Aleksandr Chernikov
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Aleksandr Chernikov's performance-implied value at EUR 2.5M-10.3M, below the estimated acquisition range of EUR 4.2M-8.8M. Its 24-month market value projection is EUR 3.3M-9.7M. Context-adjusted goal contributions are 0.76x the positional average in the league (1589 minutes, league coefficient 0.56). Confidence is medium: no event-level data (xG, progressive actions) is available from the current free source, and injury history is unavailable.
Bargain Index: 27
What drives the score. Not a black box: each component and its level.
| Performance | Above average | 68.8th pct among MID peers (age-neutral) |
| Age | Neutral | 26.4 years |
| Acquisition cost | Favorable | est. €6.8M vs market €8.0M |
| Expected appreciation | Very low | -30% over ~2 years (model) |
| Value gap | Negative | weak predictor on its own |
| Development | Low | |
| League translation | Moderate | league coefficient 0.56 |
| 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 1163 evaluated MID players with 900+ minutes.
Performance (last season, league)
- Minutes
- 1589 (59% of available)
- Goals + assists / 90
- 0.17
- Context-adjusted G+A / 90
- 0.09
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 69 (Above 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
- 0.56 (rank 10)
- Team strength (Elo)
- 1536
- Opponent strength
- 1340
- 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)
- €3.3M – €9.7M
Historical comparables (8): median 2-year value change -15% (IQR -47% to +29%).
Risk profile
Overall: High
- ⚠Limited sample: 1589 league minutes last season.
- ⚠League level coefficient 0.56 (1.00 = big-five average): output may not translate.
- ⚠No continental-competition minutes last season.
- ⚠League level estimated mainly from squad values (few matches vs other leagues).
- ⚠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
- 18 (MID)
- Relative output kept
- 54%–153%
- Held a regular role (900+ min)
- 56%
- 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 | FK Krasnodar | Premier Liga | DM | 23 | 1589 | 59% | 1 | 2 | 0.17 | 0.09 | 1340 | 1536 | 0.56 |
| 2024/25 | FK Krasnodar | Premier Liga | DM | 27 | 1860 | 69% | 2 | 1 | 0.15 | 0.11 | 1299 | 1511 | 0.55 |
| 2023/24 | FK Krasnodar | Premier Liga | DM | 27 | 2344 | 87% | 1 | 0 | 0.04 | 0.05 | 1336 | 1405 | 0.49 |
| 2022/23 | FK Krasnodar | Premier Liga | DM | 13 | 824 | 31% | 0 | 1 | 0.11 | 0.08 | 1278 | 1405 | 0.53 |
| 2021/22 | FK Krasnodar | Premier Liga | DM | 23 | 1850 | 69% | 2 | 1 | 0.15 | 0.10 | 1349 | 1371 | 0.52 |
| 2020/21 | FK Krasnodar | Premier Liga | DM | 1 | 45 | 2% | 0 | 0 | 0.00 | 0.05 | 1113 | 1357 | 0.55 |
| 2019/20 | FK Krasnodar | Premier Liga | DM | 6 | 184 | 7% | 0 | 0 | 0.00 | 0.07 | 1387 | 1465 | 0.63 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Russian Cup | FK Krasnodar | 6 | 338 | 0 | 0 | — |
| 2025/26 | Russian Super Cup | FK Krasnodar | 1 | 66 | 0 | 0 | 1478 |
| 2024/25 | Russian Cup | FK Krasnodar | 7 | 358 | 0 | 1 | — |
| 2024/25 | Russian Super Cup | FK Krasnodar | 1 | 90 | 0 | 0 | 1491 |
| 2023/24 | Russian Cup | FK Krasnodar | 7 | 247 | 0 | 0 | — |
| 2022/23 | Russian Cup | FK Krasnodar | 5 | 76 | 0 | 0 | — |
| 2021/22 | Russian Cup | FK Krasnodar | 2 | 159 | 1 | 0 | — |
| 2019/20 | Russian Cup | FK Krasnodar | 1 | 21 | 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 |
|---|---|---|---|---|
| André André Liga Portugal · 2017 | 28 | €6.5M | €4.0M | fell |
| Lazare Amani Jupiler Pro League · 2024 | 26 | €5.0M | €1.0M | fell |
| Josip Juranovic Bundesliga · 2023 | 28 | €12.0M | €4.0M | fell |
| Claudinho Premier Liga · 2022 | 25 | €18.0M | €18.0M | flat |
| Alessio Castro-Montes Jupiler Pro League · 2023 | 26 | €3.8M | €5.0M | rose |
| Gojko Cimirot Super League 1 · 2018 | 26 | €3.5M | €4.5M | rose |
| Daler Kuzyaev Premier Liga · 2019 | 26 | €11.0M | €8.0M | fell |
| Vitaliy Buyalskyi Premier Liga · 2021 | 28 | €5.0M | €7.0M | rose |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 1 Jul 2021 | Krasnodar 2 | Krasnodar | Unknown | €500k |
| 1 Jul 2018 | Krasnodar II | Krasnodar 2 | Unknown | €150k |
| 9 Aug 2016 | Krasnodar U17 | Krasnodar II | Unknown | €100k |
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.