Bruny Nsimba
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Bruny Nsimba's performance-implied value at EUR 1.0M-1.8M, below the estimated acquisition range of EUR 1.1M-2.7M. Its 24-month market value projection is EUR 0.9M-2.8M. Context-adjusted goal contributions are 1.67x the positional average in the league (1730 minutes, league coefficient 0.65). Confidence is medium: no event-level data (xG, progressive actions) is available from the current free source, and injury history is unavailable.
Bargain Index: 24
What drives the score. Not a black box: each component and its level.
| Performance | Below average | 28.6th pct among ATT peers (age-neutral) |
| Age | Neutral | 26.2 years |
| Acquisition cost | Neutral | est. €2.2M vs market €2.5M |
| Expected appreciation | Very low | -30% over ~2 years (model) |
| Value gap | Very negative | weak predictor on its own |
| Development | Low | |
| League translation | Moderate | league coefficient 0.65 |
| 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
- 1730 (64% of available)
- Goals + assists / 90
- 0.62
- Context-adjusted G+A / 90
- 0.85
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 29 (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
- 0.65 (rank 6)
- Team strength (Elo)
- 1207
- Opponent strength
- 1389
- 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)
- €925k – €2.8M
Trajectory drivers: relative output up 93% vs positional peers.
Historical comparables (8): median 2-year value change +8% (IQR -16% to +28%).
Risk profile
Overall: Moderate
- ⚠Limited sample: 1730 league minutes last season.
- ⚠No continental-competition minutes last 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
- 78 (ATT)
- Relative output kept
- 72%–126%
- Held a regular role (900+ min)
- 60%
- 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 | FCV Dender EH | Jupiler Pro League | ST | 25 | 1730 | 64% | 8 | 4 | 0.62 | 0.85 | 1389 | 1207 | 0.65 |
| 2024/25 | FCV Dender EH | Jupiler Pro League | ST | 29 | 1935 | 72% | 6 | 2 | 0.37 | 0.46 | 1380 | 1267 | 0.63 |
| 2022/23 | Royal Antwerp FC | Jupiler Pro League | RW | 10 | 113 | 4% | 1 | 0 | 0.80 | 0.34 | 1316 | 1497 | 0.58 |
| 2021/22 | Royal Antwerp FC | Jupiler Pro League | RW | 1 | 9 | 0% | 0 | 0 | 0.00 | 0.22 | 1196 | 1402 | 0.49 |
| 2020/21 | Royal Antwerp FC | Jupiler Pro League | RW | 5 | 165 | 5% | 0 | 1 | 0.55 | 0.33 | 1324 | 1436 | 0.55 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Jupiler Pro League Relegation Play Offs | FCV Dender EH | 3 | 89 | 1 | 0 | 1293 |
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 |
|---|---|---|---|---|
| Gianni Bruno Jupiler Pro League · 2019 | 28 | €1.8M | €2.5M | rose |
| Mario González Liga Portugal · 2021 | 25 | €3.0M | €3.5M | flat |
| Valon Ethemi Super Lig · 2023 | 26 | €2.0M | €1.5M | fell |
| Hyun-jun Suk Liga Portugal · 2016 | 25 | €4.0M | €3.5M | flat |
| Léo Jabá Liga Portugal · 2024 | 26 | €2.0M | €2.0M | flat |
| Aitor Cantalapiedra Eredivisie · 2020 | 24 | €1.6M | €2.0M | rose |
| Vladimir Pisarskiy Premier Liga · 2023 | 27 | €2.0M | €1.0M | fell |
| Jonathan Okita Eredivisie · 2022 | 26 | €800k | €2.0M | rose |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 1 Jul 2026 | FCV Dender EH | Standard Liège | Free / loan | €2.5M |
| 1 Jul 2023 | SK Beveren | FCV Dender EH | Free / loan | €400k |
| 31 Jan 2023 | Royal Antwerp | SK Beveren | Unknown | €300k |
| 13 Feb 2020 | Antwerp U21 | Royal Antwerp | Unknown | Data unavailable |
| 1 Jul 2019 | KRC Genk U21 | Antwerp U21 | Free / loan | Data unavailable |
| 1 Jul 2018 | KRC Genk U19 | KRC Genk U21 | Unknown | Data unavailable |
| 1 Jul 2017 | KRC Genk U17 | KRC Genk U19 | Unknown | Data unavailable |
| 1 Jul 2016 | KRC Genk Youth | KRC Genk U17 | Unknown | Data unavailable |
| 1 Jul 2013 | KV Mechelen Yth | KRC Genk Youth | Free / loan | Data unavailable |
| 1 Jul 2011 | Dender Yth. | KV Mechelen Yth | Free / loan | Data unavailable |
| 1 Jul 2009 | Anderlecht Yth. | Dender Yth. | 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.