Albert Sambi Lokonga

26 yrs · Central midfielder (also DM) · Belgium
Hamburger SV · Bundesliga · Foot: right · Height: 183 cm
Risk: LowConfidence: MediumSample: MediumDevelopment: LowContract: until 30 Jun 2028
Market value
€12.0M
Updated 6 days ago
Estimated acquisition
€7.7M – €13.5M
Estimated · 20–80% range
Model value
€5.6M – €18.2M
Performance-implied · estimated
Projected (24m)
€5.0M – €12.9M
Resale range · estimated
Potential value gap
-€7.9M – €10.5M
Model value − acquisition

Value picture

Where the market, the likely price and the model estimates sit.

Estimated acquisition€7.7M – €13.5M
Model value (performance-implied)€5.6M – €18.2M
Projected value (24 months)€5.0M – €12.9M
Dashed line: current market value (€12.0M). Bars are 20–80% model ranges; tick = median.

The model rates Albert Sambi Lokonga's performance-implied value at EUR 5.6M-18.2M, below the estimated acquisition range of EUR 7.7M-13.5M. Its 24-month market value projection is EUR 5.0M-12.9M. Context-adjusted goal contributions are 1.30x the positional average in the league (1714 minutes, league coefficient 0.94). Confidence is medium: no event-level data (xG, progressive actions) is available from the current free source, and injury history is unavailable.

Bargain Index: 16

What drives the score. Not a black box: each component and its level.

PerformanceHigh77.3th pct among MID peers (age-neutral)
AgeNeutral26.7 years
Acquisition costNeutralest. €11.1M vs market €12.0M
Expected appreciationVery low-32% over ~2 years (model)
Value gapNegativeweak predictor on its own
DevelopmentLow
League translationBig-five leagueleague coefficient 0.94
Tactical fitNot evaluatedRequires event/role data not available from the current free source.
RiskLow
Data confidenceMedium

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.

Highest recorded: €16.0M

Profile vs positional peers

Percentiles among 1163 evaluated MID players with 900+ minutes.

Performance (last season, league)

Minutes
1714 (56% of available)
Goals + assists / 90
0.26
Context-adjusted G+A / 90
0.28
xG, xA, progression
Data unavailable
Defensive actions
Data unavailable
Performance percentile
77 (High)

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
0.94 (rank 3)
Team strength (Elo)
1380
Opponent strength
1513
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)
€5.0M – €12.9M

Trajectory drivers: changed club; relative output up 35% vs positional peers.

Historical comparables (8): median 2-year value change -38% (IQR -53% to -8%).

Risk profile

Overall: Low

  • ⚠Limited sample: 1714 league 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).

Already playing in a big-five league.

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.

SeasonClubLeaguePosAppsMinMin shareGAG+A/90Adj. G+A/90Opp. EloTeam EloLeague str.
2025/26Hamburger SVBundesligaCM26171456%500.260.28151313800.94
2024/25Sevilla FCLaligaCM22147443%020.120.20151514100.95
2023/24Luton TownPremier LeagueDM17131038%130.270.27154113151.14
2022/23Crystal PalacePremier LeagueCM953616%000.000.16164215361.23
2022/23Arsenal FCPremier LeagueCM61966%000.000.12155117261.23
2021/22Arsenal FCPremier LeagueCM19113233%000.000.07150516671.17
2020/21RSC AnderlechtJupiler Pro LeagueCM27238578%320.190.16136614570.55
2019/20RSC AnderlechtJupiler Pro LeagueCM23199476%030.140.13135914430.63
2018/19RSC AnderlechtJupiler Pro LeagueCM644516%000.000.11140014520.65
2017/18RSC AnderlechtJupiler Pro LeagueDM533412%000.000.05127914900.63

Cups & continental competitions

SeasonCompetitionClubAppsMinGAAvg opp. Elo
2024/25Copa Del ReySevilla FC19000—
2023/24Fa CupLuton Town213300—
2022/23Uefa Europa LeagueArsenal FC6478001528
2022/23Fa CupArsenal FC210700—
2021/22Fa CupArsenal FC19000—
2018/19Uefa Europa LeagueRSC Anderlecht222001478

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)AgeValue then~2y laterOutcome
Gastón Ramírez
Serie A · 2018
28€10.0M€6.5Mfell
Matheus Henrique
Serie A · 2023
26€10.0M€6.0Mfell
Simone Bastoni
Serie A · 2022
26€7.5M€1.5Mfell
Enis Bardhi
Laliga · 2022
27€8.0M€6.5Mflat
Nicolás Domínguez
Serie A · 2022
24€13.0M€17.0Mrose
Dennis Geiger
Bundesliga · 2023
25€8.0M€2.0Mfell
Rubén Vargas
Bundesliga · 2024
26€7.5M€12.0Mrose
Clément Chantôme
Ligue 1 · 2014
27€6.0M€3.5Mfell

Transfer history

Fees as reported by the source; undisclosed fees shown as unknown, never estimated.

DateFromToFeeMV at time
1 Sept 2025ArsenalHamburg€300k€8.0M
30 Jun 2025Sevilla FCArsenalFree / loan€8.0M
15 Jul 2024ArsenalSevilla FCFree / loan€15.0M
31 May 2024LutonArsenalFree / loan€15.0M
1 Sept 2023ArsenalLutonFree / loan€15.0M
31 May 2023Crystal PalaceArsenalFree / loan€15.0M
31 Jan 2023ArsenalCrystal PalaceFree / loan€15.0M
19 Jul 2021RSC AnderlechtArsenal€17.5M€12.0M
1 Jan 2018Anderlecht U21RSC AnderlechtUnknownData unavailable
1 Jul 2017Anderlecht U19Anderlecht U21UnknownData unavailable
1 Jul 2016Anderlecht U17Anderlecht U19UnknownData 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.