How ScoutMePlay scores
Every report is built around the same four player-development pillars used across European Category-1 youth academies. This page explains exactly how we evaluate, benchmark, and tier players — so coaches, scouts, and parents can understand and trust the numbers.
Aligned with UEFA youth-development pillars · Not certified or endorsed by UEFA
The four pillars
Skills with the ball — first touch, ball control, passing, dribbling, shooting, weak-foot use, 1v1.
Decisions without the ball — positioning, off-ball movement, scanning, decision-making, timing of runs, game understanding.
Athletic foundation — acceleration, speed, balance, agility, intensity (90-minute), body control.
Habits and character — confidence, work rate, courage in duels, response to mistakes, competitive mindset, focus.
Every sub-skill maps to one of these four pillars — the same framework used across European elite-youth coaching curricula.
The four-tier ladder
Each sub-skill is scored 1–10 and then placed into one of four tiers, calibrated to the player's age bracket and position. The tier shows where this player sits today, not where they might end up.
Top-end Category-1 academies of national associations (e.g. La Masia, Clairefontaine, Cobham-level). Roughly the top 1–3% of an age group.
Strong regional or national pro-club academies. Trial-ready for serious competitive pathways. Roughly the top 10–15%.
Higher-level competitive club football — best teams in the region, talent centres, district selections. Roughly the top 30%.
Mainstream club football where most players develop. The baseline for organised youth football.
Age brackets
A 7/10 for first touch means something different at U11 than at U17. We calibrate every score against the typical milestone for the age bracket and position.
Foundation — coordination, ball mastery, basic decision-making.
Build phase — scanning habits, positional discipline, both-footed development.
Performance phase — match impact, pressing intensity, tactical role clarity.
Specialisation — position-specific excellence, physical maturity, mental resilience.
Pre-professional — match management, leadership, consistency across 90 minutes.
Professional threshold — high-performance habits, durability, decision quality at speed.
Position adjustments
Each attribute is weighted by position. A centre-back's tier ladder emphasises aerial duels, positioning, and 1v1 defending. A central midfielder's emphasises scanning, passing range, and press-resistance. A winger's emphasises acceleration, 1v1 dribbling, and final-ball delivery. Two players with the same overall score can sit in different tiers depending on their position.
Confidence scoring
Every score carries a confidence level based on how many clear observations were available in the footage:
- High confidence — 6 or more clear observations of the skill
- Medium confidence — 3–5 observations
- Low confidence — 1–2 observations; treat as directional
- Need more footage — skill not observable in the clip; we mark it as such rather than guess
What we don't claim
- · We are not UEFA-certified. We align with the same pillars used in UEFA elite-youth coaching education — that's it.
- · We don't publish childhood scores of professional players. Stylistic archetype comparisons describe style, not factual youth data.
- · We don't guarantee selection, signing, or progression to any club or academy.
- · Set-pieces from open play, off-camera defensive work, and goalkeeping moments are not assessable from outfield clips.
Data sources & calibration
Every comparison and tier in this report is anchored against publicly verifiable senior-pro data — never against pure curated guesses. Three open datasets do the heavy lifting:
StatsBomb Open Data · UEFA Euro 2024
Used to calibrate the "Pro Calibration" panel on every report. For each player position, we pre-computed per-90 percentiles (p25 / p50 / p75 / p90) of: pass completion, progressive passes, key passes, xG, goals, dribbles completed, duels won, pressures, interceptions, ball recoveries. The player's scores are then anchored to these distributions — so "8/10 passing" literally means "top 25% of Euro 2024 starters at this position."
github.com/statsbomb/open-data · License: CC BY-NC-SA 4.0 (StatsBomb Open Data terms) · Updated annually.
EA Sports FIFA · 7,473 senior pros
Used by the "FIFA Data Twin" panel to run a real k-nearest-neighbour similarity search across senior pros. We pre-process the public Kaggle FIFA dataset into a slim runtime file, map every FIFA attribute (ball control, dribbling, short-passing, vision, composure, acceleration, balance, etc.) onto the same 0-10 scale we use for the player, then compute per-attribute Euclidean RMSE.The reported similarity is hard-capped at 92% — a youth player's scoring vector should never report 99% match to a peak-career pro; capping it keeps the figure honest.
Source: Kaggle FIFA 22 complete dataset (Stefano Leone) · attribute ratings © EA Sports, used in a derived non-republished form for similarity matching only.
FBref & Transfermarkt · career snapshots
Powers the "Career snapshot" block on every archetype card — career appearances, trophies, FBref per-90 stats (e.g. "Modric career pass completion ~88% across 13 La Liga seasons"). All numbers are researched offline and shipped inarchetypes.json; we never scrape FBref at runtime to respect Sports Reference's terms of service.
Career data cross-referenced against FBref career-totals, Transfermarkt player profiles, and the player's Wikipedia infobox at build time. Annual refresh.
Why pre-compute everything offline? Runtime web scraping is fragile, slow, and legally grey. Every dataset above is licensed for the use described, processed into a slim runtime file at build time, then cited verbatim in the report — so a scout or parent can independently verify any number we cite.