Utilising competition participation history at youth age to forecast dropout risk and sporting success likelihoods in competitive swimming

This study investigates how competition participation during youth relates to dropout risk in competitive swimming, while also examining whether participation variables can predict key sporting success outcomes such as: (a) effective career length; (b) competitive activity between ages 20 and 26; (c) number of World Championships and Olympic Games appearances; and (d) highest status achieved at those meets (medallist, non-medallist or non-participant). Using data from 2154 swimmers ( F = 1197; M = 957) obtained from the World Aquatics database spanning 1980 to 2019, athletes aged 13 to 32 years were analysed. Dropout was defined as a consecutive four-year period without competition results following debut. A Cox proportional hazards model assessed the influence of debut age, medal success, race volume and engagement in multiple disciplines between ages 13–18 on dropout risk. Median time to dropout was 6 years for men and 5 years for women. Women were 1.47 times as likely as men to drop out. Athletes from Asia were more likely to drop out than athletes from Europe, Oceania and South America. Older debut age, youth medal success, higher total races with lower annual average, and greater discipline diversity were associated with lower dropout risk. For predicting sporting success outcomes, Random Forest and XGBoost machine learning models trained on a standardised set of predictors demonstrated predictive ability above chance, though their performance suggested that incorporating additional variables could enhance accuracy. Overall, findings support encouraging multi-discipline engagement and managing competition load during youth to reduce dropout risk.

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Publication Details

Journal
International Journal of Sports Science & Coaching
Published
2025-09-09
DOI
https://doi.org/10.1177/17479541251372398
Primary Topic
Sports Performance and Training
Type
article
Field-Weighted Citation Impact
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article

Utilising competition participation history at youth age to forecast dropout risk and sporting success likelihoods in competitive swimming

Haresh Suppiah, Matthew James Wylde, Paul B. Gastin, Minh Huynh et al.
International Journal of Sports Science & Coaching
Sports Performance and Training
article

Utilising competition participation history at youth age to forecast dropout risk and sporting success likelihoods in competitive swimming

Haresh Suppiah, Matthew James Wylde, Paul B. Gastin, Minh Huynh, Nur Adilah Masismadi, Esther Chia
article en

Abstract

This study investigates how competition participation during youth relates to dropout risk in competitive swimming, while also examining whether participation variables can predict key sporting success outcomes such as: (a) effective career length; (b) competitive activity between ages 20 and 26; (c) number of World Championships and Olympic Games appearances; and (d) highest status achieved at those meets (medallist, non-medallist or non-participant). Using data from 2154 swimmers ( F = 1197; M = 957) obtained from the World Aquatics database spanning 1980 to 2019, athletes aged 13 to 32 years were analysed. Dropout was defined as a consecutive four-year period without competition results following debut. A Cox proportional hazards model assessed the influence of debut age, medal success, race volume and engagement in multiple disciplines between ages 13–18 on dropout risk. Median time to dropout was 6 years for men and 5 years for women. Women were 1.47 times as likely as men to drop out. Athletes from Asia were more likely to drop out than athletes from Europe, Oceania and South America. Older debut age, youth medal success, higher total races with lower annual average, and greater discipline diversity were associated with lower dropout risk. For predicting sporting success outcomes, Random Forest and XGBoost machine learning models trained on a standardised set of predictors demonstrated predictive ability above chance, though their performance suggested that incorporating additional variables could enhance accuracy. Overall, findings support encouraging multi-discipline engagement and managing competition load during youth to reduce dropout risk.

International Journal of Sports Science & Coaching
La Trobe University (AU), Institute of High Performance Computing (SG), Monash University (AU)
Openalex Percentile: Top 69%
Sports Performance and Training
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