Giorgi Gocholeishvili
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Giorgi Gocholeishvili's performance-implied value at EUR 1.4M-2.8M, above the estimated acquisition range of EUR 0.9M-2.6M. Its 24-month market value projection is EUR 1.0M-3.0M. Context-adjusted goal contributions are 0.84x the positional average in the league (1009 minutes, league coefficient 0.94). Confidence is medium: no event-level data (xG, progressive actions) is available from the current free source, and injury history is unavailable.
Bargain Index: 53
What drives the score. Not a black box: each component and its level.
| Performance | Average | 43.6th pct among MID peers (age-neutral) |
| Age | Neutral | 25.4 years |
| Acquisition cost | Neutral | est. €1.7M vs market €2.0M |
| Expected appreciation | Low | -11% over ~2 years (model) |
| Value gap | Small | weak predictor on its own |
| Development | Low | |
| 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 1163 evaluated MID players with 900+ minutes.
Performance (last season, league)
- Minutes
- 1009 (33% of available)
- Goals + assists / 90
- 0.09
- Context-adjusted G+A / 90
- 0.19
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 44 (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 30)
- Team strength (Elo)
- 1383
- Opponent strength
- 1477
- 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)
- €953k – €3.0M
Trajectory drivers: minutes share down 21 pts; changed club; league level up (+205 Elo); role change RB -> RM.
Historical comparables (8): median 2-year value change -35% (IQR -41% to +17%).
Risk profile
Overall: Moderate
- ⚠Limited sample: 1009 league minutes last season.
- ⚠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 | Hamburger SV | Bundesliga | RM | 24 | 933 | 30% | 0 | 1 | 0.10 | 0.19 | 1477 | 1380 | 0.94 |
| 2025/26 | FC Shakhtar Donetsk | Premier Liga | RB | 1 | 76 | 3% | 0 | 0 | 0.00 | 0.06 | 1017 | 1420 | 0.25 |
| 2024/25 | FC Copenhagen | Superliga | RB | 15 | 1075 | 54% | 1 | 2 | 0.25 | 0.11 | 1275 | 1399 | 0.38 |
| 2023/24 | FC Shakhtar Donetsk | Premier Liga | RB | 18 | 1151 | 43% | 0 | 2 | 0.16 | 0.09 | 1255 | 1497 | 0.34 |
| 2022/23 | FC Shakhtar Donetsk | Premier Liga | RB | 13 | 777 | 29% | 1 | 0 | 0.12 | 0.07 | 1227 | 1546 | 0.38 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Dfb Pokal | Hamburger SV | 3 | 218 | 0 | 0 | — |
| 2025/26 | Uefa Europa League Qualifying | FC Shakhtar Donetsk | 3 | 46 | 0 | 0 | 1300 |
| 2024/25 | Uefa Conference League Qualifying | FC Copenhagen | 3 | 230 | 0 | 0 | 1342 |
| 2024/25 | Oddset Pokalen | FC Copenhagen | 2 | 48 | 0 | 0 | — |
| 2023/24 | Uefa Champions League | FC Shakhtar Donetsk | 4 | 284 | 0 | 1 | 1643 |
| 2023/24 | Ukrainian Cup | FC Shakhtar Donetsk | 1 | 68 | 0 | 0 | — |
| 2023/24 | Uefa Europa League | FC Shakhtar Donetsk | 1 | 13 | 0 | 0 | 1547 |
| 2022/23 | Uefa Conference League Qualifying | Iberia 1999 Tbilisi | 4 | 390 | 0 | 0 | 1333 |
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 |
|---|---|---|---|---|
| Isaac Cofie Serie A · 2017 | 26 | €1.5M | €1.0M | fell |
| Jérémy Pied Ligue 1 · 2014 | 25 | €2.5M | €3.5M | rose |
| Vincent Pajot Ligue 1 · 2014 | 24 | €2.0M | €2.5M | rose |
| Afriyie Acquah Serie A · 2017 | 25 | €2.8M | €1.8M | fell |
| Liam Henderson Serie A · 2023 | 27 | €2.5M | €1.4M | fell |
| Yacouba Sylla Ligue 1 · 2017 | 27 | €1.8M | €700k | fell |
| Mehdi Abeid Ligue 1 · 2018 | 26 | €1.8M | €2.0M | flat |
| Adrien Regattin Ligue 1 · 2016 | 25 | €2.0M | €1.2M | fell |
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 | Hamburg | Shakhtar D. | Free / loan | €2.0M |
| 7 Aug 2025 | Shakhtar D. | Hamburg | Free / loan | €2.5M |
| 30 Jun 2025 | Copenhagen | Shakhtar D. | Free / loan | €2.5M |
| 29 Jul 2024 | Shakhtar D. | Copenhagen | Free / loan | €2.5M |
| 1 Jan 2023 | Saburtalo | Shakhtar D. | €1.0M | €900k |
| 1 Jan 2021 | Saburtalo Acad. | Saburtalo | 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.