World Cup · Methodology

How it works

Scores estimate each player's current skill for this World Cup. We start from his transfer market value, then correct it for the two things that pull value away from on-pitch ability right now — age and position — before turning it into a 0–99 score.

Step 0

Start: transfer value

A player's market value is Transfermarkt's estimate of his fee today, in euros — a market read that bakes in ability, form, minutes, and league level. It's the best public proxy for quality, but it's skewed: a teenager is priced for potential, a 36-year-old is cheap despite still being elite. So value is the starting point, not the final word.

  • Real Transfermarkt values for 595 players.
  • Estimated values for 165 (listed blank/absent) — modeled from club strength, age, league, and role, flagged with a ~.
Step 1

Age adjustment → current skill

Value reflects future resale, not just skill today: it's inflated by youth potential and deflated by a veteran's short horizon. So value is divided by an age factor — trimming young players' potential premium and lifting proven veterans. The curve is calibrated from the data (each player's current value vs his career-peak value, by age) and then dampened to half strength, since much of the raw decline is genuine skill loss we want to keep (1.0 at the ~27 prime):

19 yrs
÷1.19
young → trimmed
27 yrs
÷1.00
prime → unchanged
34 yrs
÷0.56
veteran → lifted
Step 2

Position adjustment

The market underpays keepers and defenders for equal quality (keepers average ~€3.7m vs ~€11m for midfielders here), so the value is scaled by position to judge each player against his own position's market:

Goalkeeper
×1.68
Defender
×1.04
Midfielder
×0.86
Forward
×0.94

The raw €value shown on roster pages is unadjusted; only the score uses the age- and position-adjusted value.

Step 3

Adjusted value → score (0–99)

The adjusted value becomes a score on a logarithmic curve (score = 70 + 5.47 × ln(value), capped at 99) — log, because values span €0.1m–€200m and a linear scale would crush everyone but the superstars. Each doubling of value ≈ +3.8 points:

€5m 79
€20m 86
€50m 91
€100m 95
€200m 99
Step 4

Team numbers

The app projects each nation's best XI in a 4-3-3, then derives:

  • XI talent — the 11 starters' average score (the headline ranking).
  • GK / DEF / MID / ATT — average score within each line of the XI.
  • XI value — the 11 starters' combined market value.
  • Top player — the squad's highest-rated player.
Step 5

Why teams rank high vs low

A team ranks high when its projected XI is full of in-their-prime players at elite clubs; low when its starters are cheaper, domestic-league names. Because the curve is logarithmic, depth beats a lone superstar; because of the age and position adjustments, a world-class veteran keeper isn't dragged down — and a hyped teenager isn't propped up on potential alone.

Caveats

What this is — and isn't

Without live match stats, this approximates current skill from market value plus age/position corrections — a useful lens, not a perfect rating. 165 players use estimated values, and the groups and bracket are projections, not the official draw. Treat it as “how loaded is each squad on paper” — not a predictor.

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