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A case study comparison of objective and subjective evaluation methods of physical qualities in youth soccer players.

James H DugdaleDajo SandersTony D MyersA Mark WilliamsAngus M Hunter
Published in: Journal of sports sciences (2020)
Subjective and objective assessments may be used congruently when making decisions regarding player recruitment in soccer, yet there have been few attempts to examine the level of agreement between these methods. Therefore, we compare levels of agreement between subjective and objective assessments of physical qualities associated with youth soccer performance. In total, 80 male youth soccer players (13.2 ± 1.9 years), and 12 professional coaches volunteered to participate. Players were objectively assessed using five fitness measures: Yo-Yo Intermittent Recovery Test Level 1; Countermovement vertical jump; Functional Movement Screen™; 5/20 m sprint; alongside anthropometric measures. Additionally, coaches subjectively rated each player on the same five physical qualities using 5-point Likert scales. Inter-rater agreement between ratings from lead and assistant coaches was established for each age group. Moreover, Bayesian regression models were fitted to determine how well coach ratings were able to predict fitness test performance. Although inter-rater agreement between lead and assistant coaches was moderate-to-substantial (ω = 0.48-0.68), relationships between coaches subjective rating's and corresponding fitness test performance were only highly related for the highest and lowest performing players. We suggest that while ratings derived from objective and subjective assessment methods may be related when attempting to differentiate between distinct populations, concerns exist when evaluating homogeneous samples using these methods. Our data highlight the benefits of using both types of measures in the talent identification process.
Keyphrases
  • physical activity
  • sleep quality
  • mental health
  • body composition
  • high intensity
  • young adults
  • high throughput
  • depressive symptoms
  • big data
  • resistance training
  • genetic diversity
  • data analysis