RESUMO
BACKGROUND: Recently a proof-of-concept was proposed to derive the soccer players' individual in-situ acceleration-speed (AS) profile from global positioning system (GPS) data collected over several sessions and games. The present study aimed to propose an automatized method of individual GPS-derived in-situ AS profiling in a professional rugby union setting. METHOD: AS profiles of forty-nine male professional rugby union players representing 61.5 million positions, from which acceleration was derived from speed during 51 training sessions and 11 official games, were analyzed. A density-based clustering algorithm was applied to identify outlier points. Multiple AS linear relationships were modeled for each player and session, generating numerous theoretical maximal acceleration (A0), theoretical maximal running speed (S0) and AS slope (ASslope, i.e., overall orientation of the AS profile). Each average provides information on the most relevant value while the standard deviation denotes the method accuracy. In order to assess the reliability of the AS profile within the data collection period, data were compared over two 2-week phases by the inter-class correlation coefficient. A0 and S0 between positions and type of sessions (trainings and games) were compared using ANOVA and post hoc tests when the significant threshold had been reached. RESULTS: All AS individual profiles show linear trends with high coefficient of determination (r2 > 0.81). Good reliability (Inter-class Correlation Coefficient ranging from 0.92 to 0.72) was observed between AS profiles, when determined 2 weeks apart for each player. AS profiles depend on players' positions, types of training and games. Training and games data highlight that highest A0 are obtained during games, while greatest S0 are attained during speed sessions. CONCLUSIONS: This study provides individual in-situ GPS-derived AS profiles with automatization capability. The method calculates an error of measurement for A0 and S0, of paramount importance in order to improve their daily use. The AS profile differences between training, games and playing positions open several perspectives for performance testing, training monitoring, injury prevention and return-to-sport sequences in professional rugby union, with possible transferability to other sprint-based sports. KEY POINTS: AS profiles computed from rugby union GPS data provide positional benchmarks during training and competition. This study provides automatic detection of atypical data and the computation of error measurement of theoretical maximal acceleration and speed components. This refinement constitutes a step forward for a daily use of ecological data by considering data collection and method reliabilities. This easy-to-implement approach may facilitate its use to the performance management process (talent identification, training monitoring and individualization, return-to-sport).
RESUMO
PURPOSE: To measure the proportion of French swimmers that progressed, stagnated, or regressed during the 2020 national championship compared with previous ones. METHOD: Individual best performances were collected at the French national championships from 2000 to 2020. Yearly proportions of swimmers who improved, stagnated, or regressed in performances were compared with their previous performances. RESULTS: In 2020, the proportion of swimmers with performance regression has significantly increased (33% vs 17% in 2019). Women showed a higher proportion of performance regression (41%) than men (26%, P < .0001) in 2020. Only 39% of women and 53% of men experienced progression in 2020 (vs 60.8% [3.7%] and 66.7% [5.2%], respectively, in the previous years). Only the 2008 and 2009 championships showed a regression proportion that did not increase with age. The 2010 championship (the year of swimsuits ban) showed a higher proportion of regressing athletes than these previous years. Long-distance events showed higher proportion of performance regression (36.2% [0.5%]) for 400-, 800-, and 1500-m races than for short-distance ones (32.1% [3.2%]; 50-, 100-, and 200-m events). Breaststroke events showed higher regression (42.4%) than other styles (30.5% [2.1%]). Younger swimmers more often improved their performance than older ones (61.9% [8.5%] for swimmers less than 18 y of age vs 20.0% [10.8%] for those 25 y and older). CONCLUSION: A high proportion of swimmers experienced performance regression during the 2020 French national championships. A higher impact was observed among female, long-distance, and breaststroke swimmers. Eight weeks of lockdown without training may have led to poorer swimming performances.
