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Record W7066948649

The Influence of Growth and Maturation on Technical Skill Development in Youth Soccer

2024· dissertation· en· W7066948649 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2024
Typedissertation
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsnot available
Fundersnot available
KeywordsAnthropometrySittingPositive Youth DevelopmentMatch playTest (biology)Dreyfus model of skill acquisitionFootball
DOInot available

Abstract

fetched live from OpenAlex

Background: Youth soccer teams typically use chronological age-banded tryouts to select final rosters; therefore, youth players are more likely to be selected for the short-term advantages of early maturation rather than skill. Because of this, later maturing individuals may be overlooked or deselected, even if they have the greatest potential for the sport. Although it has been shown that growth and maturational influence soccer performance, less is known about its effects on soccer skill development. Skill is the learned ability to bring maximum certainty about pre-determined results. Traditionally, skill has been assessed subjectively; however, objective measures, such as the Loughborough Soccer Passing Test (LSPT), have recently been developed. The LSPT can distinguish various components of skill performance between players of different abilities. This thesis investigated how growth and maturation influence youth soccer skills development as assessed by the LSPT. A secondary aim was to compare skill development between the sexes. The third aim was to investigate the role of fat mass on skill development. Methods: A convenience sample of youth soccer players aged 9 to 15 were recruited from ASTRA Soccer Academy, Saskatoon. Soccer descriptives were collected by questionnaire. Anthropometric measures included height, sitting height, weight, and fat composition (Tanita DC-13C). Chronological age (CA) was determined from birth and measurement date. Biological age (BA) was estimated using an anthropometric equation to predict years from attainment of peak height velocity (PHV). The LSPT assessed soccer-specific technical skills. Skills were assessed in a designated area, and time to complete with penalties was recorded. The lower the time, the higher the technical skills rating. Descriptive statistics, correlations and ANCOVA were used to analyze the data. Results: 42 players were recruited (12 males and 30 females). The CA age range was 9.6 to 15.2 years and BA was -2.9 to 2.9 years from PHV. Males had significantly lower times than females (p <0.05), and scores decreased with increasing BA (p < 0.05). No relationship was found between BMI (r = 0.22) and body fat percentage (r =0.02) with LSPT score. Conclusion: The results suggest skill acquisition is associated with children’s growth and maturation. This suggests that coaches should consider a player’s growth and maturational status when objectively identifying a soccer player’s skill.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.185
Teacher spread0.179 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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