Chidera Ejuke

28 yrs · Left winger · Nigeria
Sevilla FC · Laliga · Foot: right · Height: 176 cm
Risk: ModerateConfidence: MediumSample: MediumDevelopment: LowContract: until 30 Jun 2027
Market value
€4.0M
Updated 6 days ago
Estimated acquisition
€1.2M – €3.4M
Estimated · 20–80% range
Model value
€1.9M – €3.5M
Performance-implied · estimated
Projected (24m)
€1.3M – €3.4M
Resale range · estimated
Potential value gap
-€1.5M – €2.4M
Model value − acquisition

Value picture

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

Estimated acquisition€1.2M – €3.4M
Model value (performance-implied)€1.9M – €3.5M
Projected value (24 months)€1.3M – €3.4M
Dashed line: current market value (€4.0M). Bars are 20–80% model ranges; tick = median.

The model rates Chidera Ejuke's performance-implied value at EUR 1.9M-3.5M, above the estimated acquisition range of EUR 1.2M-3.4M. Its 24-month market value projection is EUR 1.3M-3.4M. Context-adjusted goal contributions are 0.91x the positional average in the league (922 minutes, league coefficient 0.95). 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: 61

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

PerformanceAverage48.2th pct among ATT peers (age-neutral)
AgeUnfavorable28.5 years
Acquisition costVery favorableest. €1.6M vs market €4.0M
Expected appreciationVery low-45% over ~2 years (model)
Value gapLargeweak predictor on its own
DevelopmentLow
League translationBig-five leagueleague coefficient 0.95
Tactical fitNot evaluatedRequires event/role data not available from the current free source.
RiskModerate
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: €9.0M

Profile vs positional peers

Percentiles among 900 evaluated ATT players with 900+ minutes.

Performance (last season, league)

Minutes
922 (27% of available)
Goals + assists / 90
0.20
Context-adjusted G+A / 90
0.37
xG, xA, progression
Data unavailable
Defensive actions
Data unavailable
Performance percentile
48 (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
0.95 (rank 2)
Team strength (Elo)
1397
Opponent strength
1492
Possession, role
Data unavailable

League strength 1.00 = average club of the big-five leagues. Elo includes continental matches.

Potential

Development
Low
Trajectory
stable
Breakout probability
Age > 23
Resale range (24m)
€1.3M – €3.4M

Historical comparables (8): median 2-year value change -39% (IQR -63% to -13%).

Risk profile

Overall: Moderate

  • ⚠Limited sample: 922 league minutes last season.
  • ⚠Contract ends in 12 months: cheaper, but competition and wage demands likely.
  • ⚠Played under 40% of available league minutes (injury data unavailable, cause unknown).
  • ⓘ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.
2025/26Sevilla FCLaligaLW2792227%110.200.37149213970.95
2024/25Sevilla FCLaligaLW2595728%210.280.43153914100.95
2023/24Royal Antwerp FCJupiler Pro LeagueLW21133149%340.470.32136914920.63
2022/23Hertha BSCBundesligaLW2088529%030.310.41154413541.04
2021/22PFK CSKA MoskvaPremier LigaLW30182368%550.490.45134913630.52
2020/21PFK CSKA MoskvaPremier LigaLW25158959%530.450.37132713830.55
2019/20SC HeerenveenEredivisieLW25206288%940.570.53136813170.62

Cups & continental competitions

SeasonCompetitionClubAppsMinGAAvg opp. Elo
2025/26Copa Del ReySevilla FC29400—
2025/26Africa Cup Of NationsNigeria21200—
2023/24Uefa Champions LeagueRoyal Antwerp FC4153001656
2022/23Dfb PokalHertha BSC14700—
2021/22Russian CupPFK CSKA Moskva23400—
2020/21Uefa Europa LeaguePFK CSKA Moskva5323001513
2020/21Russian CupPFK CSKA Moskva319700—
2019/20Knvb BekerSC Heerenveen434012—

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
Maxi López
Serie A · 2013
29€5.0M€2.0Mfell
Roman Yaremchuk
Laliga · 2024
29€3.5M€3.5Mflat
Lewis Grabban
Premier League · 2016
28€4.0M€3.0Mfell
Antonio Floro Flores
Serie A · 2013
30€3.0M€1.5Mfell
Eldor Shomurodov
Serie A · 2023
28€6.0M€5.0Mflat
Mohammed Abdellaoue
Bundesliga · 2014
29€3.0M€600kfell
Florian Niederlechner
Bundesliga · 2019
29€3.5M€4.0Mflat
Shon Weissman
Laliga · 2023
27€4.0M€1.2Mfell

Transfer history

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

DateFromToFeeMV at time
1 Jul 2024CSKA MoscowSevilla FCFree / loan€6.0M
30 Jun 2024Royal AntwerpCSKA MoscowFree / loan€6.0M
30 Jul 2023CSKA MoscowRoyal AntwerpFree / loan€5.5M
30 Jun 2023Hertha BSCCSKA MoscowFree / loan€5.5M
13 Jul 2022CSKA MoscowHertha BSCFree / loan€7.5M
28 Aug 2020HeerenveenCSKA Moscow€11.5M€5.5M
15 Jul 2019VålerengaHeerenveen€2.0M€400k
10 Mar 2017Gombe UnitedVålerengaUnknownData unavailable
1 Jul 2016Supreme CourtGombe UnitedUnknownData unavailable
1 Jul 2014Ikon Allah FASupreme CourtUnknownData 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.