FarleyRosa

LWLeft WingerAttack

Club: Panetolikos
League: Super League
Nationality: Brazil
Age: 32
Height: 174 cm
Foot: Right
Valued: 4 Jun 2026

Reading the valuation

The market values Rosa at €400k. Model A, which never saw Rosa during training, estimates €474k: the market value is 16% below that estimate.

That is a factor of ×1.18. 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 €402k, 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.

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: 7
Minutes: 505
Goals: 2
Assists: 2
Started: 7/7
Min / app: 72
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 Rosa…

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 €400k

Checking API

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

Dashed ring: the attacker median (50th percentile)

Starts

Share of appearances started rather than entered from the bench.

100% this player59% attacker median100th 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: €100k; Jul 2013
Peak: €900k; May 2018
Model target: €400k; Jun 2026
Valuations: 26; 14 club changes

Jun 2026€400kPanetolikosValuation the model is trained to reproduce

Jun 2026: €400k, Panetolikos. Dotted lines mark the €2M, €10M and €30M tier boundaries.

Show as a table

Date	Market value	Club
2013-07-22	€100k	FC Sevastopol
2014-01-02	€500k	FC Sevastopol
2014-06-30	€600k	FC Sevastopol
2015-04-11	€550k	Apollon Limassol
2016-05-05	€600k	AEK Larnaca
2016-12-21	€500k	Panetolikos
2017-05-11	€600k	Panetolikos
2017-12-18	€750k	Panetolikos
2018-05-22	€900k	Panetolikos
2019-01-08	€700k	Al-Ettifaq FC
2019-09-23	€700k	Atromitos Athens
2019-12-18	€600k	Atromitos Athens
2020-04-08	€475k	Panetolikos
2020-08-04	€500k	Panetolikos
2020-12-04	€700k	Al-Fujairah SC
2021-05-29	€500k	Hapoel Beer Sheva
2021-12-31	€500k	Hapoel Tel Aviv
2022-05-28	€400k	Tianjin Jinmen Tiger
2023-01-13	€650k	Tianjin Jinmen Tiger
2023-06-26	€900k	Tianjin Jinmen Tiger
2023-12-14	€700k	Tianjin Jinmen Tiger
2024-06-14	€650k	Daejeon Hana Citizen
2024-12-11	€450k	Nantong Zhiyun
2025-06-23	€450k	Guangdong GZ-Power
2025-12-09	€450k	Guangdong GZ-Power
2026-06-04	€400k	Panetolikos

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: −0.169

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 →

Super League356 players · median €600k

Valued above 29% of the 356 Super League players.

See them in the Explorer →

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

Valued above 11% of the 1,583 attackers.

See them in the Explorer →

Where Rosa appears

TerminalSuper League in the Player Explorer
TerminalSuper League on the League Landscape

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).