FairValue

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  • EnvironmentOverviewWhat FairValue measures, what it found, where to go next.
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Guilherme

Bahia

LWBrazil · NK Veres Rivne

№ 1253920Emerging €226k −0.12

Player dossierPremier Liha

GuilhermeBahia

LWLeft WingerAttack

Club
NK Veres Rivne
League
Premier Liha
Nationality
Brazil
Age
20
Height
170 cm
Foot
Left
Valued
2 Jun 2026

Reading the valuation

The market values Bahia at €200k. Model A, which never saw Bahia during training, estimates €226k: the market value is 11% below that estimate.

That is a factor of ×1.13. 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 €588k, 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.

▼ −0.12A €226k▼ −1.08B €588k
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
15
Minutes
487
Goals
1
Assists
0
Started
5/15
Min / app
32
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 Bahia…

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 €200k

Checking API
EmergingEstablishedEliteWorld Class€2M€10M€30M€100k€1M€100MMarket €200kModel A €226k

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

Guilherme Bahia's percentiles among attackers: Goals per 90 32nd, Assists per 90 6th, Minutes, two years 1st, Starts 14th, Minutes, last 365 days 13th, European club minutes 28th32ndGoals6thAssists1stMinutes14thStarts13thRecent28thEurope

Dashed ring: the attacker median (50th percentile)

Goals per 90

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

0.18 this player0.26 attacker median32nd percentile

0.00peer deciles · median line · this player ●1.17

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
Mar 2026
Peak
€200k
Jun 2026
Model target
€200k
Jun 2026
Valuations
2
0 club changes
Jun 2026€200kNK Veres RivneValuation the model is trained to reproduce

Jun 2026: €200k, NK Veres Rivne. Dotted lines mark the €2M, €10M and €30M tier boundaries.

Show as a table
DateMarket valueClub
2026-03-23€100kNK Veres Rivne
2026-06-02€200kNK Veres Rivne

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
−0.121

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 Liha414 players · median €400k

Valued above 10% of the 414 Premier Liha players.

€50k€200k€1M€5M€200kSee them in the Explorer →

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

Valued above 4% of the 1,583 attackers.

€20k€300k€5M€75M€200kSee them in the Explorer →

Where Bahia 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).