Search

Swimming analysts aid coaches and athletes in the decision-making by providing evidence-based recommendations. The aim of this narrative review was to report the best practices of swimming analysts that have been supporting high-performance athletes. It also aims to share how swimming analysts can translate applied research into practice. The role of the swimming analyst, as part of a holistic team supporting high-performance athletes, has been expanding and is needed to be distinguished from the job scope of a swimming researcher. As testing can be time-consuming, analysts must decide what to test and when to conduct the evaluation sessions. Swimming analysts engage in the modelling and forecast of the performance, that in short- and mid-term can help set races target-times, and in the long-term provide insights on talent and career development. Races can be analysed by manual, semi-automatic or fully automatic video analysis with single or multi-cameras set-ups. The qualitative and quantitative analyses of the swim strokes, start, turns, and finish are also part of the analyst job scope and associated with race performance goals. Land-based training is another task that can be assigned to analysts and aims to enhance the performance, prevent musculoskeletal injuries and monitor its risk factors. [ABSTRACT FROM AUTHOR]

Work presented in this paper provides a methodology for categorising swimming start performance based on peak force production on the main block and footrest components of the Omega OSB11 starting block. A total of 46 elite British swimmers were tested, producing over 1000 start trials. Overwater cameras were synchronised to a specifically designed start block that allowed the measurement of force production via two sets of four, tri-axis, force transducers; one set in the main block and one in the footrest. Data were then analysed, segregating trials for gender. Each start was categorised, with respect to the peak force production in horizontal and vertical components, into one of nine categories. Three performance indicators, i.e. block time, take-off velocity and distance of entry, were used to assess whether differences in performance could be correlated with these categories. Results from these data suggest that swimmers generating higher than average peak forces were more likely to produce a better overall start performance than those who produced forces lower than the average, for this population of athletes. [ABSTRACT FROM AUTHOR]