Artem Karpukas
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Artem Karpukas's performance-implied value at EUR 1.4M-10.0M, below the estimated acquisition range of EUR 3.0M-8.0M. Its 24-month market value projection is EUR 3.3M-10.3M. Context-adjusted goal contributions are 0.70x the positional average in the league (2145 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.
Acquisition note: Final year of contract: selling club's leverage is reduced.
Bargain Index: 85
What drives the score. Not a black box: each component and its level.
| Performance | Average | 51.2th pct among MID peers (age-neutral) |
| Age | Neutral | 24 years |
| Acquisition cost | Very favorable | est. €4.0M vs market €7.0M |
| Expected appreciation | Low | -15% over ~2 years (model) |
| Value gap | Negative | weak predictor on its own |
| Development | Moderate | |
| 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
- 2145 (79% of available)
- Goals + assists / 90
- 0.13
- Context-adjusted G+A / 90
- 0.09
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 51 (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)
- 1418
- Opponent strength
- 1334
- Possession, role
- Data unavailable
League strength 1.00 = average club of the big-five leagues. Elo includes continental matches.
Potential
- Development
- Moderate
- Trajectory
- stable
- Breakout probability
- Age > 23
- Resale range (24m)
- €3.3M – €10.3M
Trajectory drivers: minutes share up 22 pts; relative output down 30% vs positional peers.
Historical comparables (8): median 2-year value change +111% (IQR +58% to +128%).
Risk profile
Overall: High
- ⚠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).
- ⚠Contract ends in 12 months: cheaper, but competition and wage demands likely.
- ⓘ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 | Футбольный клуб "Локомотив" Москва | Premier Liga | DM | 28 | 2145 | 79% | 1 | 2 | 0.13 | 0.09 | 1334 | 1418 | 0.56 |
| 2024/25 | Футбольный клуб "Локомотив" Москва | Premier Liga | DM | 25 | 1560 | 58% | 1 | 2 | 0.17 | 0.13 | 1295 | 1413 | 0.55 |
| 2023/24 | Футбольный клуб "Локомотив" Москва | Premier Liga | DM | 23 | 1598 | 59% | 1 | 0 | 0.06 | 0.06 | 1331 | 1416 | 0.49 |
| 2022/23 | Футбольный клуб "Локомотив" Москва | Premier Liga | DM | 27 | 2193 | 81% | 2 | 1 | 0.12 | 0.10 | 1311 | 1399 | 0.53 |
| 2021/22 | Футбольный клуб "Локомотив" Москва | Premier Liga | CM | 6 | 430 | 16% | 0 | 0 | 0.00 | 0.13 | 1401 | 1344 | 0.52 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Russian Cup | Футбольный клуб "Локомотив" Москва | 7 | 378 | 1 | 0 | — |
| 2024/25 | Russian Cup | Футбольный клуб "Локомотив" Москва | 9 | 362 | 0 | 0 | — |
| 2023/24 | Russian Cup | Футбольный клуб "Локомотив" Москва | 7 | 399 | 0 | 0 | — |
| 2022/23 | Russian Cup | Футбольный клуб "Локомотив" Москва | 8 | 621 | 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 |
|---|---|---|---|---|
| Sebastian Szymanski Premier Liga · 2021 | 22 | €8.0M | €18.0M | rose |
| Ramiz Zerrouki Eredivisie · 2022 | 24 | €3.5M | €9.0M | rose |
| Neeskens Kebano Jupiler Pro League · 2016 | 24 | €5.0M | €3.5M | fell |
| Jurgen Ekkelenkamp Jupiler Pro League · 2024 | 24 | €4.5M | €10.0M | rose |
| Wendel Liga Portugal · 2020 | 23 | €8.0M | €19.0M | rose |
| Kristian Thorstvedt Jupiler Pro League · 2022 | 23 | €5.0M | €8.0M | rose |
| Galeno Liga Portugal · 2021 | 24 | €10.0M | €20.0M | rose |
| Bryan Heynen Jupiler Pro League · 2022 | 25 | €6.5M | €10.0M | rose |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 1 Feb 2022 | Loko-Kazanka M. | Loko Moscow | Unknown | €125k |
| 1 Jul 2021 | Loko Moscow II | Loko-Kazanka M. | Unknown | €100k |
| 1 Aug 2020 | Ak. Loko U17 | Loko Moscow 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.