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Data · dataset · 2019

Research materials for: The development of talent in sports: A dynamic network approach

Listed in IISH Dataverse and ODISSEI Portal — shown once because both records carry DOI 10.34894/8rwgdo

Understanding the development of talent has been a major challenge across the arts, education, and particularly sports.

Description

In the article, we show that a dynamic network model predicts typical individual developmental patterns, which for a few athletes result in exceptional achievements. We first validated the model on individual trajectories of famous athletes (Roger Federer, Serena Williams, Sidney Crosby, and Lionel Messi).

Second, we fitted the model on athletic achievements across sports, geographical scale and gender. We show that the model provides good predictions for the distributions of grand slam victories in tennis (male players, n = 1528; female players, n = 1274), major wins in golf (male players, n = 1011; female players, n = 1183), goals scored in the NHL (ice hockey, n = 6677) and in FC Barcelona (soccer, n = 585). The research materials include the basic dynamic network model, the manual of the model, the archival data we used, and the simulated data.

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Stated by source
Social Sciences · Social Sciences
Inferred from text
Curriculum and pedagogy 70%
Provenance · 2 source records, 11 field assertions
SourceKeyLast seenRaw
IISH Dataversedoi:10.34894/8RWGDO10 d agoJSON v1
ODISSEI Portaldoi:10.34894/8RWGDO6 d agoJSON v1
FieldAssertionExtractorEvidence
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concepts[field].dataverse_subject:social-sciencessource · datasets iisg amsterdamconnector:datasets_iisg_amsterdam@1.0.0/subjects
concepts[field].local:field:social-sciencemapping · portal odissei nlconnector:portal_odissei_nl@1.0.0/subjects
concepts[field].local:field:social-sciencemapping · datasets iisg amsterdamconnector:datasets_iisg_amsterdam@1.0.0/subjects
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