FairValue

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

Johannesen

CMDenmark · FC Fredericia

№ 1017247Emerging €743k −0.30

Player dossierSuperliga

SofusJohannesen

CMCentral MidfieldMidfield

Club
FC Fredericia
League
Superliga
Nationality
Denmark
Age
19
Height
–
Foot
–
Valued
25 May 2026

Reading the valuation

The market values Johannesen at €550k. Model A, which never saw Johannesen during training, estimates €743k: the market value is 26% below that estimate.

That is a factor of ×1.35. 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 €459k, 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.

▼ −0.30A €743k▲ +0.18B €459k
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
749
Goals
4
Assists
1
Started
8/15
Min / app
50
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 Johannesen…

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 €550k

Checking API
EmergingEstablishedEliteWorld Class€2M€10M€30M€100k€1M€100MMarket €550kModel A €743k

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

Sofus Johannesen's percentiles among midfielders: Goals per 90 99th, Assists per 90 60th, Minutes, two years 7th, Starts 26th, Minutes, last 365 days 22nd, European club minutes 30th99thGoals60thAssists7thMinutes26thStarts22ndRecent30thEurope

Dashed ring: the midfielder median (50th percentile)

Goals per 90

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

0.48 this player0.08 midfielder median99th percentile

0.00peer deciles · median line · this player ●0.93

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
€150k
Oct 2025
Peak
€550k
May 2026
Model target
€550k
May 2026
Valuations
3
0 club changes
May 2026€550kFC FredericiaValuation the model is trained to reproduce

May 2026: €550k, FC Fredericia. Dotted lines mark the €2M, €10M and €30M tier boundaries.

Show as a table
DateMarket valueClub
2025-10-28€150kFC Fredericia
2025-12-15€250kFC Fredericia
2026-05-25€550kFC Fredericia

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
−0.300

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 32% of the 256 Superliga players.

€20k€150k€1M€7.5M€550kSee them in the Explorer →

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

Valued above 19% of the 1,687 midfielders.

€20k€200k€2M€20M€550kSee them in the Explorer →

Where Johannesen 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).