
Oumar Sako
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Oumar Sako's performance-implied value at EUR 0.6M-1.2M, below the estimated acquisition range of EUR 0.7M-1.8M. Its 24-month market value projection is EUR 0.7M-1.8M. 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: 33
What drives the score. Not a black box: each component and its level.
| Performance | Average | 35.5th pct among DEF peers (age-neutral) |
| Age | Unfavorable | 30.2 years |
| Acquisition cost | Very favorable | est. €933k vs market €2.5M |
| Expected appreciation | Very low | -57% 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 | 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 1268 evaluated DEF players with 900+ minutes.
Performance (last season, league)
- Minutes
- 1700 (63% of available)
- Goals + assists / 90
- 0.00
- Context-adjusted G+A / 90
- 0.03
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 36 (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)
- 1301
- 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)
- €700k – €1.8M
Trajectory drivers: relative output down 42% vs positional peers.
Historical comparables (8): median 2-year value change -50% (IQR -72% to -41%).
Risk profile
Overall: Very High
- ⚠Limited sample: 1700 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).
- ⚠Contract ends in 12 months: cheaper, but competition and wage demands likely.
- ⚠Age 30: 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
- 25 (DEF)
- Relative output kept
- 48%–200%
- Held a regular role (900+ min)
- 72%
- 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 Rostov | Premier Liga | CB | 23 | 1700 | 63% | 0 | 0 | 0.00 | 0.03 | 1340 | 1301 | 0.56 |
| 2024/25 | FK Rostov | Premier Liga | CB | 28 | 1994 | 74% | 1 | 0 | 0.05 | 0.05 | 1298 | 1342 | 0.55 |
| 2023/24 | FK Rostov | Premier Liga | CB | 11 | 990 | 37% | 0 | 1 | 0.09 | 0.07 | 1334 | 1317 | 0.49 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Russian Cup | FK Rostov | 6 | 317 | 0 | 0 | — |
| 2024/25 | Russian Cup | FK Rostov | 11 | 711 | 0 | 0 | — |
| 2023/24 | Russian Cup | FK Rostov | 3 | 209 | 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 |
|---|---|---|---|---|
| Tiago Pinto Super Lig · 2017 | 29 | €3.0M | €700k | fell |
| Benoît Poulain Jupiler Pro League · 2016 | 29 | €2.0M | €2.5M | rose |
| Baiano Liga Portugal · 2017 | 30 | €2.5M | €750k | fell |
| Melli Jupiler Pro League · 2013 | 29 | €1.2M | €600k | fell |
| Rens van Eijden Eredivisie · 2017 | 29 | €2.0M | €400k | fell |
| Jordi Amat Jupiler Pro League · 2021 | 29 | €1.4M | €900k | fell |
| Jean-Armel Kana-Biyik Super Lig · 2019 | 30 | €1.3M | €750k | fell |
| Marat Bystrov Premier Liga · 2023 | 31 | €1.0M | €500k | 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 | Arda Kardzhali | Rostov | €350k | €1.2M |
| 30 Jun 2024 | Rostov | Arda Kardzhali | Free / loan | €1.2M |
| 30 Jan 2024 | Arda Kardzhali | Rostov | Free / loan | €600k |
| 1 Jul 2023 | LASK | Arda Kardzhali | €150k | €500k |
| 30 Jun 2023 | Arda Kardzhali | LASK | Free / loan | €500k |
| 27 Jul 2022 | LASK | Arda Kardzhali | Free / loan | €300k |
| 13 Jan 2022 | Beroe | LASK | €300k | €225k |
| 1 Jul 2021 | Al-Kharaitiyat | Beroe | Free / loan | €50k |
| 24 Sept 2020 | ASEC Mimosas | Al-Kharaitiyat | Free / loan | Data unavailable |
| 1 Jul 2018 | AS Tanda | ASEC Mimosas | Free / loan | Data unavailable |
| 1 Jul 2017 | AS Denguélé | AS Tanda | 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.