Career patterns within men’s and women’s soccer talent systems: the typical pathway to the top is atypical

DOI

Data for the published paper "Career patterns within men’s and women’s soccer talent systems: the typical pathway to the top is atypical". This study aimed to examine whether early recruitment correlates with senior performance levels and, as a next step, to quantitatively explore the shape of nearly 3,000 Dutch male and female youth soccer players’ career patterns.Talent systems in soccer aim to identify and recruit the most promising players, ideally during early childhood. Compared to non-recruited players, recruited players are typically provided with higher-quality coaching and training facilities, which are assumed to accelerate their skill development. As a result, future elite players are expected to emerge from this group of early recruits in a singular, uninterrupted progression. The career patterns are stored in two data sets (natteam.csv; academy.csv). The Rmarkdown file runs all of the code to generate the results and the four figures in the accompanying paper. In addition, it generates 3 tables in that are stored in the supplementary file.

The files in this datapackage construct the analysis from the two data sets (natteam.csv; academy.csv). The data-analysis file runs all of the code to generate the results and the 4 figures in the accompanying paper. In addition, it generates 3 tables in the supplementary file.

Identifier
DOI https://doi.org/10.34894/CG4XEQ
Metadata Access https://dataverse.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.34894/CG4XEQ
Provenance
Creator Verbeek, Jan ORCID logo; Niessen, Susan M. ORCID logo; van Der Steen, Steffie ORCID logo; Van Yperen, Nico W. ORCID logo; Den Hartigh. Ruud ORCID logo
Publisher DataverseNL
Contributor Groningen Digital Competence Centre; Faculty of Behavioural Sciences, Psychology; DataverseNL Network
Publication Year 2025
Rights info:eu-repo/semantics/restrictedAccess
OpenAccess false
Contact Groningen Digital Competence Centre (University of Groningen)
Representation
Resource Type Dataset
Format text/csv; text/x-r-notebook; text/markdown
Size 775707; 23379; 70457; 3820
Version 1.0
Discipline Agriculture, Forestry, Horticulture, Aquaculture; Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine; Life Sciences; Medicine; Social Sciences; Social and Behavioural Sciences; Soil Sciences