The aim of this study was to compare the mechanical and efficiency constraints between free swim and swimming with differential pressure sensors (Aquanex System). These conditions were also analysed to understand the differences between sexes. Thirty young swimmers, 14 boys and 16 girls (12.31 ± 0.67 years) performed three 25-m front crawl maximal bouts under each condition: free swim and swimming with sensors. Under the condition with sensors, swimmers carried the Aquanex System composed of two hand pressure sensors (v.4.1, Model DU2, Type A, Swimming Technology Research, Richmond, VA, USA). The 25-m time (T25) was assessed as a swimming performance variable. The swimming velocity (v), stroke rate (SR), and stroke length (SL) were assessed and calculated as stroke mechanics variables. Thereafter, the stroke index (SI) and arm stroke efficiency (η F) were estimated for swimming efficiency. Statistical significance was set at p ≤ 0.05. Swimming performance was impaired when swimmers swam with sensors (overall: p = 0.03, d = 0.14; Δ = 1.30%) and a significant decrease in v was found for overall (p = 0.04, d = 0.14; Δ = 1.42%) and the girls’ group (p < 0.01, d = 0.39; Δ = -1.99%). The remaining stroke mechanics variables showed no differences between conditions, as well as for swimming efficiency. Furthermore, there were no differences between girls and boys in free swim and with sensors for all variables. Swimming with the Aquanex System seems not to impose constraints in the mechanics and efficiency of young swimmers, despite differences in swimming performance and v.

The aim of this study was to analyze the reliability of using a differential pressure system to measure in-water force in young competitive swimmers. Ten boys and five girls (12.38 ± 0.48 years, 49.13 ± 6.82 kg, 159.71 ± 7.99 cm) were randomly assigned to perform two maximum bouts of 25 m front crawl on different days (trial one, T1; trial two, T2), one week apart. A differential pressure system composed of two hand sensors (Aquanex System, v.4.1, Model DU2, Type A, Swimming Technology Research, Richmond, VA, United States) was used to measure the peak (RFPEAK) and the mean (RFMEAN) resultant force of the dominant and non-dominant hands (in Newton, N). Reliability was analyzed by computing the intraclass correlation coefficient (ICC), typical error (TE), smallest worthwhile change (SWC), coefficient of variation (CV%), standard error of measurement (SEM), and the minimal detectable change (MDC). Bland–Altman plots with 95% limits of agreement were also analyzed. The results showed no differences between T1 and T2 in all variables (p &gt; 0.05). The ICC showed “excellent” reliability (ICC &gt; 0.90) for the RFPEAK and RFMEAN in both hands. The CV% was rated as “good” (&lt;5%) and TE was smaller than SWC in all variables. The Bland-Altman plots showed high reliability with a small bias (RFPEAK dominant, -0.29 N; RFPEAK non-dominant, -0.83 N; RFMEAN dominant, 0.03 N; RFMEAN non-dominant, 0.50 N). The pressure sensor system (Aquanex System) seems to be a reliable device for measuring the hand resultant force during front crawl in young swimmers and can be used to monitor the changes over time.

The aim of the present study was two-fold: (i) to analyze the progression and variability of swimming performance (from entry times to best performances) in the 50, 100, and 200 m at the most recent FINA World Championships and (ii) to compare the performance of the Top16, semifinalists, and finalists between all rounds. Swimmers who qualified with the FINA A and B standards for the Budapest 2022 World Championships were considered. A total of 1102 individual performances swimmers were analyzed in freestyle, backstroke, breaststroke, and butterfly events. The data was retrieved from the official open-access websites of OMEGA and FINA. Wilcoxon test was used to compare swimmers’ entry times and best performances. Repeated measures ANOVA followed by the Bonferroni post-hoc test were performed to analyze the round-to-round progression. The percentage of improvement and variation in the swimmers’ performance was computed between rounds. A negative progression (entry times better than best performance) and a high variability (> 0.69%) were found for most events. The finalists showed a positive progression with a greater improvement (~1%) from the heats to the semifinals. However, the performance progression remained unchanged between the semifinals and finals. The variability tended to decrease between rounds making each round more homogeneous. Coaches and swimmers can use these indicators to prepare a race strategy between rounds.