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Record W3009584864 · doi:10.5539/jel.v9n2p134

Examining the Relation Between the Physical Features of 10–12 Year-Old Male Tennis Players and the Speeds of the Service Strikes

2020· article· en· W3009584864 on OpenAlexvenueno aff
Yunus Emre Bağış

Bibliographic record

VenueJournal of Education and Learning · 2020
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsnot available
Fundersnot available
KeywordsCircumferenceAnimal scienceMathematicsAnthropometryMedicinePhysical therapyInternal medicineGeometryBiology

Abstract

fetched live from OpenAlex

The purpose of the present study was to examine the relation between the physical characteristics of male tennis players who were aged 10–12 and their service strike speeds. A total of 13 licensed male tennis players (mean age 10.1±0.1 years, mean height 1.46±.06 m, mean body weight 38.7±1.8 kg, mean sporting age 4.7±0.3 years) who played at Middle East Technical University Tennis Club participated in the study. The demographic, anthropometric, (width, length, circumference, and subcutaneous fat) and ball speed measurements of the tennis players were taken and recorded. The data were analyzed by using the “Descriptive Statistics” and “Pearson Correlation” in the Statistical Package Program. When length measurements were examined, it was determined that although there was a positive relation between ball speeds and hand length (p<0.05); a negative relation was detected between the other measurements (p>0.05). When the width measurements were evaluated, it was determined that although there was a positive relation between ball speeds and chest, elbow and wrist widths (p<0.05); a negative relation was detected between the other measurements (p>0.05). In terms of the circumferences, although a positive relation was detected between ball speeds and arm contraction, chest, chest inspiration, and chest expiration circumference (p<0.05); a negative relation was detected between the other circumference measurements (p>0.05). When subcutaneous fat measurements were examined, it was determined that there was a negative relation between ball speeds (p>0.05). As a result, when previous studies and literature were examined, it was determined that many studies emphasized that the factors that affect the service speed of young tennis players have a positive relationship with age. It is obvious that the strength features, and depending on this, anthropometric properties improve with age. It is considered that special force and technical training drills, regardless of the age category, may affect the speed and accuracy of the service strike in tennis. Our study offers a different perspective to coaches on this subject.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.034
GPT teacher head0.287
Teacher spread0.253 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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