
Vyacheslav Tankovskyi
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Vyacheslav Tankovskyi's performance-implied value at EUR 0.2M-0.4M, above the estimated acquisition range of EUR 0.1M-0.4M. Its 24-month market value projection is EUR 0.2M-0.5M. Context-adjusted goal contributions are 0.69x the positional average in the league (792 minutes, league coefficient 0.25). 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 | Below average | 11.3th pct among MID peers (age-neutral) |
| Age | Unfavorable | 30.9 years |
| Acquisition cost | Very favorable | est. €186k vs market €600k |
| Expected appreciation | Very low | -45% over ~2 years (model) |
| Value gap | 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 | 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 1164 evaluated MID players with 900+ minutes.
Performance (last season, league)
- Minutes
- 792 (29% of available)
- Goals + assists / 90
- 0.11
- Context-adjusted G+A / 90
- 0.15
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 11 (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)
- 1242
- Opponent strength
- 1118
- 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)
- €166k – €508k
Trajectory drivers: team strength up (+132 Elo); relative output down 26% vs positional peers.
Historical comparables (8): median 2-year value change -40% (IQR -50% to -33%).
Risk profile
Overall: Very High
- ▲Small sample: 792 league minutes last season.
- ▲League level coefficient 0.25 (1.00 = big-five average): output may not translate.
- ⚠No continental-competition minutes last season.
- ⚠Contract ends in 12 months: cheaper, but competition and wage demands likely.
- ⚠Age 31: resale value typically declines.
- ⚠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).
- Historical movers
- 37 (all positions)
- Relative output kept
- 87%–128%
- Held a regular role (900+ min)
- 86%
- Confidence
- Medium
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 | LNZ Cherkasy | Premier Liga | CM | 16 | 792 | 29% | 0 | 1 | 0.11 | 0.15 | 1118 | 1242 | 0.25 |
| 2024/25 | LNZ Cherkasy | Premier Liga | CM | 13 | 957 | 35% | 1 | 0 | 0.09 | 0.20 | 1210 | 1110 | 0.28 |
| 2023/24 | FK Polissya Zhytomyr | Premier Liga | CM | 27 | 1977 | 73% | 2 | 2 | 0.18 | 0.20 | 1268 | 1265 | 0.34 |
| 2022/23 | Metalist Kharkiv | Premier Liga | CM | 14 | 1187 | 44% | 0 | 0 | 0.00 | 0.11 | 1296 | 1089 | 0.38 |
| 2022/23 | SC Dnipro-1 | Premier Liga | CM | 7 | 267 | 10% | 0 | 0 | 0.00 | 0.14 | 1314 | 1398 | 0.38 |
| 2020/21 | FK Mariupol | Premier Liga | CM | 15 | 1213 | 52% | 1 | 0 | 0.07 | 0.13 | 1240 | 1222 | 0.49 |
| 2019/20 | FK Mariupol | Premier Liga | CM | 9 | 578 | 29% | 0 | 0 | 0.00 | 0.12 | 1267 | 1267 | 0.54 |
| 2018/19 | Arsenal Kyiv | Premier Liga | CM | 4 | 360 | 18% | 0 | 0 | 0.00 | 0.26 | 1354 | 1186 | 0.57 |
| 2017/18 | FK Mariupol | Premier Liga | CM | 9 | 737 | 37% | 0 | 2 | 0.24 | 0.31 | 1290 | 1296 | 0.62 |
| 2017/18 | FC Shakhtar Donetsk | Premier Liga | CM | 1 | 19 | 1% | 0 | 0 | 0.00 | 0.15 | 1334 | 1676 | 0.62 |
| 2016/17 | FC Shakhtar Donetsk | Premier Liga | CM | 4 | 360 | 13% | 0 | 0 | 0.00 | 0.11 | 1367 | 1636 | 0.56 |
| 2015/16 | Zorya Lugansk | Premier Liga | CM | 13 | 525 | 22% | 0 | 0 | 0.00 | 0.14 | 1371 | 1455 | 0.54 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Ukrainian Cup | LNZ Cherkasy | 4 | 242 | 1 | 0 | — |
| 2023/24 | Ukrainian Cup | FK Polissya Zhytomyr | 4 | 250 | 0 | 0 | — |
| 2020/21 | Ukrainian Cup | FK Mariupol | 1 | 58 | 0 | 0 | — |
| 2019/20 | Uefa Europa League Qualifying | FK Mariupol | 2 | 117 | 0 | 0 | 1481 |
| 2019/20 | Ukrainian Cup | FK Mariupol | 2 | 56 | 0 | 0 | — |
| 2017/18 | Ukrainian Cup | FK Mariupol | 3 | 183 | 1 | 0 | — |
| 2016/17 | Uefa Europa League | FC Shakhtar Donetsk | 2 | 106 | 0 | 0 | 1446 |
| 2016/17 | Ukrainian Cup | FC Shakhtar Donetsk | 1 | 90 | 0 | 0 | — |
| 2015/16 | Ukrainian Cup | Zorya Lugansk | 5 | 258 | 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 |
|---|---|---|---|---|
| Vyacheslav Churko Premier Liga · 2024 | 31 | €400k | €200k | fell |
| Dmytro Myshnyov Premier Liga · 2024 | 30 | €500k | €250k | fell |
| Caleb Stanko Super League 1 · 2022 | 29 | €500k | €350k | fell |
| Facundo Bertoglio Super League 1 · 2023 | 33 | €400k | €250k | fell |
| Federico Gino Super League 1 · 2023 | 30 | €250k | €175k | fell |
| Liam Donnelly Scottish Premiership · 2024 | 28 | €350k | €200k | fell |
| Volodymyr Tanchyk Premier Liga · 2024 | 33 | €250k | €100k | fell |
| Sotiris Ninis Super League 1 · 2021 | 31 | €300k | €200k | fell |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 12 Jan 2025 | Without Club | LNZ Cherkasy | Unknown | €800k |
| 6 Sept 2024 | Polissya | Without Club | Unknown | €1.0M |
| 3 Jul 2023 | Metalist | Polissya | €150k | €500k |
| 30 Jun 2023 | SC Dnipro-1 | Metalist | Free / loan | €500k |
| 20 Feb 2023 | Metalist | SC Dnipro-1 | Free / loan | €500k |
| 19 Aug 2021 | Shakhtar D. | Metalist | Free / loan | €400k |
| 30 Jun 2021 | FC Mariupol | Shakhtar D. | Free / loan | €400k |
| 5 Aug 2019 | Shakhtar D. | FC Mariupol | Free / loan | €400k |
| 30 Jun 2019 | Arsenal Kyiv | Shakhtar D. | Free / loan | €400k |
| 22 Feb 2019 | Shakhtar D. | Arsenal Kyiv | Free / loan | €500k |
| 31 Dec 2017 | FC Mariupol | Shakhtar D. | Free / loan | €600k |
| 16 Aug 2017 | Shakhtar D. | FC Mariupol | Free / loan | €600k |
| 1 Jul 2017 | Shakhtar II | Shakhtar D. | Unknown | €600k |
| 30 Jun 2016 | Zorya Lugansk | Shakhtar II | Free / loan | €300k |
| 24 Jul 2015 | Shakhtar II | Zorya Lugansk | Free / loan | €100k |
| 1 Jul 2012 | Shakhtar U17 | Shakhtar II | 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.