Data · dataset · 2025
Developmental performance trajectories of talented tennis players during adolescence: a prospective longitudinal approach
Listed in IISH Dataverse and ODISSEI Portal — shown once because both records carry DOI 10.34894/qarluv
The development of talent may take different forms for youth athletes, but there are only few longitudinal studies tracking this process.
Description
This study prospectively examines: 1) the development of talented Dutch tennis players aged 11.5 to 16, and 2) the predictability of performance at age 16, based on players’ performance in preceding years. Biannually, we collected performance rating data of 1010 players (645 males, 365 females), who were ranked top-300 in the national youth ranking at least once.
Applying Growth Mixture Modelling, we found that a 4-class model fit the male sample, while a 5-class model fit the female sample. The best male class displayed non-linear development, improving slowly until age 13.5, after which development accelerated. The best female class showed consistent linear improvement.
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The correlation between performance at age 16 and preceding ages was consistently higher for the female sample. Additionally, the overlap percentage between the 5% best players at age 16 and preceding ages was consistently higher for the female sample as well. Our findings shed a new light on male-female differences in talent development trajectories, and suggest that early talent identification could be more feasible for female players compared to male players.
Files: Scripts for the analyses in study titled: "Developmental performance trajectories of talented tennis players during adolescence: a prospective longitudinal approach". Preprocessing starts in Python scipt ("Rating_analysis_python.py"), then the GMM analysis is performed using the R script("Rating_analysis_R.R"), finally the additional analyses are finished in the Python script("Rating_analysis_python.py").
Links
Where it is published
- Dataverse dataset page dataverse.nl/dataset.xhtml?persistentId=doi%3A10.34894%2FQARLUV ↗
landing page · from datasets iisg amsterdam
- Dataverse dataset page portal.odissei.nl/dataset.xhtml?persistentId=doi%3A10.34894%2FQARLUV ↗
landing page · from portal odissei nl
- DOI doi.org/10.34894/qarluv ↗
DOI / persistent id · from datasets iisg amsterdam
Catalogue records · 2
- Dataverse API dataverse.nl/api/datasets/:persistentId/?persistentId=doi%3A10.34894%2FQARL… ↗
metadata API · from datasets iisg amsterdam
- Dataverse API portal.odissei.nl/api/datasets/:persistentId/?persistentId=doi%3A10.34894%2FQARL… ↗
metadata API · from portal odissei nl
Topics
- Stated by source
- Medicine, Health and Life Sciences · Medicine, Health and Life Sciences · Social Sciences · Social Sciences
- From keywords
- Life Sciences · Life Sciences · Medicine & Health · Medicine & Health · Social Science · Social Science
- Inferred from text
- Curriculum and pedagogy 68% · Longitudinal study 65%
Provenance · 2 source records, 18 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| IISH Dataverse | doi:10.34894/QARLUV | 12 d ago | JSON v1 |
| ODISSEI Portal | doi:10.34894/QARLUV | 8 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:3901 | enrichment · datasets iisg amsterdam | taxonomy-embedding@1.1.0 | title+keywords+description (68%) |
| concepts[field].dataverse_subject:medicine-health-and-life-sciences | source · portal odissei nl | connector:portal_odissei_nl@1.0.0 | /subjects |
| concepts[field].dataverse_subject:medicine-health-and-life-sciences | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /subjects |
| concepts[field].dataverse_subject:social-sciences | source · portal odissei nl | connector:portal_odissei_nl@1.0.0 | /subjects |
| concepts[field].dataverse_subject:social-sciences | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /subjects |
| concepts[field].local:field:life-sciences | mapping · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /subjects |
| concepts[field].local:field:life-sciences | mapping · portal odissei nl | connector:portal_odissei_nl@1.0.0 | /subjects |
| concepts[field].local:field:medicine-health | mapping · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /subjects |
| concepts[field].local:field:medicine-health | mapping · portal odissei nl | connector:portal_odissei_nl@1.0.0 | /subjects |
| concepts[field].local:field:social-science | mapping · portal odissei nl | connector:portal_odissei_nl@1.0.0 | /subjects |
| concepts[field].local:field:social-science | mapping · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /subjects |
| concepts[method].local:method:longitudinal-study | enrichment · datasets iisg amsterdam | keyword-concept-rules@1.0.0 | title+description (65%) |
| created_date | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | |
| description | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /description |
| publication_date | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | |
| title | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /name |
| updated_date | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | |
| version_label | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 |