Malik Tillman

24 yrs · Attacking midfielder (also LW, RW) · United States
Bayer 04 Leverkusen · Bundesliga · Foot: right · Height: 187 cm
Risk: ModerateConfidence: MediumSample: MediumDevelopment: ModerateContract: until 30 Jun 2030
Market value
€30.0M
Updated 6 days ago
Estimated acquisition
€18.6M – €38.8M
Estimated · 20–80% range
Model value
€12.9M – €42.5M
Performance-implied · estimated
Projected (24m)
€18.5M – €47.0M
Resale range · estimated
Potential value gap
-€25.9M – €23.9M
Model value − acquisition

Value picture

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

Estimated acquisition€18.6M – €38.8M
Model value (performance-implied)€12.9M – €42.5M
Projected value (24 months)€18.5M – €47.0M
Dashed line: current market value (€30.0M). Bars are 20–80% model ranges; tick = median.

The model rates Malik Tillman's performance-implied value at EUR 12.9M-42.5M, below the estimated acquisition range of EUR 18.6M-38.8M. Its 24-month market value projection is EUR 18.5M-47.0M. Context-adjusted goal contributions are 0.65x the positional average in the league (1677 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: 39

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

PerformanceHigh84.4th pct among MID peers (age-neutral)
AgeNeutral24.1 years
Acquisition costNeutralest. €29.1M vs market €30.0M
Expected appreciationLow-11% over ~2 years (model)
Value gapVery negativeweak predictor on its own
DevelopmentModerate
League translationBig-five leagueleague coefficient 0.94
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: €35.0M

Profile vs positional peers

Percentiles among 1163 evaluated MID players with 900+ minutes.

Performance (last season, league)

Minutes
1677 (55% of available)
Goals + assists / 90
0.38
Context-adjusted G+A / 90
0.26
xG, xA, progression
Data unavailable
Defensive actions
Data unavailable
Performance percentile
84 (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)
1626
Opponent strength
1467
Possession, role
Data unavailable

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

Potential

Development
Moderate
Trajectory
declining
Breakout probability
Age > 23
Resale range (24m)
€18.5M – €47.0M

Trajectory drivers: changed club; league level up (+168 Elo).

Historical comparables (8): median 2-year value change -11% (IQR -29% to +29%).

Risk profile

Overall: Moderate

  • ⚠Limited sample: 1677 league minutes last season.
  • ⚠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).

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.
2025/26Bayer 04 LeverkusenBundesligaAM29167755%610.380.26146716260.94
2024/25PSV EindhovenEredivisieAM26191963%1220.660.29130516320.50
2023/24PSV EindhovenEredivisieLW28159152%9111.130.41133416590.48
2022/23Rangers FCScottish PremiershipAM28194365%1040.650.33129515270.40
2021/22Bayern MunichBundesligaRW41023%000.000.13149718471.05

Cups & continental competitions

SeasonCompetitionClubAppsMinGAAvg opp. Elo
2025/26Uefa Champions LeagueBayer 04 Leverkusen10533201643
2025/26World CupUnited States317601—
2025/26Dfb PokalBayer 04 Leverkusen312500—
2024/25Uefa Champions LeaguePSV Eindhoven6534321595
2024/25Johan Cruijff SchaalPSV Eindhoven190011593
2024/25Knvb BekerPSV Eindhoven16010—
2023/24Uefa Champions LeaguePSV Eindhoven8503031659
2023/24Knvb BekerPSV Eindhoven213501—
2023/24Uefa Champions League QualifyingPSV Eindhoven13001528
2022/23Uefa Champions League QualifyingRangers FC4328111588
2022/23Uefa Champions LeagueRangers FC5246001751
2022/23Scottish Fa CupRangers FC319310—
2021/22Dfb PokalBayern Munich14510—
2021/22Uefa Champions LeagueBayern Munich218001646

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
Nordi Mukiele
Bundesliga · 2021
24€25.0M€18.0Mfell
Oscar
Premier League · 2016
25€35.0M€24.0Mfell
Piotr Zielinski
Serie A · 2018
24€32.0M€32.0Mflat
Rodrigo Bentancur
Serie A · 2020
23€40.0M€28.0Mfell
Timothy Castagne
Serie A · 2020
25€16.0M€28.0Mrose
Geoffrey Kondogbia
Serie A · 2016
23€24.0M€30.0Mrose
Andrea Cambiaso
Serie A · 2024
24€25.0M€20.0Mfell
Lorenzo Pellegrini
Serie A · 2020
24€32.0M€45.0Mrose

Transfer history

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

DateFromToFeeMV at time
12 Jul 2025PSVLeverkusen€35.0M€32.0M
1 Jul 2024Bayern MunichPSV€12.0M€20.0M
30 Jun 2024PSVBayern MunichFree / loan€20.0M
10 Aug 2023Bayern MunichPSVFree / loan€5.0M
30 Jun 2023RangersBayern MunichFree / loan€5.0M
15 Jul 2022Bayern MunichRangersFree / loan€1.5M
1 Jul 2021FC Bayern IIBayern MunichUnknown€500k
1 Jul 2020FC Bayern U19FC Bayern IIUnknown€500k
1 Jan 2019FC Bayern U17FC Bayern U19UnknownData unavailable
1 Jul 2017B. München Yth.FC Bayern U17UnknownData unavailable
20 Aug 2015Gr. Fürth Yth.B. München Yth.Free / loanData 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.