FairValue

Checking model

Esc

  • 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.

↑ ↓ to move · Enter to open · Esc to closeLoading player index…

Victor

Sá

LWBrazil · FC Krasnodar

№ 381724Established €2M +0.24

Player dossierPremier Liga

VictorSá

LWLeft WingerAttack

Club
FC Krasnodar
League
Premier Liga
Nationality
Brazil
Age
32
Height
178 cm
Foot
Both
Valued
26 May 2026

Reading the valuation

The market values Sá at €2.5M. Model A, which never saw Sá during training, estimates €2M: the market value is 28% above that estimate.

That is a factor of ×1.28. 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 €922k, 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.

▲ +0.24A €2M▲ +1.00B €922k
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
60
Minutes
4,068
Goals
9
Assists
6
Started
50/60
Min / app
68
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 Sá…

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 €2.5M

Checking API
EmergingEstablishedEliteWorld Class€2M€10M€30M€100k€1M€100MMarket €2.5MModel A €2M

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

Victor Sá's percentiles among attackers: Goals per 90 36th, Assists per 90 44th, Minutes, two years 82nd, Starts 87th, Minutes, last 365 days 72nd, European club minutes 28th36thGoals44thAssists82ndMinutes87thStarts72ndRecent28thEurope

Dashed ring: the attacker median (50th percentile)

Starts

Share of appearances started rather than entered from the bench.

83% this player59% attacker median87th percentile

5%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
€50k
Jul 2015
Peak
€4.5M
Dec 2019
Model target
€2.5M
May 2026
Valuations
28
5 club changes
May 2026€2.5MFC KrasnodarValuation the model is trained to reproduce

May 2026: €2.5M, FC Krasnodar. Dotted lines mark the €2M, €10M and €30M tier boundaries.

Show as a table
DateMarket valueClub
2015-07-16€50kSV Kapfenberg
2015-12-01€150kSV Kapfenberg
2016-05-30€250kSV Kapfenberg
2016-12-03€300kSV Kapfenberg
2017-05-27€400kSV Kapfenberg
2018-01-02€400kLASK
2018-03-30€600kLASK
2018-06-14€1MLASK
2018-10-25€1.5MLASK
2018-12-19€2MLASK
2019-04-15€3MLASK
2019-06-03€3MLASK
2019-12-17€4.5MVfL Wolfsburg
2020-04-08€3.5MVfL Wolfsburg
2021-02-10€3MVfL Wolfsburg
2021-06-09€3MVfL Wolfsburg
2021-11-25€2.5MAl-Jazira Club
2022-08-19€2.5MBotafogo de Futebol e Regatas
2022-11-14€2.5MBotafogo de Futebol e Regatas
2023-04-07€2MBotafogo de Futebol e Regatas
2023-07-25€1.8MBotafogo de Futebol e Regatas
2023-12-11€1.8MBotafogo de Futebol e Regatas
2024-06-04€2MFC Krasnodar
2024-09-18€2.5MFC Krasnodar
2024-12-12€3MFC Krasnodar
2025-06-04€3MFC Krasnodar
2025-12-16€3MFC Krasnodar
2026-05-26€2.5MFC Krasnodar

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
+0.245

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 Liga412 players · median €1M

Valued above 70% of the 412 Premier Liga players.

€50k€300k€2M€15M€2.5MSee them in the Explorer →

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

Valued above 48% of the 1,583 attackers.

€20k€300k€5M€75M€2.5MSee them in the Explorer →

Where Sá 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).