Sékou Koïta
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Sékou Koïta's performance-implied value at EUR 0.6M-1.0M, below the estimated acquisition range of EUR 0.7M-2.0M. Its 24-month market value projection is EUR 1.0M-2.7M. Context-adjusted goal contributions are 0.97x the positional average in the league (1813 minutes, league coefficient 0.40). 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: 77
What drives the score. Not a black box: each component and its level.
| Performance | Below average | 16.4th pct among ATT peers (age-neutral) |
| Age | Neutral | 26.6 years |
| Acquisition cost | Very favorable | est. €974k vs market €2.5M |
| Expected appreciation | Very low | -35% over ~2 years (model) |
| Value gap | Very negative | weak predictor on its own |
| Development | Low | |
| League translation | Uncertain | league coefficient 0.4 |
| 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
- 1813 (59% of available)
- Goals + assists / 90
- 0.30
- Context-adjusted G+A / 90
- 0.50
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 16 (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
- 0.40 (rank 18)
- Team strength (Elo)
- 1173
- Opponent strength
- 1290
- 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)
- €994k – €2.7M
Trajectory drivers: minutes share up 30 pts; changed club; team strength down (-306 Elo); league level down (-67 Elo); role change SS -> ST; relative output up 36% vs positional peers.
Historical comparables (8): median 2-year value change -6% (IQR -37% to +20%).
Risk profile
Overall: Moderate
- ⚠League level coefficient 0.40 (1.00 = big-five average): output may not translate.
- ⚠No continental-competition minutes last season.
- ⚠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
- 53 (ATT)
- Relative output kept
- 79%–133%
- Held a regular role (900+ min)
- 58%
- 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 | Gençlerbirliği Spor Kulübü | Super Lig | ST | 27 | 1733 | 57% | 6 | 0 | 0.31 | 0.50 | 1290 | 1160 | 0.40 |
| 2025/26 | PFK CSKA Moskva | Premier Liga | SS | 4 | 80 | 3% | 0 | 0 | 0.00 | 0.37 | 1343 | 1436 | 0.56 |
| 2024/25 | PFK CSKA Moskva | Premier Liga | SS | 22 | 798 | 30% | 3 | 1 | 0.45 | 0.35 | 1318 | 1478 | 0.55 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Russian Cup | PFK CSKA Moskva | 2 | 98 | 0 | 1 | — |
| 2025/26 | Russian Super Cup | PFK CSKA Moskva | 1 | 25 | 0 | 0 | 1511 |
| 2024/25 | Russian Cup | PFK CSKA Moskva | 13 | 820 | 2 | 2 | — |
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 |
|---|---|---|---|---|
| Adolfo Gaich Super Lig · 2024 | 25 | €1.7M | €1.0M | fell |
| Hadi Sacko Super Lig · 2020 | 26 | €1.2M | €350k | fell |
| Emre Kılınç Super Lig · 2023 | 29 | €2.8M | €1.8M | fell |
| Dereck Kutesa Jupiler Pro League · 2022 | 25 | €1.2M | €2.0M | rose |
| Tyler Boyd Super Lig · 2022 | 28 | €700k | €1.2M | rose |
| Pelle van Amersfoort Eredivisie · 2024 | 28 | €1.5M | €1.5M | flat |
| Riad Bajic Super Lig · 2020 | 26 | €1.4M | €1.5M | flat |
| Steeven Langil Jupiler Pro League · 2015 | 27 | €900k | €800k | flat |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 1 Jul 2026 | CSKA Moscow | Genclerbirligi | €1.6M | €2.5M |
| 30 Jun 2026 | Genclerbirligi | CSKA Moscow | Free / loan | €2.5M |
| 19 Aug 2025 | CSKA Moscow | Genclerbirligi | Free / loan | €3.5M |
| 8 Jul 2024 | Salzburg | CSKA Moscow | Free / loan | €4.0M |
| 1 Jul 2019 | FC Liefering | Salzburg | Unknown | €1.5M |
| 30 Jun 2019 | Wolfsberger AC | FC Liefering | Free / loan | €1.5M |
| 8 Jan 2019 | FC Liefering | Wolfsberger AC | Free / loan | €400k |
| 1 Jan 2018 | USC Kita | FC Liefering | Unknown | Data unavailable |
| 1 Jul 2017 | AS Bakaridjan | USC Kita | Unknown | Data unavailable |
| 30 Jun 2017 | USC Kita | AS Bakaridjan | Free / loan | Data unavailable |
| 1 Aug 2016 | AS Bakaridjan | USC Kita | 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.