FairValue

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  • EnvironmentOverviewWhat FairValue measures, what it found, where to go next.
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  • TerminalPlayer ExplorerSearch, filter and sort the player export.
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  • TerminalMarket LandscapeHow observed value is distributed, and where the model drifts.

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Rubén

Vargas

LWSwitzerland · Sevilla FC

№ 345886Elite €3.9M +1.12

Player dossierLaLiga

RubénVargas

LWLeft WingerAttack

Club
Sevilla FC
League
LaLiga
Nationality
Switzerland
Age
27
Height
179 cm
Foot
Right
Valued
5 Jun 2026

Reading the valuation

The market values Vargas at €12M. Model A, which never saw Vargas during training, estimates €3.9M: the market value is 207% above that estimate.

That is a factor of ×3.07. Model A's typical held-out miss is ×1.50 either way, so this gap is larger than its usual error.

Without league and club, Model B estimates €4M, closer to the market here, although it is usually further off (typical miss ×2.07).

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

▲ +1.12A €3.9M▲ +1.11B €4M
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
46
Minutes
2,667
Goals
6
Assists
7
Started
32/46
Min / app
58
Cards
5Y 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 Vargas…

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 €12M

Checking API
EmergingEstablishedEliteWorld Class€2M€10M€30M€100k€1M€100MMarket €12MModel A €3.9M

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

Rubén Vargas's percentiles among attackers: Goals per 90 37th, Assists per 90 80th, Minutes, two years 60th, Starts 68th, Minutes, last 365 days 61st, European club minutes 28th37thGoals80thAssists60thMinutes68thStarts61stRecent28thEurope

Dashed ring: the attacker median (50th percentile)

Assists per 90

Club assists per 90 minutes in the same window.

0.24 this player0.15 attacker median80th percentile

0.00peer deciles · median line · this player ●0.73

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
€100k
Jul 2017
Peak
€13M
Nov 2020
Model target
€12M
Jun 2026
Valuations
30
2 club changes
Jun 2026€12MSevilla FCValuation the model is trained to reproduce

Jun 2026: €12M, Sevilla FC. Dotted lines mark the €2M, €10M and €30M tier boundaries.

Show as a table
DateMarket valueClub
2017-07-12€100kFC Luzern
2017-09-29€300kFC Luzern
2018-01-08€300kFC Luzern
2018-04-24€500kFC Luzern
2018-07-12€1MFC Luzern
2019-01-21€2MFC Luzern
2019-04-15€2.8MFC Luzern
2019-06-04€4MFC Luzern
2019-10-02€7MFC Augsburg
2019-12-17€8MFC Augsburg
2020-03-11€10MFC Augsburg
2020-04-08€9MFC Augsburg
2020-11-26€13MFC Augsburg
2021-02-10€13MFC Augsburg
2021-05-25€13MFC Augsburg
2021-10-07€11MFC Augsburg
2021-12-22€11MFC Augsburg
2022-03-24€9MFC Augsburg
2022-06-09€8MFC Augsburg
2022-09-21€6MFC Augsburg
2022-11-09€6MFC Augsburg
2023-06-22€6.5MFC Augsburg
2023-12-14€6.5MFC Augsburg
2024-05-29€7.5MFC Augsburg
2024-07-18€9MFC Augsburg
2024-12-20€7MFC Augsburg
2025-06-09€7MSevilla FC
2025-10-02€11MSevilla FC
2025-12-12€12MSevilla FC
2026-06-05€12MSevilla 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
+1.122

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 →

LaLiga509 players · median €4M

Valued above 77% of the 509 LaLiga players.

€100k€1M€10M€100M€12MSee them in the Explorer →

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

Valued above 79% of the 1,583 attackers.

€20k€300k€5M€75M€12MSee them in the Explorer →

Where Vargas 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).