
Ilya Petrov
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Ilya Petrov's performance-implied value at EUR 0.5M-1.5M, above the estimated acquisition range of EUR 0.3M-0.9M. Its 24-month market value projection is EUR 0.4M-1.0M. Context-adjusted goal contributions are 1.16x the positional average in the league (1919 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: 54
What drives the score. Not a black box: each component and its level.
| Performance | Below average | 30.3th pct among MID peers (age-neutral) |
| Age | Unfavorable | 31 years |
| Acquisition cost | Very favorable | est. €465k vs market €1.2M |
| Expected appreciation | Very low | -49% over ~2 years (model) |
| Value gap | Large | 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
- 1919 (71% of available)
- Goals + assists / 90
- 0.23
- Context-adjusted G+A / 90
- 0.25
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 30 (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
- 0.56 (rank 10)
- Team strength (Elo)
- 1326
- Opponent strength
- 1332
- Possession, role
- Data unavailable
League strength 1.00 = average club of the big-five leagues. Elo includes continental matches.
Potential
- Development
- Low
- Trajectory
- insufficient
- Breakout probability
- Age > 23
- Resale range (24m)
- €378k – €962k
Historical comparables (8): median 2-year value change -65% (IQR -75% to -47%).
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.
- ⚠Age 31: resale value typically declines.
- ⓘ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 Baltika | Premier Liga | CM | 27 | 1919 | 71% | 1 | 4 | 0.23 | 0.25 | 1332 | 1326 | 0.56 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Russian Cup | FK Baltika | 1 | 59 | 0 | 0 | — |
| 2013/14 | Russian Cup | Volga Nizhniy Novgorod (- 2016) | 1 | 16 | 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 |
|---|---|---|---|---|
| Mitchell Donald Super Lig · 2019 | 31 | €1.3M | €300k | fell |
| Guirane N'Daw Super League 1 · 2014 | 30 | €1.0M | €250k | fell |
| Roger Guerreiro Super League 1 · 2013 | 31 | €750k | €400k | fell |
| Ryota Morioka Jupiler Pro League · 2022 | 31 | €2.0M | €400k | fell |
| Tarantini Liga Portugal · 2016 | 33 | €1.3M | €500k | fell |
| Zola Matumona Jupiler Pro League · 2013 | 32 | €650k | €350k | fell |
| Vítor Gomes Liga Portugal · 2018 | 31 | €800k | €475k | fell |
| Jesper Jörgensen Jupiler Pro League · 2015 | 31 | €800k | €250k | 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 2024 | SKA Khabarovsk | Baltika | Free / loan | €600k |
| 1 Jul 2022 | Kuban | SKA Khabarovsk | Free / loan | €500k |
| 1 Jul 2021 | Neftekhimik | Kuban | Free / loan | €600k |
| 1 Aug 2019 | Mordovia | Neftekhimik | Free / loan | €500k |
| 1 Jul 2018 | Leiria | Mordovia | Free / loan | €300k |
| 31 Jan 2018 | Dinamo Moscow | Leiria | Unknown | €350k |
| 31 Dec 2017 | Avangard Kursk | Dinamo Moscow | Free / loan | €350k |
| 1 Jul 2017 | Dinamo Moscow | Avangard Kursk | Free / loan | €350k |
| 30 Jun 2017 | Mordovia | Dinamo Moscow | Free / loan | €350k |
| 31 Jul 2016 | Dinamo Moscow | Mordovia | Free / loan | €250k |
| 1 Jul 2016 | Volga NN | Dinamo Moscow | Free / loan | €250k |
| 1 Jul 2014 | Volga NN II | Volga NN | Unknown | Data unavailable |
| 1 Jan 2013 | Krasnodar II | Volga NN II | Unknown | Data unavailable |
| 4 Aug 2011 | Krasnodar U17 | Krasnodar II | Unknown | Data unavailable |
| 1 Jan 2011 | UOR-5 | Krasnodar U17 | 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.