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.
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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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Léo

Scienza

AMBrazil · Southampton FC

№ 804219Established €6.8M +0.27

Player dossierPremier League

LéoScienza

AMAttacking MidfieldMidfield

Club
Southampton FC
League
Premier League
Nationality
Brazil
Age
27
Height
175 cm
Foot
Both
Valued
3 Dec 2025

Reading the valuation

The market values Scienza at €9M. Model A, which never saw Scienza during training, estimates €6.8M: the market value is 32% above that estimate.

That is a factor of ×1.32. 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 €2.1M, 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 €6.8M▲ +1.46B €2.1M
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
33
Minutes
1,657
Goals
7
Assists
4
Started
19/33
Min / app
50
Cards
2Y 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 Scienza…

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 €9M

Checking API
EmergingEstablishedEliteWorld Class€2M€10M€30M€100k€1M€100MMarket €9MModel A €6.8M

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 1,687 midfielders

Léo Scienza's percentiles among midfielders: Goals per 90 97th, Assists per 90 87th, Minutes, two years 29th, Starts 31st, Minutes, last 365 days 24th, European club minutes 67th97thGoals87thAssists29thMinutes31stStarts24thRecent67thEurope

Dashed ring: the midfielder median (50th percentile)

Goals per 90

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

0.38 this player0.08 midfielder median97th percentile

0.00peer deciles · median line · this player ●0.93

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
€75k
Nov 2020
Peak
€9M
Oct 2025
Model target
€9M
Dec 2025
Valuations
15
4 club changes
Dec 2025€9MSouthampton FCValuation the model is trained to reproduce

Dec 2025: €9M, Southampton FC. Dotted lines mark the €2M, €10M and €30M tier boundaries.

Show as a table
DateMarket valueClub
2020-11-10€75kFC Schalke 04 II
2021-01-05€100kFC Schalke 04 II
2021-06-26€100kFC Schalke 04 II
2021-12-22€100kFC Schalke 04 II
2022-06-13€200kFC Schalke 04 II
2022-11-30€250k1.FC Magdeburg
2023-06-28€200k1.FC Magdeburg
2023-12-28€300kSSV Ulm 1846
2024-03-20€450kSSV Ulm 1846
2024-06-11€1MSSV Ulm 1846
2024-10-09€2.5M1.FC Heidenheim 1846
2024-12-20€3M1.FC Heidenheim 1846
2025-06-05€3M1.FC Heidenheim 1846
2025-10-06€9MSouthampton FC
2025-12-03€9MSouthampton FC

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
+0.274

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 31% of the 555 Premier League players.

€150k€1M€7.5M€50M€9MSee them in the Explorer →

Midfielders, all leagues1,687 players · median €2M

Valued above 77% of the 1,687 midfielders.

€20k€200k€2M€20M€9MSee them in the Explorer →

Where Scienza 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).