A 2026 review kept 38 talent-ID studies from 7,186 records. Tests and coach ratings should guide cuts only when validated against later level and adjusted for age, maturity, position and match context.

A 2026 Frontiers in Psychology review screened 7,186 records and retained 38 empirical studies from 1976 to 2024, covering more than 48,000 youth players from U9 to U19.

Researchers first measured height, weight, sprint speed and jump tests, then added ball skills and physiological tests, and later included psychological and social questionnaires and tracking data.

The review applies less clearly outside male adolescents, Europe and English-language publication. 91.4% of the included studies focused only on male adolescents, Europe supplied 54.3% of the evidence base, and English-language publication was required. ¹

After a scout’s first look, a test or rating must predict later playing level before the club uses it to keep or release a player.

Clubs can use a fast 20-metre sprint, strong jump, tidy dribble test or coach rating only if it predicts later football level against the right age group, maturity band, role and match context.

In a German DFB prospective study, 13,869 male U12 to U15 players completed objective motor tests and were rated by coaches. Three seasons later, only 9% reached professional youth academy level.

Subjective ratings and objective tests each had predictive value, but the combined model performed best in every age group, with Nagelkerke R2 from 0.15 to 0.20. Sprint, tactical skills and dribbling were the strongest predictors in that combined model. ²

Written ratings of pre-orientation, first touch, situation-appropriate decision-making and follow-up action can be compared with a player’s later level. The DFB coach-rating manual asked coaches to rate tactical behaviour before, during and after ball actions, including pre-orientation, offering or creating space, first touch, orientation on the ball, situation-appropriate decision-making, re-orientation and follow-up action.

A survey of 125 soccer scouts found that scouts often reported structured assessment but still formed final predictions through intuitive integration; scouts watching players aged 12 or younger thought reliable professional-potential prediction was possible only at 13.6 years old on average. ³

The long-term German U12 cohort did not support using one early test as a stand-alone selection tool. The study followed 14,178 U12 players for roughly eight to 10 years; 89 became professional and 913 semi-professional.

The model explained 24.8% of adult performance level, and technical skills appeared stronger than speed abilities, but the authors still warned that the effect sizes were too limited for exclusive selection decisions. ⁴

Chronological age, relative age and biological maturity can each distort how a youth player is assessed. A 2020 German maturity-diagnostics study compared pragmatic maturity measures with MRI skeletal age in 63 elite male U12 and U14 players. The practical measures correlated with MRI, but individual differences remained, so the authors recommended at least two maturity assessment methods.

A 2025 Austrian academy study found significant relative age effects in U14 and U15 teams, and maturity offset correlated strongly with eccentric hamstring strength, vertical jump and sprint performance. ^{5 6}

Small-sided games let staff count touches, ball time, high-speed releases, running and accelerations in play. A Scottish FA selection-trial study put 90 adolescent players through physical tests, anthropometrics and eight 9v9 small-sided games using foot-mounted inertial measurement units.

Successful players had more touches, more time on the ball, more high-speed releases, more high-speed running and more accelerations during the games. The study was still small and cross-sectional, and its maturity estimates carried error. ⁷

The Premier League EPPP page describes benchmark fitness testing and maturation screening across a large academy system. The Premier League EPPP page describes a programme for ages 9 to 23, with benchmark fitness testing from U12 to U23, comparisons by biological age, chronological age and position, and growth and maturation screening around peak height velocity. ⁸

Bio-banding changes the comparison group, so academy staff need coach buy-in and player understanding before players move down. A bio-banding practitioner study surveyed 25 academy practitioners and interviewed seven; 80% had implemented bio-banding, but coaches’ buy-in, lack of understanding and social stigma around playing down were reported barriers.

When an early-maturing player cannot rely on size against similar bodies, staff can watch the first touch, pass choice and movement after release; when a late-maturing player faces similar bodies, staff can see whether the technical level was hidden by contact and reach. ⁹

Studies on boys do not prove that the same tests predict outcomes for girls and women. A 2025 German U15 female study followed 264 players and found that adding coach ratings to objective tests helped predict U17 Bundesliga and Women’s Bundesliga outcomes.

The same study noted that biological maturation was not considered, so the maturity question remains open in that sample. ¹⁰

Each player file should keep the outcome, test and coach grades, age-maturity data and football context before selectors meet.

Player files should state whether the club is predicting academy retention, U17 Bundesliga, professional youth academy, semi-pro or pro level. Coach grades, sprint and jump scores, dribble tests, touches, ball time and small-sided-game actions should also be in the file.

The third is the age and maturity file with birth quartile, height, sitting height, body mass and two maturity estimates. The fourth is the football context, including position, minutes, level, opposition and format.

If the club cannot check a criterion against those records, staff should use it for monitoring rather than release or retention on its own.