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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Portrait of Tyler Dibling

Tyler

Dibling

RWEngland · Everton FC

№ 866655Elite €11.4M +0.40

Image: FootyLogos

Player dossierPremier League

TylerDibling

RWRight WingerAttack

Club
Everton FC
League
Premier League
Nationality
England
Age
20
Height
178 cm
Foot
Left
Valued
3 Jun 2026

Reading the valuation

The market values Dibling at €17M. Model A, which never saw Dibling during training, estimates €11.4M: the market value is 49% above that estimate.

That is a factor of ×1.49. 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 €2.2M, 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.

▲ +0.40A €11.4M▲ +2.02B €2.2M
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
53
Minutes
2,611
Goals
4
Assists
3
Started
29/53
Min / app
49
Cards
9Y 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 Dibling…

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 €17M

Checking API
EmergingEstablishedEliteWorld Class€2M€10M€30M€100k€1M€100MMarket €17MModel A €11.4M

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

Tyler Dibling's percentiles among attackers: Goals per 90 21st, Assists per 90 33rd, Minutes, two years 59th, Starts 43rd, Minutes, last 365 days 15th, European club minutes 28th21stGoals33rdAssists59thMinutes43rdStarts15thRecent28thEurope

Dashed ring: the attacker median (50th percentile)

Minutes, two years

Total club minutes in the two-year window: how much the player was used.

2,611 this player2,242 attacker median59th percentile

450peer deciles · median line · this player ●8,788

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
€5M
Oct 2024
Peak
€35M
Oct 2025
Model target
€17M
Jun 2026
Valuations
8
1 club change
Jun 2026€17MEverton FCValuation the model is trained to reproduce

Jun 2026: €17M, Everton FC. Dotted lines mark the €2M, €10M and €30M tier boundaries.

Show as a table
DateMarket valueClub
2024-10-01€5MSouthampton FC
2024-12-16€22MSouthampton FC
2025-03-18€25MSouthampton FC
2025-05-30€25MSouthampton FC
2025-10-17€35MEverton FC
2025-12-09€30MEverton FC
2026-03-09€22MEverton FC
2026-06-03€17MEverton FC

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
+0.396

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 →

Premier League555 players · median €18M

Valued above 49% of the 555 Premier League players.

€150k€1M€7.5M€50M€17MSee them in the Explorer →

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

Valued above 84% of the 1,583 attackers.

€20k€300k€5M€75M€17MSee them in the Explorer →

Where Dibling 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).