Relative Age Effect in Football Academies: What the Research Says About Who Gets Selected

6 min read · March 2026

A study published in the International Journal of Sports Science and Coaching followed players through the Football Association of Ireland's national talent pathway and found that early-maturing boys made up as much as 74% of some academy cohorts. Late maturers were not just under-represented. In some squads, they were absent entirely. The same research estimated that early-maturing boys were up to twenty times more likely to be retained in the academy system than their late-maturing peers of equivalent technical ability.

This research comes from the FAI pathway. The pattern it describes isn't just specific to Ireland, however. It's the default state of elite youth football across Europe.

Most academy recruitment frameworks are built around this question: who is the best player in this cohort right now?

The evidence though points to a different question that would serve the development mission better: who is most likely to be the best player in this cohort in six years?

Most academy systems have only built infrastructure to answer the former.

What selection is actually measuring

When you ask academy staff what they look for, the answers are broadly consistent: technical ability, decision-making under pressure, psychological resilience, physical qualities. The four-corner model, holistic assessment.

The research on what drives retain-and-release decisions tells a more specific story.

A 2023 paper exploring how academy coaches make maturation-related selection judgements found that staff routinely perceived early-maturing players as more capable and better long-term prospects, on the basis of physical dominance that is present at thirteen and largely gone by eighteen.

A study of (de)selection processes at an English Category 2 academy found that retain-and-release meetings were structured around anthropometric profiling and physical testing data: sprint times, jump heights, body mass. The Premier League's EPPP requires clubs to upload player fitness data into a central Performance Management Application, where each player is benchmarked against biological, chronological and positional standards across the whole system.

The infrastructure is built to measure physical profile and this is what the system rewards.

Longitudinal work by Noon and colleagues, tracking 76 players aged 11–16 over five years at an English academy, found that being recruited before U12 was among the strongest predictors of earning a professional contract, with 87% of contracted players having entered the system before the age of twelve. Enter early, track well against the benchmarks, stay in. The selection filter operates from the moment a player first appears on a club's radar.

What those selection criteria cost

The relative age effect (RAE) is the most documented expression of this pattern. A 2022 multi-club study of 1,003 players across 23 UK professional academies confirmed the standard finding: players born in the first quarter of the selection year were substantially over-represented across squads at every age group. A 2024 longitudinal study followed players from academy intake through to professional careers and found that late-born survivors (the players who got in despite the bias working against them) went on to accumulate more professional minutes than their early-born teammates. The players the system was most likely to discard were, on average, the ones with the longer careers.

A 2025 economics paper on elite academy selection framed this directly as a misallocation of talent. Relatively older players are heavily over-selected at youth level. Late-born players who survive show higher underlying ability measures, by the paper's own assessment. The investment in selecting, developing and eventually releasing the over-selected early-borns was, by the paper's measure, largely wasted.

The early specialisation literature adds a welfare dimension the talent identification debate consistently underweights. A 2024 clinical review concluded that specialising in a single sport at young ages is linked to higher rates of overuse injury, worse mental health and no clear advantage for long-term elite success when compared to more diversified developmental paths. A 2020 systematic review and meta-analysis found higher burnout scores across all three dimensions (reduced accomplishment, sport devaluation and emotional exhaustion) in specialised athletes compared to those who had sampled multiple sports.

Academy pathways that implicitly demand year-round single-sport commitment from pre-teen ages are not neutral on this question. They're selecting for families and children who'll tolerate the load. Whether those children have the best long-term potential is a another matter.

What bio-banding tells you

The Premier League's bio-banding experiments are an admission in itself.

A tournament in which players from four clubs were grouped by biological maturity, set aside from their standard age groupings, found that early maturers reported matches as more physically challenging and were forced to rely on technique and tactics. Late maturers, the players the standard system was most likely to overlook, finally had space to show the technical and psychological qualities the age-grouped format had kept invisible.

A bio-banding intervention only needs to exist because the default format is producing a skewed picture of ability. The fact it works and the Premier League is documenting that it works, means the standard development environment isn't showing clubs what they think it's showing them.

The question worth asking

None of this is straightforward to fix from inside a club. The EPPP benchmarking structure isn't optional. The annual reporting cycle creates pressure to show physical progress at fixed points. Clubs competing for the same pool of early developers are operating in a system that rewards the same biases it produces.

But there are practical starting points.

Track your own retain-and-release data by birth quarter and maturation status over three or four seasons. If early maturers are being retained at significantly higher rates than late maturers at equivalent technical assessments, the bias is operating in your environment. Naming it changes what your staff attend to in the next cycle.

When evaluating younger players, build developmental projection into the process deliberately: not "how good is this player now?" but "what do we expect this player to look like at eighteen?" Making it an explicit question shifts the frame of every assessment conversation.

Consider where bio-banding can sit alongside your standard programme, even in training rather than competition. The evidence on what late maturers can show when the physical gap is removed is consistent enough that most clubs experimenting with it have continued.

The question the research keeps returning to isn't whether early specialisation, maturation bias and the RAE exist in your academy.

They almost certainly do.

It's worth asking whether your staff can see them clearly enough to factor them into the decisions they're already making.

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