
Yevgeniy Shevchenko
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Yevgeniy Shevchenko's performance-implied value at EUR 0.3M-0.5M, above the estimated acquisition range of EUR 0.1M-0.3M. Its 24-month market value projection is EUR 0.1M-0.4M. Context-adjusted goal contributions are 0.57x the positional average in the league (2235 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: Final year of contract: selling club's leverage is reduced.
Bargain Index: 80
What drives the score. Not a black box: each component and its level.
| Performance | Below average | 8.4th pct among MID peers (age-neutral) |
| Age | Unfavorable | 30.6 years |
| Acquisition cost | Very favorable | est. €115k vs market €400k |
| Expected appreciation | Very low | -33% 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 | Very 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 1163 evaluated MID players with 900+ minutes.
Performance (last season, league)
- Minutes
- 2235 (83% of available)
- Goals + assists / 90
- 0.08
- Context-adjusted G+A / 90
- 0.13
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 8 (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)
- 1070
- Opponent strength
- 1180
- 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)
- €123k – €352k
Trajectory drivers: changed club; team strength down (-62 Elo); role change LB -> LM; relative output down 51% vs positional peers.
Historical comparables (8): median 2-year value change -41% (IQR -55% to -23%).
Risk profile
Overall: Very High
- ▲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.
- ⚠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 | Obolon Kyiv | Premier Liga | LM | 26 | 2235 | 83% | 0 | 2 | 0.08 | 0.13 | 1180 | 1070 | 0.25 |
| 2024/25 | NK Veres Rivne | Premier Liga | LB | 24 | 2032 | 75% | 1 | 2 | 0.13 | 0.17 | 1188 | 1133 | 0.28 |
| 2023/24 | NK Veres Rivne | Premier Liga | LB | 21 | 1787 | 66% | 2 | 0 | 0.10 | 0.16 | 1269 | 1152 | 0.34 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Ukrainian Cup | Obolon Kyiv | 1 | 45 | 0 | 0 | — |
| 2024/25 | Ukrainian Cup | NK Veres Rivne | 2 | 230 | 0 | 0 | — |
| 2023/24 | Ukrainian Cup | NK Veres Rivne | 2 | 161 | 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 |
|---|---|---|---|---|
| Jason Holt Scottish Premiership · 2024 | 31 | €300k | €100k | fell |
| Oleksandr Demchenko Premier Liga · 2024 | 28 | €600k | €500k | flat |
| Scott Pittman Scottish Premiership · 2024 | 32 | €300k | €50k | fell |
| Valeriy Kucherov Premier Liga · 2024 | 31 | €400k | €200k | fell |
| Andriy Ralyuchenko Premier Liga · 2023 | 28 | €400k | €300k | fell |
| Oleksandr Kucherenko Premier Liga · 2023 | 32 | €250k | €150k | fell |
| Stephen McGinn Scottish Premiership · 2019 | 31 | €300k | €250k | flat |
| Miguel Mellado Super League 1 · 2023 | 30 | €600k | €350k | fell |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 1 Jul 2025 | Veres Rivne | Obolon | Free / loan | €400k |
| 3 Jul 2023 | Epicentr | Veres Rivne | Free / loan | €175k |
| 23 Aug 2022 | VPK-Agro | Epicentr | Free / loan | €100k |
| 30 Jul 2021 | Polissya | VPK-Agro | Free / loan | €100k |
| 15 Sept 2020 | Obolon | Polissya | Free / loan | €150k |
| 2 Mar 2015 | Lokomotyv Kyiv | Obolon-Brovar | Free / loan | Data unavailable |
| 1 Jan 2014 | Unknown | Lokomotyv Kyiv | Free / loan | Data unavailable |
| 1 Jul 2013 | Metalurg U19 | Unknown | Free / loan | 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.