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Relative age effect in French alpine skiing: Problem and solution.

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The relative age effect (RAE) biases selections in French alpine skiing, favoring athletes born early in the year. A new mathematical method adjusts performances to reduce this selection bias.

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Area of Science:

  • Sports Science
  • Biomechanical Analysis
  • Talent Identification

Background:

  • The relative age effect (RAE) is a known phenomenon in elite sports, where athletes born earlier in the calendar year have a performance advantage due to developmental and selection biases.
  • In alpine skiing, RAE may influence the identification and development of young talent, potentially overlooking skilled athletes born later in the year.

Purpose of the Study:

  • To investigate the presence and extent of the relative age effect (RAE) in French alpine skiers across various disciplines and genders.
  • To develop and propose a mathematical model for adjusting athletic performance data to mitigate RAE-induced bias in talent selection.

Main Methods:

  • Collected performance data and birthdates of French national and international alpine skiers from 2004 to 2019.
  • Utilized goodness-of-fit chi-square tests and residual analysis to examine birth trimester distributions among young competitors.
  • Developed a linear calibration model linking birth month distribution to performance to derive a correction coefficient for RAE.

Main Results:

  • Confirmed the significant presence of the relative age effect (RAE) in French alpine skiing, with individuals born early in the year being over-represented in elite youth selections.
  • Established a calibration coefficient derived from the relationship between birth month and performance, enabling the adjustment of individual performances.
  • Demonstrated that the proposed method effectively rebalances performance data, accounting for RAE across different genders and disciplines.

Conclusions:

  • The relative age effect (RAE) is a quantifiable bias in French alpine skiing talent pools.
  • The developed mathematical adjustment method provides a tool for coaches to obtain a more objective assessment of skier performance.
  • Implementing this correction can help reduce selection bias and promote fairer talent identification in alpine skiing.