Dataset Information

Variation in competition performance, number of races, and age: Long-term athlete development in elite female swimmers.

ABSTRACT: While talent development and the contributing factors to success are hardly discussed among the experts in the field, the aim of the study was to investigate annual variation in competition performance (AVCP), number of races per year, and age, as potential success factors for international swimming competitions. Data from 40'277 long-course races, performed by all individual female starters (n = 253) at the 2018 European Swimming Championships (2018EC) for all 10 years prior to these championships, were analyzed. Relationships between 2018EC ranking and potential success factors, i.e., AVCP, number of races per year, and age, were determined using Pearson's correlation coefficient and multiple linear regression analysis. While AVCP was not related to ranking, higher ranked swimmers at the 2018EC swam more races during each of the ten years prior to the championships (P < 0.001). Additionally, older athletes were more successful (r = -0.42, P < 0.001). The regression model explained highly significant proportions (P < 0.001) and 43%, 34%, 35%, 49% of total variance in the 2018EC ranking for 50m, 100m, 200m, and 400m races, respectively. As number of races per year (? = -0.29 --0.40) had a significant effect on ranking of 50-400m races, and age (? = -0.40 --0.61) showed a significant effect on ranking over all race distances, number of races per year and age may serve as success factors for international swimming competitions. The larger number of races swum by higher ranked female swimmers may have aided long-term athlete development regarding technical, physiological, and mental skill acquisitions. As older athletes were more successful, female swimmers under the age of peak performance, who did not reach semi-finals or finals, may increase their chances of success in following championships with increased experience.

SUBMITTER: Born DP

PROVIDER: S-EPMC7673509 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Variation in competition performance, number of races, and age: Long-term athlete development in elite female swimmers.

Born Dennis-Peter DP Lomax Ishbel I Romann Michael M

PloS one 20201118 11

While talent development and the contributing factors to success are hardly discussed among the experts in the field, the aim of the study was to investigate annual variation in competition performance (AVCP), number of races per year, and age, as potential success factors for international swimming competitions. Data from 40'277 long-course races, performed by all individual female starters (n = 253) at the 2018 European Swimming Championships (2018EC) for all 10 years prior to these championsh ...[more]

PMID: 33206722

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Project description:In this paper, we present the ON score for evaluating the performance of athletes and teams that includes a season-long evaluation system, a single-game evaluation, and an evaluation of an athlete's overall contribution to their team. The approach used to calculate the ON score is based on mixed-effects regression models that take into account the hierarchical structure of the data and a principal component analysis to calculate athlete rating. We apply our methodology to a large dataset of National Basketball Association (NBA) games spanning four seasons from 2015-2016 to 2018-2019. Our model is validated using two systematic approaches, and our results demonstrate the reliability of our approach to calculate an athlete's performance. This provides coaches, General Managers and player agents with a powerful tool to gain deeper insights into their players' performance, make more informed decisions and ultimately improve team performance. Our methodology has several key advantages. First, by incorporating the hierarchical structure of the data, we can obtain valuable information about an athlete's contribution within their team. Second, the use of principal component analysis allows us to calculate a single score, the ON score, that captures the overall performance of an athlete. Third, our approach is based on classical restricted likelihood methods, which makes the calculation faster than Bayesian methods typically requiring 1000 posterior samples. With our approach, coaches and managers can evaluate athletes' performance throughout the season, compare athletes and teams over a year, and assess an athlete's performance during a single game. Our methodology can also complement other ratings and box score metrics to provide a more comprehensive assessment of an athlete's performance as our method uses the hierarchical nature of performance data (i.e. player nested within team over season) which is typically ignored in player rating systems. In summary, our methodology represents a significant contribution to the field of sports analytics and provides the foundation for future developments.

Project description:Background: In elite athletes, training individualization is widely recommended to optimize competitive performance. Previous studies have evidenced the impact of hormonal fluctuations on different performance parameters among female athletes. While consideration of menstrual cycle (MC) phases as a parameter in training individualization strategies is necessary, systematic evidence identifying such impacts in elite athletes should be evaluated. Objective: Systematically review publications that have investigated the link between MC phases and performance in elite female athletes. The overarching aim is to identify whether a consensus across studies exists enabling evidence-based recommendations for training individualization depending on menstrual cycle phases. Methods: This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Three major scientific publication databases were searched from inception until November 3, 2020. Studies included focused on the influence of physiological or psychological parameters throughout at least one phase of the menstrual cycle of elite athletes. Results: A total of 780 search results were yielded and 26 references from a past bibliography were added manually. About 662 papers were reviewed of which 218 studies were assessed for eligibility. Of these, only seven (1%) precisely investigated the influence of a performance or physical parameter during at least one menstrual cycle phase. These seven studies included a total of 314 elite female participants (20.58 ± 1.91 years). Three used interviews, questionnaires or prospective analyses of reports. Four conducted several performance tests or included physical measures although only two performed tests during training or before/during competition. Among the seven studies, five performed hormonal testing through sampling of blood, saliva, or urine. The remaining relied on athletes' menstruation diaries. The current evidence suggests a variable association between menstrual cycle and a few performance-related outcomes, such as endurance or power resistance, ligament stiffness, decision making skills, psychology, or competitiveness. Conclusion: Different sports performance-related parameters are affected during the menstrual cycle among elite athletes, but the parameters themselves and the magnitude and the direction of the effects are inconclusive. Additional longitudinal and prospective studies to systematically monitor on-field performance parameters are urgently required in order to enable recommendations and training individualization in female elite athletes.

Project description:BackgroundThe human ACTN3 gene encodes α-actinin-3, an actin-binding protein with a pivotal role in muscle structure and metabolism. A common genetic single nucleotide polymorphism (SNP) at codon 577 of the ACTN3 results in the replacement of an arginine (R) with a stop codon (X). The R allele is a normal functional version of the gene, whereas the X allele contains a sequence change that completely stops production of functional α-actinin-3 protein. The ACTN3 R577X polymorphism was found to be associated with power athletic performance especially among track and field athletes. The aim of the current study was to compare allelic and genotype frequencies of the ACTN3 R577X polymorphism among runners and swimmers specializing in different distances, and >non-athletic controls.MethodsOne hundred and thirty-seven runners, 91 swimmers and 217 controls, participated in the study. Runners were assigned to two subgroups according to their event specialty-long-distance runners (LDR) and short-distance runners (SDR). Swimmers were also assigned to two subgroups according to their main swimming event-long-distance swimmers (LDS) and short-distance swimmers (SDS). Genomic DNA was extracted from peripheral EDTA-treated anti-coagulated blood using a standard protocol. Genotypes were determined using the Taqman allelic discrimination assay.ResultsRunners' genotype and allele differed significantly between LDR, SDR, and controls, with the lowest prevalence of RR genotype and R allele among LDR. XX genotype and X allele prevalence was significantly higher among LDR compared to the other groups (p < 0.01 for all). On the other hand, swimmers' genotype and allele frequencies did not differ significantly between subgroups (LDS and SDS). Yet, LDS had significantly higher RR genotype and R allele frequencies compared to LDR.ConclusionsThe findings suggest that while ACTN3 R577X polymorphism is a genetic polymorphism that may distinguish between SDR and LDR, it cannot differentiate significantly between SDS and LDS.Trial registrationClinicalTrials.gov: NCT01319032.Key pointsACTN3 R577X polymorphism is largely associated with running events specialization, with high prevalence of RR genotype and R allele frequency among short-distance runners compare to long-distance runners.Unlike in running, ACTN3 R577X polymorphism is not associated with swimming specialization.The inability of the ACTN3 R577X polymorphism to distinguish between swimmers specializing in different events, presumably since other factors such as body physique, technique, tactics, etc., are more likely to determine such a distinction.

Dataset Information

Variation in competition performance, number of races, and age: Long-term athlete development in elite female swimmers.

Publications

Variation in competition performance, number of races, and age: Long-term athlete development in elite female swimmers.

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