The influence of sound waves and musical experiences on movement coordination with beats.

Synchronizing movement with external stimuli is important in musicians and athletes. This study investigated the effects of sound characteristics, including sound with harmonics (square wave) and without harmonics (sine wave) and levels of expertise in sports and music on rhythmic ability. Thirty-two university students participated in the study. The participants were divided into sixteen music education (ME) and sixteen physical education (PE) majors. They were asked to perform finger tapping tasks with 1,2 and 3 Hz beat rates, tapping in time with the sine and square wave beat produced by a metronome. The relative phase angle of finger tapping and the onset time of metronome sound were calculated using circular statistics. The results showed that type of wave and music experience affected the rhythmic ability of participants. Our study highlights the importance of types of waves on rhythmic ability, especially for participants with no background in music. The square wave is recommended for athletes to learn to synchronize their movement with beats.

Load-Velocity Profile and Active Drag in Young Female Swimmers: An Age-Group Comparison.

PURPOSE: The present study aimed to establish differences in load-velocity profiling, active drag (AD), and drag coefficient (Cd) between 3 age groups of female swimmers. METHODS: Thirty-three swimmers (11, 13, or 16 y old) were recruited. The individual load-velocity profile was determined for the 4 competitive swimming strokes. The maximal velocity (V0), maximal load (L0), L0 normalized to the body mass, AD, and Cd were compared between the groups. A 2-way analysis of variance and correlation analysis were conducted. RESULTS: Compared with their younger counterparts, 16-year-old swimmers generally had larger V0, L0, and AD, which was particularly evident when comparing them with 11-year-old swimmers (P ≤ .052). The exception was breaststroke, where no differences were observed in L0 and AD and Cd was smaller in the 16-year-old group than the 11-year-old group (P = .03). There was a negative correlation between Cd and V0 for all groups in backstroke (P ≤ .038) and for the 11-year-old group and 13-year-old group in breaststroke (P ≤ .022) and front crawl (P ≤ .010). For the 16-year-old group, large correlations with V0 were observed for L0, L0 normalized to the body mass, and AD (P ≤ .010) in breaststroke and for L0 and AD with V0 in front crawl (P ≤ .042). In butterfly, large negative correlations with V0 were observed in the 13-year-old group for all parameters (P ≤ .027). CONCLUSIONS: Greater propulsive force is likely the factor that differentiates the oldest age group from the younger groups, except for breaststroke, where a lower Cd (implying a better technique) is evident in the oldest group.

Reliability of a semi-tethered front crawl sprint performance test in adolescent swimmers.

This study aimed to evaluate the test-retest reliability of a sprint performance test with semi-tethered front crawl swimming to indirectly assess the current potential to perform at maximal anaerobic effort in adolescent swimmers. Eight adolescent swimmers participated in this study (gender: females (n = 4) aged 13.0 ± 0.8 years, body height 1.6 ± 0.0 m, body mass 50.1 ± 4.5 kg; and males (n = 4) aged 13.3 ± 1.3 years, body height 1.7 ± 0.1 m, body mass 59.0 ± 8.2 kg. The testing protocol consisted of two trials of 25 m semi-tethered front crawl swimming with maximal effort and with 1 kg resisted isotonic load. Velocity data were recorded automatically by the 1080 Sprint device for 15 m (between 3 m and 18 m). The Fast Fourier Transform algorithm filtered raw instantaneous swimming velocity data in distance (time) function. A third-degree polynomial was used to extract the individual velocity profile, from which the following variables were chosen for test-retest reliability and the assessment of sprint performance: ttrial15, vmax, vmin, tvto max, tvat max, Dto vmax, Dat vmax, fatigue index. Parameters such as vmax, vmin, and ttrial15 were estimated from swimming velocity profiles and considered as reliable. The CV showed low variance <5%; while ICC2,1 demonstrated respectively good (ICC2,1: 0.88), very good (ICC2,1: 0.95), and excellent (ICC2,1: 0.98) rate of relative reliability; and the Bland-Altman index revealed an acceptable agreement (LoA ≤5%) between two measurements. The sprint performance test based on semi-tethered front crawl swimming confirmed that ttrial15, vmax, and vmin were reliable variables to indirectly indicate a potential to perform the maximal anaerobic effort among adolescent swimmers. The evaluation of the swimming velocity profiles allows coaches to monitor the adaptive changes of performance during the training process.

Using Statistical Parametric Mapping as a statistical method for more detailed insights in swimming: a systematic review.

Swimming is a time-based sport and hence strongly dependent from velocity. Most studies about swimming refer to velocity as discrete variable, i.e., 0-D (no time dimension). However, it was argued that using swimming velocity as a continuous variable (1-D, with time dimension) with Statistical Parametric Mapping (SPM) can bring deeper and detailed insights about swimming performance. Therefore, the aim of this study was to perform a systematic review about the current body of knowledge of using Statistical Parametric Mapping in a swimming context. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used to identify relevant articles. After screening, nine articles related to Statistical Parametric Mapping (SPM) analysis in swimming were retained for synthesis. Results showed that four articles (44.4%) aimed to understand the kinematics, isokinetic joint torque or electromyographic (EMG) pattern of the swimmer's shoulder either on land or during front crawl trials. Two articles (22.2%) focused on understanding the swimming velocity while performing the breaststroke stroke. One article (11.1%) analyzed the swimmers' propulsion at front-crawl stroke, another one (11.1%) compared swimming velocity during a complete stroke cycle in young swimmers of both sexes as a discrete variable and as a continuous variable. Also, one article (11.1%) analyzed the underwater undulatory velocity. In an EMG context, some findings verified in SPM are not possible to be discovered with traditional 0-D statistical methods. Studies about swimming velocity (breaststroke, freestyle, and underwater undulatory velocity) and propulsion (front-crawl) also highlighted the SPM advantages in comparison to traditional statistical methods. By using SPM, researchers were able to verify specifically where within the stroke cycle significant differences were found. Therefore, coaches can get more detailed information to design specific training drills to overcome hypothetical handicaps.

The gold rush in para swimming: changes in the speed curve of a visually impaired world and paralympic champion - a case study.

This case study examined the association between 50 m freestyle and speed curve parameters of a world-class Paralympic swimmer and analysed the changes in speed curves and their frequency components across her performance levels. From 2018 to 2021, a visually impaired female swimmer (26.59 s in 50 m freestyle, S12 class) underwent 22 tests to obtain instantaneous speed synchronised with video recording. She regularly performed 50 m freestyle in competitions and time trials. The fast Fourier transformation method converted the speed signal into frequency domains and determined the relative contribution of the harmonics with two maxima and minima (H2, arms actions) and six maxima and minima (H6, legs actions). The functional paired t-test compared the speed curves at the beginning (PRE) and end (POST) of the analysed period. The 50 m freestyle time correlated with average speed (r = -0.50, p = 0.02). The contribution of H6 increased in the first year and remained large, whereas the contribution of H2 was lower throughout the whole period. POST was faster than PRE in five moments that coincide with the downward leg kick moments. These changes allowed her to stay longer at the upper part of the curve and improve performance over time.

Is the use of the coefficient of variation a valid way to assess the swimming intra-cycle velocity fluctuation?

OBJECTIVES: Swimming intra-cycle velocity fluctuation has often been assessed using the coefficient of variation, which requires a mathematical assumption of a positive linear relationship between the velocity mean and standard deviation. As this assumption has never been tested, the current study aimed to investigate the within-participant relationship between the mean and standard deviation of the intra-cycle velocity. DESIGN: Cross-sectional study. METHODS: The intra-trial mean and standard deviation of one stroke cycle centre of mass velocity (vCMmean and vCMSD, respectively) were obtained from 80 front crawl trials (10 participants × eight swimming speeds) using whole-body three-dimensional motion analysis. The linear mixed-effect model and intra-class correlation analysis were used to test the linear relationship between vCMmean and vCMSD (n = 80) and the absolute agreement between vCMmean and vCMSD relative to those during the fastest trial (n = 70). RESULTS: Neither the linear regression model (95 % confidence interval range of the fixed effect of vCMmean: -0.003-0.031) nor the intra-class correlation coefficient (ICC = 0.07; p = 0.26) verified linear relationships between vCMmean and vCMSD, which violated the background assumption of coefficient of variation calculation. CONCLUSIONS: When investigating the intra-cycle velocity fluctuation, the coefficient of variation should not be used alone. Researchers and practitioners should always interpret/report the obtained results together with the mean and standard deviation to avoid misleading conclusions and feedback because the coefficient of variation obtained from one cycle velocity data is likely biased by mean velocity.

Differences in seasonal best times between short and long course in freestyle events in Spanish age-group swimmers.

Swimmers perform better times in short course due to the greater numbers of turns; however, the differences between short (SC) and long course (LC) depending on the swimmers' age and sex are unclear. The main aim of this study was to analyse the differences in seasonal best times between SC and LC in freestyle events in relation to age and sex. Seasonal best times performed in SC and LC in each freestyle swimming event of 100 top national Spanish swimmers in two seasons were included in this analysis. A three-way ANOVA was performed to analyse the effect of the three factors on the difference between SC and LC times. Senior swimmers presented the greatest differences between SC and LC in comparison with other age-groups. Age-groups 11-12 and 14-16 showed similar SC and LC differences; nevertheless, these differences are significant (p < 0.05) with the 13-14 age-group. Generally, from 14 to 15 years old the differences between SC and LC increased. The result of this study indicates that the differences between SC and LC are unsteady throughout the swimming career. Thus, when considering swimmers' performance using both SC and LC results, SC results should be adjusted depending on the age of the swimmers.

"Selecting the right tool for the job" a narrative overview of experimental methods used to measure or estimate active and passive drag in competitive swimming.

Free-swimming performance depends strongly on the ability to develop propulsive force and minimise resistive drag. Therefore, estimating resistive drag (passive or active) may be important to understand how free-swimming performance can be improved. The purpose of this narrative overview was to describe and discuss experimental methods of measuring or estimating active and passive drag relevant to competitive swimming. Studies were identified using a mixed-model approach comprising a search of SCOPUS and Web of Science data bases, follow-up of relevant studies cited in manuscripts from the primary search, and additional studies identified by the co-authors based on their specific areas of fluid dynamics expertise. The utility and limitations of active and passive drag methods were critically discussed with reference to primary research domains in this field, 'swimmer morphology' and 'technique analysis'. This overview and the subsequent discussions provide implications for researchers when selecting an appropriate method to measure resistive forces (active or passive) relevant to improving performance in free-swimming.

Intra- and inter-individual variability in the underwater pull-out technique in 200 m breaststroke turns.

The purpose of the present study was to investigate the intra- and inter-individual variability in arm-leg coordination during the underwater phase of the turn segment in 200 m breaststroke. Thirteen male swimmers were recruited and performed a 200 m breaststroke in a pre-calibrated 25 m pool. Sub-phases during the underwater segment were obtained using a notational analysis, and the mean velocity, displacement and duration during each sub-phase were obtained. A hierarchical cluster analysis (HCA) was performed using the analysed variables in all phases to identify inter-individual variability and random intra-individual variability. In addition, a linear mixed model (LMM: lap as a fixed effect and the participant as a random effect) was conducted to investigate systematic intra-individual variability. HCA identified three coordination patterns that were distinguished by the timing of the dolphin kick relative to the arm pull-out and the duration of the glide with arms at the side. All swimmers except one performed the arm pull-out after the dolphin kick. Nine swimmers maintained one coordination pattern, but other swimmers switched their coordination during the trial, particularly by shortening the duration of the glide with arms at the side. LMM showed a linear decrease (from the first to the last turn) in the time gap between the end of the dolphin kick and the start of the arm pull-out (a glide with the streamlined body position; F = 9.64, p = 0.034) and the glide duration with the arms at the side (F = 11.66, p = 0.015). In conclusion, both inter- and intra-individual variabilities during the underwater phase were evident in 200 m breaststroke turns, which were categorised into three patterns based on the timing of the dolphin kick and the duration of glides.

Kinematic and kinetic parameters to identify water polo players' eggbeater kick techniques.

This study aimed to clarify the kinematic and kinetic parameters that identify the technical differences in the eggbeater kick. Twelve water polo players performed the eggbeater kick, and its kinematics were recorded by a motion capture system. Pressure distributions around the feet were measured by sixteen pressure sensors attached to the dorsal and plantar surfaces of the feet, from which the resultant fluid force acting on the feet and the vertical component of the force (i.e., propulsive force) were estimated. Repeated-measures analysis of variance (including post hoc test) results showed that the pressure difference, due to negative pressure on the dorsal side of the foot, around the first toe was significantly larger than the other foot segments (difference of up to 7 kN/m2, P < 0.01). Moreover, cluster analysis (including Fisher information) results showed that the kinetic (fluid force and pressure) data had a major influence on clustering; the highest Fisher information was 10.42 for the mean propulsive force. Among the kinematic foot parameters, the influence of the foot angle data on clustering was large, suggesting its importance as a technical parameter of the eggbeater kick in relation to the kinetic data.

Differences in the rotational effect of buoyancy and trunk kinematics between front crawl and backstroke swimming.

The purpose of the present study was to investigate differences between front crawl and backstroke swimming in hydrodynamic (produced by swimmers) and buoyant torque around the transverse axis. Ten swimmers performed 50 m front crawl and backstroke at four selected velocities (same velocities for both techniques). All trials were recorded by four underwater and two above-water cameras to collect data for three-dimensional whole-body motion during one stroke cycle (defined as a period between two consecutive wrist entries to the water). The inverse dynamics approach was applied to obtain buoyant and hydrodynamic torque around the transverse axis. The differences between front crawl and backstroke techniques across four levels of velocity were assessed with a two-way repeated-measures ANOVA. There was a main effect of technique on the mean buoyant and hydrodynamic torque, with 30-40 % larger leg-raising buoyant torque and leg sinking hydrodynamic torque in front crawl than in backstroke (p ≤ 0.001). The time-series data revealed that the hydrodynamic leg-sinking torque had its peaks during the first half of the underwater upper-limb motion in front crawl, but that was not observed in backstroke, implying that the strategy of counterbalancing the buoyant torque is different between the techniques.

Differences between elite and sub-elite swimmers in a 100 m breaststroke: a new race analysis approach with time-series velocity data.

The purpose of the present study was to investigate differences in a 100 m breaststroke time-trial between elite and sub-elite swimmers. Elite and sub-elite male swimmers (seven each; 772.1 ± 35.2 and 610.6 ± 24.7 FINA point, respectively) performed 100 m breaststroke, which was recorded by a multi-camera system that provided the mean and time-series velocity data in the glide, pull-out, and clean-swimming segments. The mean velocity in each segment was compared between the groups using an independent-samples t-test (for the 1st lap) and two-way mixed-design ANOVA (for the 2nd-4th laps), which suggested a larger mean clean-swimming (in all laps; 7-11% difference) and glide (in the 2nd and 3rd lap; about 13% difference) velocity for the elite swimmers. The time-series data displayed faster velocity in elite swimmers than in the sub-elite group during the first part (up to 40% time) of the glide segment (p < 0.05). Differences in the clean-swimming segment between the groups were observed (p < 0.001) apart from the first 5-15% time of the segment. No differences in the pull-out and at the beginning of the clean-swimming imply that coaches and swimmers should not assume that a good clean-swimming technique also guarantees fast velocity in these segments.

How do swimmers control their front crawl swimming velocity? Current knowledge and gaps from hydrodynamic perspectives.

The aim of this study was to review the literature on front crawl swimming biomechanics, focusing on propulsive and resistive forces at different swimming velocities. Recent studies show that the resistive force increases in proportion to the cube of the velocity, which implies that a proficient technique to miminise the resistive (and maximise the propulsive) force is particularly important in sprinters. To increase the velocity in races, swimmers increase their stroke frequency. However, experimental and simulation studies have revealed that there is a maximum frequency beyond which swimmers cannot further increase swimming velocity due to a change in the angle of attack of the hand that reduces its propulsive force. While the results of experimental and simulation studies are consistent regarding the effect of the arm actions on propulsion, the findings of investigations into the effect of the kicking motion are conflicting. Some studies have indicated a positive effect of kicking on propulsion at high swimming velocities while the others have yielded the opposite result. Therefore, this review contributes to knowledge of how the upper-limb propulsion can be optimised and indicates a need for further investigation to understand how the kicking action can be optimised in front crawl swimming.Abbreviations: C: Energy cost [kJ/m]; E: Metabolic power [W, kJ/s]; Fhand: Fluid resultant force exerted by the hand [N]; Ftotal: Total resultant force [N] (See Appendix A); Fnormal: The sum of the fluid forces acting on body segments toward directions perpendicular to the segmental long axis, which is proportional to the square of the segmental velocity. [N] (See Appendix A); Ftangent: The sum of the fluid forces acting on body segments along the direction parallel to the segmental long axis, which is proportional to the square of the segmental velocity. [N] (See Appendix A); Faddmass: The sum of the inertial force acting on the body segments due to the acceleration of a mass of water [N] (See Appendix A); Fbuoyant: The sum of the buoyant forces acting on the body segments [N] (See Appendix A); D: Fluid resistive force acting on a swimmer's body (active drag) [N]; T: Thrust (propulsive) force acting in the swimming direction in reaction to the swimmer's actions [N]; Thand: Thrust force produced in reaction to the actions of the hand [N]; Tupper_limb: Thrust force produced in reaction to the actions of the upper limbs [N]; Tlower_limb: Thrust force produced in reaction to the actions of the lower limbs [N]; Mbody: Whole-body mass of the swimmer [kg]; SF: Stroke frequency (stroke number per second) [Hz]; SL: Stroke length (distance travelled per stroke) [m]; v: Instantaneous centre of mass velocity of the swimmer [m/s]; V-: Mean of the instantaneous centre of mass velocities in the swimming direction over the period of the stroke cycle [m/s]; a: Centre of mass acceleration of the swimmer [m/s2]; V-hand: Mean of the instantaneous magnitudes of hand velocity over a period of time [m/s]; Wtot: Total mechanical power [W]; Wext: External mechanical power [W]; Wd: Drag power (mechanical power needed to overcome drag) [W, Nm/s]; α: Angle of attack of the palm plane with respect to the velocity vector of the hand [deg]; ηo: Overall efficiency [%]; ηp: Propelling efficiency [%]; MAD-system: Measuring Active Drag system; MRT method: Measuring Residual Thrust method.

Effect of torso morphology on maximum hydrodynamic resistance in front crawl swimming.

The aim of this study was to determine the influence of torso morphology on maximum instantaneous hydrodynamic resistance in front crawl swimming. Outlines of the torso in the frontal and anteroposterior planes were calculated from photographic images to determine continuous form gradients (m/m) for the anterior, posterior and lateral aspects of the torso. Torso cross-sectional areas at each vertical sample (0.001 m) were used to calculate maximal rate of change in cross-sectional area (m2/m) in the chest-waist and waist-hip segments. During the non-propulsive hand phase in middle-long distance front crawl, kicking propulsion is negligible and therefore the net force is equal to the drag. Drag coefficients were calculated at the instant of maximum horizontal deceleration of centre of mass during the non-propulsive hand phase of 400 m pace front crawl. Maximal rate of change in cross-sectional area (r = 0.44, p = 0.014) and posterior form gradient (r = 0.50, p = 0.006) of the waist-hip torso segment had moderate positive correlations with the maximal drag coefficient. A regression model including these variables explained 41% of the variance (p = 0.001). Indentation at the waist and curvature of the buttocks may result in greater drag force and influence swimming performance.

Differences in Race Characteristics between World-Class Individual-Medley and Stroke-Specialist Swimmers.

The purpose of the present study was to investigate differences between world-class individual medley (IM) swimmers and stroke-specialists using race analyses. A total of eighty 200 m races (8 finalists × 2 sexes × 5 events) at the 2021 European long-course swimming championships were analysed. Eight digital video cameras recorded the races, and the video footage was manually analysed to obtain underwater distance, underwater time, and underwater speed, as well as clean-swimming speed, stroke rate, and distance per stroke. Each lap of the IM races was compared with the first, second, third, and fourth laps of butterfly, backstroke, breaststroke, and freestyle races, respectively. Differences between IM swimmers and specialists in each analysed variable were assessed using an independent-sample t-test, and the effects of sex and stroke on the differences were analysed using a two-way analysis of variance with relative values (IM swimmers' score relative to the mean specialists' score) as dependent variables. Breaststroke specialists showed faster clean-swimming speed and longer distance per stroke than IM swimmers for both males (clean-swimming speed: p = 0.011; distance per stroke: p = 0.023) and females (clean-swimming speed: p = 0.003; distance per stroke: p = 0.036). For backstroke and front crawl, specialists exhibited faster underwater speeds than IM swimmers (all p < 0.001). Females showed faster relative speeds during butterfly clean-swimming segments (p < 0.001) and breaststroke underwater segments than males (p = 0.028). IM swimmers should focus especially on breaststroke training, particularly aiming to improve their distance per stroke.

Reliability of the active drag assessment using an isotonic resisted sprint protocol in human swimming.

The purpose of the presents study was to investigate the reliability of the active drag (Da) assessment using the velocity perturbation method (VPM) with different external resisted forces. Eight male and eight female swimmers performed 25 m sprints with five isotonic loads (1-2-3-4-5 kg for females; 1-3-5-7-9 kg for males), which were repeated twice on different days. The mean velocity and semi-tethered force were computed for each condition, and the free-swimming maximum velocity was estimated with load-velocity profiling. From the obtained variables, Da at the maximum free-swimming condition was calculated using VPM. Absolute and typical errors and the intra-class correlation (ICC) were calculated to assess test-retest reliability. 95% confidence interval (95% CI) lower bound of ICC was larger than 0.75 in 3, 4 (females only) and 5 kg trials in both sexes (corresponding to 37-60 N additional resistance; all p < 0.001), which also showed small absolute and relative typical errors (≤ 2.7 N and ≤ 4.4%). In both sexes, 1 kg load trial (16-17 N additional resistance) showed the lowest reliability (95% CI of ICC; - 0.25-0.83 in males and 0.07-0.94 in females). These results suggested that a tethered force of 37-60 N should be used to assess Da using VPM.

Front crawl body roll characteristics in a Paralympic medallist and national level swimmers with unilateral arm amputation.

The purpose of this study was to establish the asymmetry and body wave characteristics related to shoulder, hip, knee, and ankle roll in unilateral arm amputee swimmers. Three unilateral arm amputee swimmers, including one Paralympic medallist (swimmer A), volunteered in this study. They conducted two 10-15 s front crawl tests with sub-maximum and maximum speeds in a flume. Shoulder, hip, knee, and ankle roll amplitude and progression of a torsional body wave was quantified using a motion capture system and a Fourier analysis. Swimmer A showed 50% higher stroke frequency than the other swimmers. Swimmers achieved larger shoulder roll amplitude towards the affected than the unaffected side by 19-89%. Swimmer A showed body wave velocity slowing down when it travelled caudally, while national level swimmers presented increasing wave velocity, suggesting that swimmer A had a less effective kicking than the other swimmers. In conclusion, the technique of the unilateral arm amputee swimmers was characterised by a large shoulder roll angle towards the affected side. The Paralympic medallist had larger shoulder roll asymmetry and less effective kicking than the other swimmers and yet achieved higher swimming speed because of his high stroke frequency.

Arm-leg coordination during the underwater pull-out sequence in the 50, 100 and 200 m breaststroke start.

OBJECTIVES: To investigate the arm-leg coordination from different perspectives of motor control during the underwater start sequence to understand whether differences exist between the three competitive breaststroke swimming events. DESIGN: Cross-sectional study. METHODS: Forty-one breaststroke races (with race times relative to the world record): 50-meter (n = 14, 87.6%), 100-meter (n = 14, 88.5%) and 200-meter (n = 13, 85.4%) were recorded. A race analysis system tracked the two-dimensional displacement of the head. Key points from the underwater start sequence were obtained from notational analysis in order to compute seven time-gaps and four phases to assess the arm-leg coordination and timing of the dolphin kick. A one-way ANOVA with Bonferroni post-hoc correction was used to assess differences between the time gaps and phases for the three events. RESULTS: Differences between the three events were found for total underwater glide, and the first (T0) and second (T1) major glide phase. No differences between the events were found in relative duration and distance for the time gaps related to arm-leg coordination (T1-3, T4, T6) and timing of the dolphin kick (T4-5) during the underwater start sequence. CONCLUSIONS: The arm-leg coordination and timing of the dolphin kick showed no difference between the events, but the total underwater glide duration was longer in both the 100- and 200-meter compared with the 50-meter start. This shows that swimmers did not change the complex inter-limb coordination between the competitive events, but only modified the least complex movement, gliding, to adapt to the swimming speed of the respective events.

Arm - Leg coordination profiling during the dolphin kick and the arm pull-out in elite breaststrokers.

In breaststroke races, the dolphin kick could finish before, at the same time, or during the arm pull-out, but it is unclear how swimmers perform this technique. The aim of this study was to investigate whether swimmers glide between the dolphin kick and arm pull-out, favour continuity or even overlap those two phases, as it would impact the active underwater sequence. Fourteen international and national male swimmers performed 100-m breaststroke with all-out effort in a pre-calibrated 25 m swimming pool. A multi-camera system tracked the head of the swimmers. Key points of the active underwater sequence were obtained from notational analysis. A hierarchical cluster analysis identified three coordination profiles. All swimmers started their dolphin kick before the arm pull-out. However, one swimmer started the arm pull-out before the end of the dolphin kick, seven swimmers started the arm pull-out after the end of the dolphin kick, and four swimmers synchronised the beginning of the arm pull-out and the end of the dolphin kick, while two other swimmers mixed two coordination profiles among the start and the three turns. Those different profiles allow achieving similar performance outcome, suggesting individual training regarding the underwater phase.

The Relationship Between Selected Load-Velocity Profile Parameters and 50 m Front Crawl Swimming Performance.

The purpose of the present study was to establish relationships between sprint front crawl performance and a swimming load-velocity profile. Fourteen male national-level swimmers performed 50 m front crawl and semi-tethered swimming with three progressive loads. The 50 m performance was recorded with a multi-camera system, with which two-dimensional head displacement and the beginning of each arm-stroke motion were quantified. Forward velocity (V50m), stroke length (SL) and frequency (SF) were quantified for each cycle, and the mean value of all cycles, excluding the first and last cycles, was used for the analysis. From the semi-tethered swimming test, the mean velocity during three stroke cycles in mid-pool was calculated and plotted as a function of the external load, and a linear regression line expressing the relationship between the load and velocity was established for each swimmer. The intercepts between the established line and the axes of the plot were defined as theoretical maximum velocity (V0) and load (L0). Large to very large correlations were observed between V50m and all variables derived from the load-velocity profiling; L0 (R = 0.632, p = 0.015), L0 normalized by body mass (R = 0.743, p = 0.002), V0 (R = 0.698, p = 0.006), and the slope (R = 0.541, p < 0.046). No significant relationships of SL and SL with V50m and the load-velocity variables were observed, suggesting that each swimmer has his own strategy to achieve the highest swimming velocity. The findings suggest that load-velocity profiling can be used to assess swimming-specific strength and velocity capabilities related to sprint front crawl performance.