Editorial: Physiological and biomechanical determinants of swimming performance—volume 2

The objective of this Research Topic was to develop and strengthen evidence of training and swimming performance to increase scientific knowledge in the area, considering that understanding the biomechanical, physiological, and neuromuscular determinants of swimming performance is still challenging. This way, 13 manuscripts have been reviewed and approved for this research topic (volume II). We can categorize the 13 manuscripts into three major areas of swimming research: physiology and prescription; biomechanics; performance assessment and prediction. Furthermore, we highlight that 10 of the manuscripts were carried out with the participation of at least two research institutions, often from different countries, which may demonstrate the need for international interchange and exchange of ideas and methodologies across researchers and laboratories.info:eu-repo/semantics/publishedVersio

The influence of the coaches’ demographics on young swimmers’ performance and technical determinants

The purpose of this study was to understand the relationship between the coaches’ demographics (academic degree and/or coaching level and/or coaching experience) and young swimmers’ performance and technical ability. The sample was composed by 151 young swimmers (75 boys and 76 girls: 13.02 1.19 years old, 49.97 8.77 kg of body mass, 1.60 0.08 m of height, 1.66 0.09 m of arm span), from seven different clubs. Seven coaches (one per club) were responsible for the training monitoring. Performance and a set of biomechanical variables related to swim technique and efficiency were assessed. The swimmers’ performance was enhanced according to the increase in the coaches’ academic degree (1: 75.51 10.02 s; 2: 74.55 9.56 s; 3: 73.62 7.64 s), coaching level (1: 76.79 11.27 s; 2: 75.06 9.31 s; 3: 73.65 8.43 s), and training experience ( 5-y training experience: 75.44 9.57 s; >5- y training experience: 74.60 9.54 s). Hierarchical linear modeling retained all coaches’ demographics characteristics as main predictors (being the academic degree the highest: estimate = -1.51, 95% confidence interval = -0.94 to -2.08, p = 0.014). Hence, it seems that an increase in the demographics of the coaches appears to provide them with a training perspective more directed to the efficiency of swimming. This also led to a higher performance enhancementThis work was supported by the National Funds (FCT – Portuguese Foundation for Science and Technology) under the project UIDB/DTP/04045/2020.info:eu-repo/semantics/publishedVersio

Progression of Sprint Interval Training Set Performance and Physiological Responses during a Six-Week Training Period

The aim of this study was to examine the progression and the effect of sprint interval training (SIT) on swimmers’ performance and physiological responses during and after a 6-week period. Eight swimmers (age: 16.7 ± 4.2 years) performed maximum efforts for (a) 200 and 400 m front crawl for the determination of critical speed (CS), (b) four 50 m repetitions (4 × 50 m) and a 100 m test before (Pre) and after (Post) the 6-week training period. SIT was applied three times per week including two sets of 4 × 50 m sprints starting every 2 min. Pre and Post swimming time (T), blood lactate (BL), heart rate (HR), and rate of perceived exertion (RPE) were evaluated. CS increased by 4.4 ± 5.2% (p = 0.01) after 6 weeks. The Pre vs. Post values of T in 4 × 50 and 100 m and BL were unchanged (T: d = 0.05, 0.09, p = 0.14, 0.47, respectively; BL: d = 0.12, p = 0.42), while HR was decreased (d = 0.24, p = 0.04). The progression of T in 4 × 50 m training sprints was unchanged (p = 0.25) while BL increased in weeks 3 (9.4 ± 5.9%) and 5 (13.9 ± 7.8%) compared to week 1 (p = 0.01). SIT improved the swimmers’ aerobic endurance. The lactate response progressively increased despite similar SIT performance during the 6-week period

Dry-Land Force–Velocity, Power–Velocity, and Swimming-Specific Force Relation to Single and Repeated Sprint Swimming Performance

The aim of this study was to identify the relationship between dry-land and in-water strength with performance and kinematic variables in short-distance, middle-distance, and repeated sprint swimming. Fifteen competitive swimmers applied a bench press exercise to measure maximum strength (MS), maximum power (P), strength corresponding to P (F@P), maximum velocity (MV), and velocity corresponding to P (V@P) using F–V and P–V relationships. On a following day, swimmers performed a 10 s tethered swimming sprint (TF), and impulse was measured (IMP). On three separate days, swimmers performed (i) 50 and 100 m, (ii) 200 and 400 m, and (iii) 4 × 50 m front crawl sprint tests. Performance time (T), arm stroke rate (SR), arm stroke length (SL), and arm stroke index (SI) were calculated in all tests. Performance in short- and middle-distance tests and in 4 × 50 m training sets were related to dry-land MS, P, TF, and IMP (r = 0.51–0.83; p p < 0.05). A combination of dry-land P and in-water TF variables explains 80% of the 50 m performance time variation. Bench press power and tethered swimming force correlate with performance in short- and middle-distance tests and repeated sprint swimming

Evaluation of Physical Fitness in Water Polo Players According to Playing Level and Positional Role

Background: We aimed to investigate whether water polo players of different playing levels and positions differ in fitness parameters (i.e., strength, aerobic endurance, and anaerobic potential). Methods: Twenty-four water polo players were assigned to international- (IL) and national-level (NL) groups or to centers and peripherals. At the beginning of preseason training, maximal bench press strength was measured and a speed&#8315;lactate test (5 &#215; 200m) was performed to determine the speed corresponding to lactate concentrations of 4.0 (V4), 5.0 (V5), and 10.0 (V10) mmol&#183;L&#8722;1. Results: Maximal muscular strength was similar between international- and national-level water polo players, but it was higher in centers than in peripherals (109.2 &#177; 12.2 kg vs. 96.9 &#177; 8.5 kg, p = 0.007). IL players showed higher V4, V5, and V10 compared to NL players (V4, IL: 1.27 &#177; 0.04 m&#183;s&#8722;1 vs. NL: 1.17 &#177; 0.06 m&#183;s&#8722;1), (V5, IL: 1.33 &#177; 0.03 m&#183;s&#8722;1 vs. NL: 1.22 &#177; 0.05 m&#183;s&#8722;1), and V10 (IL: 1.50 &#177; 0.31 vs. NL: 1.35 &#177; 0.06 m&#183;s&#8722;1) (p &lt; 0.01)). However, no significant differences were detected between centers and peripherals inV4, V5, and V10. Conclusions: We suggest that V4, V5, and V10 distinguish playing level in water polo, whereas they are comparable between playing positions. Although maximal strength is similar between playing levels, it is different between playing positions