FairValue

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  • EnvironmentOverviewWhat FairValue measures, what it found, where to go next.
  • EnvironmentTerminalExplore, compare and track players; market, league and model views.
  • EnvironmentStoriesValuations, head-to-heads and research findings, told as stories.
  • TerminalPlayer ExplorerSearch, filter and sort the player export.
  • TerminalComparison StudioTwo to four players on one scale.
  • TerminalWatchlistsNamed collections, kept in this browser.
  • TerminalMarket LandscapeHow observed value is distributed, and where the model drifts.

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Ebube

Duru

LBNigeria · Sönderjyske Fodbold

№ 638971Emerging €476k −0.31

Player dossierSuperliga

EbubeDuru

LBLeft-BackDefender

Club
Sönderjyske Fodbold
League
Superliga
Nationality
Nigeria
Age
26
Height
182 cm
Foot
Left
Valued
25 May 2026

Reading the valuation

The market values Duru at €350k. Model A, which never saw Duru during training, estimates €476k: the market value is 26% below that estimate.

That is a factor of ×1.36. 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 €736k, 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.

▼ −0.31A €476k▼ −0.74B €736k
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
31
Minutes
2,025
Goals
2
Assists
0
Started
23/31
Min / app
65
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 Duru…

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 €350k

Checking API
EmergingEstablishedEliteWorld Class€2M€10M€30M€100k€1M€100MMarket €350kModel A €476k

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 2,065 defenders

Ebube Duru's percentiles among defenders: Goals per 90 83rd, Assists per 90 17th, Minutes, two years 35th, Starts 34th, Minutes, last 365 days 26th, European club minutes 30th83rdGoals17thAssists35thMinutes34thStarts26thRecent30thEurope

Dashed ring: the defender median (50th percentile)

Goals per 90

Club goals per 90 minutes played in the two years to the valuation date.

0.09 this player0.03 defender median83rd percentile

0.00peer deciles · median line · this player ●0.41

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
€250k
Dec 2024
Peak
€350k
Jun 2025
Model target
€350k
May 2026
Valuations
4
0 club changes
May 2026€350kSönderjyske FodboldValuation the model is trained to reproduce

May 2026: €350k, Sönderjyske Fodbold. Dotted lines mark the €2M, €10M and €30M tier boundaries.

Show as a table
DateMarket valueClub
2024-12-09€250kSönderjyske Fodbold
2025-06-16€350kSönderjyske Fodbold
2025-12-15€350kSönderjyske Fodbold
2026-05-25€350kSönderjyske Fodbold

Audit context group-level, not about this player

Audit group
non-UEFA
Population gap, Model A
+0.093 95% CI +0.063 to +0.124
This player, market vs held-out A
−0.308

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 →

Superliga256 players · median €800k

Valued above 14% of the 256 Superliga players.

€20k€150k€1M€7.5M€350kSee them in the Explorer →

Defenders, all leagues2,065 players · median €2M

Valued above 12% of the 2,065 defenders.

€20k€200k€2M€20M€350kSee them in the Explorer →

Where Duru 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).