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:IntroductionTo investigate performance variation in all race sections, i.e., start, clean swimming, and turns, of elite short-course races for all swimming strokes and to determine the effect of performance variation on race results.MethodsComparing finalists and non-qualified swimmers, a total of 256 races of male swimmers (n = 128, age: 23.3 ± 3.1, FINA points: 876 ± 38) competing in the European short-course swimming championships were analyzed. The coefficient of variation (CV) and relative change in performance (Δ%) were used to compare intra-individual performance progression between rounds and inter-individual differences between performance levels using a linear mixed model.ResultsWhile most performance variables declined during the races (P < 0.005), performance was better maintained in 200 m compared to 100 m races, as well as in finalists compared to non-qualified swimmers. In 100 m races, Start Times improved between heats, semi-finals, and finals (P < 0.005) and contributed to the improved Split Times of Lap 1 in freestyle (P = 0.001, Δ = -1.09%), breaststroke (P < 0.001; Δ = -2.48%), and backstroke (P < 0.001; Δ = -1.72%). Swimmers increased stroke rate from heats/semi-finals to finals in freestyle (P = 0.015, Δ = 3.29%), breaststroke (P = 0.001, Δ = 6.91%), and backstroke (P = 0.005; Δ = 3.65%). Increases in stroke length and clean-swimming speed were only significant between rounds for breaststroke and backstroke (P < 0.005). In 200 m races, Total Time remained unchanged between rounds (P > 0.05), except for breaststroke (P = 0.008; CV = 0.7%; Δ = -0.59%). Start (P = 0.004; Δ = -1.72%) and Split Times (P = 0.009; Δ = -0.61%) only improved in butterfly. From the turn variables, OUT_5 m times improved towards the finals in breaststroke (P = 0.006; Δ = -1.51%) and butterfly (P = 0.016; Δ = -2.19%). No differences were observed for SR and SL, while clean-swimming speed improved between rounds in breaststroke only (P = 0.034; Δ = 0.96%).DiscussionPerformance of finalists progressed between rounds in 100 m but not 200 m races, most probably due to the absence of semi-finals. Progression in 100 m races was mainly attributed to improved Start and Split Times in Lap 1, while turn performances remained unchanged. Within round comparison showed higher performance maintenance in 200 m compared to 100 m events, which showed more pronounced positive pacing. Success of finalists was attributed to their overall higher performance level and superior progression between rounds.

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.

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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