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…

Portrait of Marko Pjaca

Marko

Pjaca

LWCroatia · FC Twente Enschede

№ 205940Emerging €1.4M +0.08

Image: FootyLogos

Player dossierEredivisie

MarkoPjaca

LWLeft WingerAttack

Club
FC Twente Enschede
League
Eredivisie
Nationality
Croatia
Age
31
Height
186 cm
Foot
Right
Valued
28 May 2026

Reading the valuation

The market values Pjaca at €1.5M. Model A, which never saw Pjaca during training, estimates €1.4M: the market value is 9% above that estimate.

That is a factor of ×1.09. 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 €2.2M, 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.

▲ +0.08A €1.4M▼ −0.40B €2.2M
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
37
Minutes
1,464
Goals
5
Assists
5
Started
14/37
Min / app
40
Cards
3Y 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 Pjaca…

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 €1.5M

Checking API
EmergingEstablishedEliteWorld Class€2M€10M€30M€100k€1M€100MMarket €1.5MModel A €1.4M

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

Marko Pjaca's percentiles among attackers: Goals per 90 58th, Assists per 90 91st, Minutes, two years 31st, Starts 18th, Minutes, last 365 days 36th, European club minutes 96th58thGoals91stAssists31stMinutes18thStarts36thRecent96thEurope

Dashed ring: the attacker median (50th percentile)

European club minutes

Share of minutes played in UEFA club competitions.

33% this player0% attacker median96th percentile

0%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
Feb 2012
Peak
€18M
Jul 2016
Model target
€1.5M
May 2026
Valuations
35
13 club changes
May 2026€1.5MFC Twente EnschedeValuation the model is trained to reproduce

May 2026: €1.5M, FC Twente Enschede. Dotted lines mark the €2M, €10M and €30M tier boundaries.

Show as a table
DateMarket valueClub
2012-02-29€50kNK Lokomotiva Zagreb
2012-09-30€50kNK Lokomotiva Zagreb
2013-03-03€100kNK Lokomotiva Zagreb
2013-10-08€500kNK Lokomotiva Zagreb
2014-03-11€950kNK Lokomotiva Zagreb
2014-10-01€1.5MGNK Dinamo Zagreb
2015-03-17€3.5MGNK Dinamo Zagreb
2015-09-14€6.5MGNK Dinamo Zagreb
2016-03-14€7MGNK Dinamo Zagreb
2016-06-01€8MGNK Dinamo Zagreb
2016-07-21€18MJuventus FC
2017-01-02€18MJuventus FC
2017-06-08€15MJuventus FC
2017-12-29€15MJuventus FC
2018-06-05€15MFC Schalke 04
2018-12-20€12.5MACF Fiorentina
2019-03-01€10MACF Fiorentina
2019-06-06€10MACF Fiorentina
2019-12-12€7.5MJuventus FC
2020-04-08€6MRSC Anderlecht
2020-08-25€5MJuventus FC
2020-12-29€5MGenoa CFC
2021-06-03€4MGenoa CFC
2021-12-28€4MTorino FC
2022-06-07€3.5MTorino FC
2022-11-11€3MFC Empoli
2023-03-21€2.2MFC Empoli
2023-06-15€1.7MFC Empoli
2023-12-18€1.7MHNK Rijeka
2024-06-04€2.5MHNK Rijeka
2024-12-23€2.7MGNK Dinamo Zagreb
2025-06-09€2.7MGNK Dinamo Zagreb
2025-12-02€2.7MFC Twente Enschede
2026-03-11€2MFC Twente Enschede
2026-05-28€1.5MFC Twente Enschede

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
+0.082

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 →

Eredivisie425 players · median €1M

Valued above 54% of the 425 Eredivisie players.

€75k€500k€3M€20M€1.5MSee them in the Explorer →

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

Valued above 37% of the 1,583 attackers.

€20k€300k€5M€75M€1.5MSee them in the Explorer →

Where Pjaca 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).