Olakunle Olusegun
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Olakunle Olusegun's performance-implied value at EUR 1.1M-2.2M, below the estimated acquisition range of EUR 1.0M-2.6M. Its 24-month market value projection is EUR 1.2M-3.6M. Context-adjusted goal contributions are 1.30x the positional average in the league (1999 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: 78
What drives the score. Not a black box: each component and its level.
| Performance | Below average | 26.6th pct among ATT peers (age-neutral) |
| Age | Neutral | 24.2 years |
| Acquisition cost | Very favorable | est. €1.5M vs market €2.5M |
| Expected appreciation | Low | -20% over ~2 years (model) |
| Value gap | Very 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 | Moderate | |
| 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 900 evaluated ATT players with 900+ minutes.
Performance (last season, league)
- Minutes
- 1999 (74% of available)
- Goals + assists / 90
- 0.41
- Context-adjusted G+A / 90
- 0.51
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 27 (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)
- 1176
- Opponent strength
- 1348
- Possession, role
- Data unavailable
League strength 1.00 = average club of the big-five leagues. Elo includes continental matches.
Potential
- Development
- Low
- Trajectory
- improving
- Breakout probability
- Age > 23
- Resale range (24m)
- €1.2M – €3.6M
Trajectory drivers: minutes share up 53 pts; changed club; team strength down (-335 Elo); role change LW -> RW; relative output up 82% vs positional peers.
Historical comparables (8): median 2-year value change -24% (IQR -35% to +0%).
Risk profile
Overall: Moderate
- ⚠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).
- ⓘ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
- 20 (ATT)
- Relative output kept
- 76%–104%
- Held a regular role (900+ min)
- 50%
- 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 | FK Nizhny Novgorod | Premier Liga | RW | 26 | 1999 | 74% | 5 | 4 | 0.41 | 0.51 | 1348 | 1176 | 0.56 |
| 2024/25 | FK Krasnodar | Premier Liga | LW | 19 | 579 | 21% | 2 | 0 | 0.31 | 0.30 | 1311 | 1511 | 0.55 |
| 2023/24 | FK Krasnodar | Premier Liga | RW | 27 | 1607 | 60% | 3 | 3 | 0.34 | 0.32 | 1339 | 1405 | 0.49 |
| 2022/23 | FK Krasnodar | Premier Liga | LW | 24 | 1615 | 60% | 5 | 2 | 0.39 | 0.32 | 1318 | 1405 | 0.53 |
| 2021/22 | FK Krasnodar | Premier Liga | LW | 9 | 708 | 26% | 0 | 2 | 0.25 | 0.32 | 1350 | 1371 | 0.52 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Russian Cup | FK Nizhny Novgorod | 5 | 346 | 0 | 0 | — |
| 2024/25 | Russian Cup | FK Krasnodar | 8 | 647 | 1 | 0 | — |
| 2024/25 | Russian Super Cup | FK Krasnodar | 1 | 75 | 0 | 0 | 1491 |
| 2023/24 | Russian Cup | FK Krasnodar | 4 | 258 | 0 | 1 | — |
| 2022/23 | Russian Cup | FK Krasnodar | 7 | 350 | 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 |
|---|---|---|---|---|
| Renaud Emond Jupiler Pro League · 2015 | 24 | €1.5M | €1.0M | fell |
| Félix Correia Liga Portugal · 2024 | 23 | €2.5M | €10.0M | rose |
| Iñigo Córdoba Eredivisie · 2022 | 25 | €2.5M | €1.5M | fell |
| Fábio Martins Liga Portugal · 2017 | 24 | €1.8M | €1.5M | flat |
| David Pollet Jupiler Pro League · 2014 | 26 | €2.0M | €1.0M | fell |
| Anton Zinkovskiy Premier Liga · 2020 | 24 | €2.2M | €3.5M | rose |
| Vladyslav Kalitvintsev Premier Liga · 2016 | 23 | €1.0M | €800k | fell |
| Simy Liga Portugal · 2015 | 23 | €1.1M | €800k | fell |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 30 Jun 2026 | Pari NN | Krasnodar | Free / loan | €2.5M |
| 23 Jul 2025 | Krasnodar | Pari NN | Free / loan | €2.5M |
| 1 Jul 2022 | Botev Plovdiv | Krasnodar | €1.2M | €700k |
| 30 Jun 2022 | Krasnodar 2 | Botev Plovdiv | Free / loan | €700k |
| 23 Aug 2021 | Botev Plovdiv | Krasnodar 2 | Free / loan | €350k |
| 19 Aug 2021 | Fremad Amager | Botev Plovdiv | Free / loan | €350k |
| 1 Sept 2020 | FDC Vista | Fremad Amager | Unknown | Data unavailable |
| 1 Jul 2020 | ABS FC | FDC Vista | 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.