FairValue

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  • EnvironmentOverviewWhat FairValue measures, what it found, where to go next.
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Aymen

Sliti

LWNetherlands · Feyenoord Rotterdam

№ 775257Established €2.6M −0.27

Player dossierEredivisie

AymenSliti

LWLeft WingerAttack

Club
Feyenoord Rotterdam
League
Eredivisie
Nationality
Netherlands
Age
20
Height
179 cm
Foot
Left
Valued
28 May 2026

Reading the valuation

The market values Sliti at €2M. Model A, which never saw Sliti during training, estimates €2.6M: the market value is 23% below that estimate.

That is a factor of ×1.30. Model A's typical held-out miss is ×1.50 either way, so this gap is within its usual error.

Without league and club, Model B estimates €3M, further from the market. Model B is usually further off (typical miss ×2.07): league and club explain much of how the market prices players.

A gap describes the model's arithmetic for this player's inputs, not what the player is worth.

▼ −0.27A €2.6M▼ −0.40B €3M
Pitch length is a log value scale fitted to this player's figures. ● observed · ◇ Model A · dashed ◇ Model B · each arc is a residual, log(observed) − log(estimate).
Apps
28
Minutes
823
Goals
2
Assists
2
Started
7/28
Min / app
29
Cards
0Y 0R

Club matches, two years to the valuation date

The Valuation Journey

What moves Model A

Asking the prediction API to explain Model A for Sliti…

SHAP describes the model's arithmetic for this player's inputs, not what causes market value. Model B can be explained only by the live service; Model A also has a published explanation for the research players.

Model A vs Model B against the observed €2M

Checking API
EmergingEstablishedEliteWorld Class€2M€10M€30M€100k€1M€100MMarket €2MModel A €2.6M

Asking the prediction API…

Held-out estimates come from cross-validation, with this player outside the training data: the honest comparison. Served models were refitted on every player, this one included, so they sit closer to the market. Shaded band: Model A's typical miss (×1.50 either way).

Player traitspercentiles vs 1,583 attackers

Aymen Sliti's percentiles among attackers: Goals per 90 41st, Assists per 90 76th, Minutes, two years 13th, Starts 7th, Minutes, last 365 days 23rd, European club minutes 90th41stGoals76thAssists13thMinutes7thStarts23rdRecent90thEurope

Dashed ring: the attacker median (50th percentile)

European club minutes

Share of minutes played in UEFA club competitions.

25% this player0% attacker median90th percentile

0%peer deciles · median line · this player ●100%

No passing, progression or defensive actions exist in the dataset, so no trait claims to measure them.

Valuation history every Transfermarkt valuation on record

First valuation
€750k
Apr 2025
Peak
€3M
Dec 2025
Model target
€2M
May 2026
Valuations
5
1 club change
May 2026€2MFeyenoord RotterdamValuation the model is trained to reproduce

May 2026: €2M, Feyenoord Rotterdam. Dotted lines mark the €2M, €10M and €30M tier boundaries.

Show as a table
DateMarket valueClub
2025-04-29€750kFeyenoord U21
2025-05-28€750kFeyenoord U21
2025-10-02€1.5MFeyenoord Rotterdam
2025-12-02€3MFeyenoord Rotterdam
2026-05-28€2MFeyenoord Rotterdam

Audit context group-level, not about this player

Audit group
UEFA
Population gap, Model A
+0.093 95% CI +0.063 to +0.124
This player, market vs held-out A
−0.265

The group comes from first-listed citizenship and is never a model input. Across the population, non-UEFA players' market values sit about 10% above Model A's held-out estimates, relative to UEFA players in the same leagues. One player's residual says nothing about that pattern (typical miss ×1.50), and none of it is evidence of discrimination: the target may itself be biased. Open the Fairness Audit

In context observed value among comparable players in this build

All players in the Terminal →

Eredivisie425 players · median €1M

Valued above 62% of the 425 Eredivisie players.

€75k€500k€3M€20M€2MSee them in the Explorer →

Attackers, all leagues1,583 players · median €2.5M

Valued above 44% of the 1,583 attackers.

€20k€300k€5M€75M€2MSee them in the Explorer →

Where Sliti appears

Watchlists and the comparison tray are kept in this browser only.

Near this valuation closest observed values: same league, then same position

Counts and ranks of observed Transfermarkt values only; model errors are never ranked here. Full player export: Every player in the modelling population (D-011).