FairValue

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

Lorents

CMDenmark · Silkeborg IF

№ 1003295Emerging €979k −0.34

Player dossierSuperliga

JuliusLorents

CMCentral MidfieldMidfield

Club
Silkeborg IF
League
Superliga
Nationality
Denmark
Age
20
Height
178 cm
Foot
–
Valued
25 May 2026

Reading the valuation

The market values Lorents at €700k. Model A, which never saw Lorents during training, estimates €979k: the market value is 29% below that estimate.

That is a factor of ×1.40. 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 €1.8M, 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.

▼ −0.34A €979k▼ −0.96B €1.8M
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
1,507
Goals
0
Assists
0
Started
11/37
Min / app
41
Cards
1Y 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 Lorents…

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 €700k

Checking API
EmergingEstablishedEliteWorld Class€2M€10M€30M€100k€1M€100MMarket €700kModel A €979k

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

Julius Lorents's percentiles among midfielders: Goals per 90 10th, Assists per 90 8th, Minutes, two years 25th, Starts 5th, Minutes, last 365 days 36th, European club minutes 77th10thGoals8thAssists25thMinutes5thStarts36thRecent77thEurope

Dashed ring: the midfielder median (50th percentile)

European club minutes

Share of minutes played in UEFA club competitions.

15% this player0% midfielder median77th percentile

0%peer deciles · median line · this player ●85%

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
€400k
Jun 2025
Peak
€800k
Dec 2025
Model target
€700k
May 2026
Valuations
3
1 club change
May 2026€700kSilkeborg IFValuation the model is trained to reproduce

May 2026: €700k, Silkeborg IF. Dotted lines mark the €2M, €10M and €30M tier boundaries.

Show as a table
DateMarket valueClub
2025-06-16€400kSilkeborg IF U19
2025-12-15€800kSilkeborg IF
2026-05-25€700kSilkeborg IF

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
−0.336

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 →

Superliga256 players · median €800k

Valued above 39% of the 256 Superliga players.

€20k€150k€1M€7.5M€700kSee them in the Explorer →

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

Valued above 23% of the 1,687 midfielders.

€20k€200k€2M€20M€700kSee them in the Explorer →

Where Lorents 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).