data unavailable |
| 1 Jul 2015 | Din. Zagreb U17 | Din. Zagreb II | Unknown | Data unavailable |
| 1 Jul 2013 | D. Zagreb Yth. | Din. Zagreb 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.