Danyil Sukhoruchko
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Danyil Sukhoruchko's performance-implied value at EUR 0.3M-0.4M, above the estimated acquisition range of EUR 0.1M-0.3M. Its 24-month market value projection is EUR 0.1M-0.3M. Context-adjusted goal contributions are 1.20x the positional average in the league (1016 minutes, league coefficient 0.25). 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: 84
What drives the score. Not a black box: each component and its level.
| Performance | Below average | 3.1th pct among ATT peers (age-neutral) |
| Age | Neutral | 26.4 years |
| Acquisition cost | Favorable | est. €179k vs market €250k |
| Expected appreciation | Neutral | +4% over ~2 years (model) |
| Value gap | Very large | weak predictor on its own |
| Development | Low | |
| League translation | Uncertain | league coefficient 0.25 |
| 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
- 1016 (38% of available)
- Goals + assists / 90
- 0.18
- Context-adjusted G+A / 90
- 0.61
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 3 (Below 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
- 0.25 (rank 30)
- Team strength (Elo)
- 909
- Opponent strength
- 1193
- 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)
- €132k – €300k
Trajectory drivers: minutes share down 41 pts; changed club; team strength down (-131 Elo); relative output up 145% vs positional peers.
Historical comparables (8): median 2-year value change +19% (IQR -10% to +95%).
Risk profile
Overall: High
- ▲League level coefficient 0.25 (1.00 = big-five average): output may not translate.
- ⚠Limited sample: 1016 league minutes last season.
- ⚠No continental-competition 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).
- Historical movers
- 18 (ATT)
- Relative output kept
- 87%–104%
- Held a regular role (900+ min)
- 94%
- Confidence
- Low
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 | SC Poltava | Premier Liga | ST | 13 | 1016 | 38% | 2 | 0 | 0.18 | 0.61 | 1193 | 909 | 0.25 |
| 2024/25 | Livyi Bereg Kyiv | Premier Liga | ST | 28 | 2132 | 79% | 0 | 0 | 0.00 | 0.26 | 1197 | 1040 | 0.28 |
| 2018/19 | Zorya Lugansk | Premier Liga | ST | 1 | 27 | 1% | 0 | 0 | 0.00 | 0.33 | 1194 | 1429 | 0.57 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Ukrainian Cup | Livyi Bereg Kyiv | 2 | 127 | 0 | 0 | — |
| 2024/25 | Ukrainian Cup | Livyi Bereg Kyiv | 1 | 25 | 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 |
|---|---|---|---|---|
| Rostyslav Rusyn Premier Liga · 2024 | 29 | €300k | €125k | fell |
| Nikolaos Vergos Super League 1 · 2023 | 27 | €450k | €550k | rose |
| Lazar Romanić Super League 1 · 2023 | 25 | €350k | €1.5M | rose |
| Oleg Vyshnevskyi Premier Liga · 2024 | 29 | €200k | €200k | flat |
| Georgios Pamlidis Super League 1 · 2022 | 29 | €300k | €350k | flat |
| Bogdan Boychuk Premier Liga · 2023 | 27 | €200k | €500k | rose |
| Rostyslav Taranukha Premier Liga · 2024 | 27 | €300k | €200k | fell |
| Sotiris Tsiloulis Super League 1 · 2022 | 27 | €250k | €450k | rose |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 9 Feb 2026 | Livyi Bereg | SC Poltava | Free / loan | €350k |
| 13 Jul 2023 | Without Club | Livyi Bereg | Unknown | €75k |
| 1 Jan 2023 | Nyva Ternopil | Without Club | Unknown | €100k |
| 12 Aug 2022 | Dynamo Kyiv II | Nyva Ternopil | Free / loan | €100k |
| 31 Dec 2021 | Chornomorets | Dynamo Kyiv II | Free / loan | €100k |
| 5 Feb 2021 | Dynamo Kyiv II | Chornomorets | Free / loan | Data unavailable |
| 30 Jun 2019 | Arsenal Kyiv II | Dynamo Kyiv II | Free / loan | Data unavailable |
| 3 Aug 2018 | Dynamo Kyiv U19 | Arsenal Kyiv II | Free / loan | Data unavailable |
| 1 Jul 2017 | Dynamo Kyiv U17 | Dynamo Kyiv 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.