Reliability of Load-Velocity Profiling in Front Crawl Swimming
ABSTRACT: The purposes of this study were to establish test-retest reliability of calculating load-velocity profiles in front crawl swimming using five and three different external loads, and if outcome results were comparable between calculation methods for monitoring performance over time. Fifteen swimmers at either national or international competition level (seven females and eight males) participated in this study. The subjects performed 25 m of semi-tethered swimming with maximal effort with five progressive loads (females 1, 2, 3, 4, and 5 kg and males 1, 3, 5, 7, and 9 kg) as well as 50 m maximal front crawl on 2 different days. The mean velocity during three stroke cycles in mid-pool was calculated and plotted as a function of the external load. Relationship between the load and velocity was expressed by a linear regression line and established for each swimmer. The intercepts between the axes of the plot and the established regression line were defined as theoretical maximum velocity (V0) and load (L0). In addition, L0 was also expressed as a percentage of body mass (rL0). The coefficient of determination (R2) and the slope (Slv) of the linear load-velocity relationship were calculated. The intra-class correlation coefficient (ICC) showed excellent agreement (ICC ?0.902) for all variables. The coefficient of variation was ?3.14% and typical error was rated as “good” in all variables. A difference was found between day 1 and 2 in V0 for three- and five-load calculations and for 50 m front crawl time (p < 0.05). No difference was found between the load-velocity profile outcomes variables compared between the three- and five-trial protocols on neither day 1 nor 2. The Bland-Altman plots showed a small bias across all resistance conditions for five loads, L0: 0.04 kg, rL0: 0.13%, V0: ?0.03 m/s, and Slv: 0.003 ?m/s/kg and for three loads, L0: ?0.24 kg, rL0: ?0.27%, V0: ?0.04 m/s, Slv: 0.002 ?m/s/kg. In conclusion, the load-velocity profile for front crawl swimming can be calculated with high reliability from both five and three external loads and comparable results in outcome variables were established. These methods can be used to monitor performance parameters over time, and to investigate and compare swimmers’ velocity and strength capabilities to allow for individualized training prescription to improve performance.
Project description: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 (V<sub>50m</sub>), 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 (V<sub>0</sub>) and load (L<sub>0</sub>). Large to very large correlations were observed between V<sub>50m</sub> and all variables derived from the load-velocity profiling; L<sub>0</sub> (R = 0.632, <i>p</i> = 0.015), L<sub>0</sub> normalized by body mass (R = 0.743, <i>p</i> = 0.002), V<sub>0</sub> (R = 0.698, <i>p</i> = 0.006), and the slope (R = 0.541, <i>p</i> < 0.046). No significant relationships of SL and SL with V<sub>50m</sub> 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.
Project description:Background/objective:Dry land-training (e.g., plyometric jump training) can be a useful mean to improve swimming performance. This study examined the effects of an 8-week plyometric jump training (PJT) program on jump and sport-specific performances in prepubertal female swimmers. Methods:Twenty-two girls were randomly assigned to either a plyometric jump training group (PJTG; n = 12, age: 10.01 ± 0.57 years, maturity-offset = -1.50 ± 0.50, body mass = 36.39 ± 6.32 kg, body height = 146.90 ± 7.62 cm, body mass index = 16.50 ± 1.73 kg/m2) or an active control (CG; n = 10, age: 10.50 ± 0.28 years, maturity-offset = -1.34 ± 0.51, body mass = 38.41 ± 9.42 kg, body height = 143.60 ± 5.05 cm, body mass index = 18.48 ± 3.77 kg/m2). Pre- and post-training, tests were conducted for the assessment of muscle power (e.g., countermovement-jump [CMJ], standing-long-jump [SLJ]). Sport-specific-performances were tested using the timed 25 and 50-m front crawl with a diving-start, timed 25-m front crawl without push-off from the wall (25-m WP), and a timed 25-m kick without push-off from the wall (25-m KWP). Results:Findings showed a significant main effect of time for the CMJ (d = 0.78), the SLJ (d = 0.91), 25-m front crawl test (d = 2.5), and the 25-m-KWP (d = 1.38) test. Significant group × time interactions were found for CMJ, SLJ, 25-m front crawl, 50-m front crawl, 25-m KWP, and 25-m WP test (d = 0.29-1.63) in favor of PJTG (d = 1.34-3.50). No significant pre-post changes were found for CG (p > 0.05). Conclusion:In sum, PJT is effective in improving muscle power and sport-specific performances in prepubertal swimmers. Therefore, PJT should be included from an early start into the regular training program of swimmers.
Project description:Background/objective:This study aimed to examine the effects of eight weeks of dry-land strength combined with swimming training on the development of upper and lower body strength, jumping ability, and swimming performance in competitive sprinter swimmers. Methods:Twenty (14 men and 6 women) university swimmers of national-level (age: 20.55 ± 1.76 years, body mass: 68.86 ± 7.69 kg, height: 1.77 ± 0.06 m, 100 m front crawl: 71.08 ± 6.71s, 50 m front crawl: 31.70 ± 2.45s) were randomly divided into two groups: experimental group (EG: 11) and control group (CG: 9). In addition to the usual in-water training (3-4 sessions per week of ?80 min), the EG performed 8 weeks (one session per week) of strength-training (ST). The ST included bench press, full squat, countermovement jumping, countermovement jumping with free-arm movement, and the medical ball throwing. Stroke length, stroke frequency, stroke index, and swimming velocity were recorded during 50 and 100 m front crawl time-trials. Strength and swimming performance were evaluated before and after 8 weeks of training. Results:The results showed a significant improvement in sprint performance (50 m: p < 0.01, d = 0.47; 100 m: p < 0.05, d = 0.42), stroke frequency (50 m: p < 0.01, d = 0.90) and stroke index (100 m: p < 0.01, d = 0.29) in the EG. Despite both groups' increased strength performance, increases in bench press were higher in the EG (p < 0.001, d = 0.75) than CG (p = 0.05, d = 0.34). Conclusions:Complementing in-water training with strength training seems to be relevant to improve upper body strength and to optimize 50 m and 100 m swimming performance, adapting technical patterns used during all-out swimming.
Project description:This study aimed to identify potential predictors of 200 m front crawl performance at the winter season peak based on the anthropometric, physiological and biomechanical domains. Twelve expert male swimmers completed an incremental 7 × 200 m step test immediately after their most important winter competitions. Measurements were made of: (i) height, body mass and arm span as anthropometrical parameters; (ii) velocity at a 4 mmol·L-1 lactate concentration (V4), maximal oxygen uptake (VO2máx) and energy cost (C), as physiological parameters; (iii) stroke frequency (SF), stroke length (SL), stroke index (SI) and propelling efficiency (?p) as biomechanical indicators; and (iv) 200 m front crawl race time in official long course competitions. Spearman correlation coefficients identified V4 as the single factor having significant relationship with performance. Simple regression analysis determined V4, SI and arm span as the most relevant variables of each group. Multiple linear regression models showed that physiological factors explained better (59%) the variation in performance at this stage of the season, followed by the biomechanical (14%) ones. Therefore, V4 can be one important aspect for training control and diagnosis for those who want to achieve success in the 200 m front crawl at the winter season peak.
Project description:Background:Movement velocity has been proposed as an effective tool to prescribe the load during resistance training in young healthy adults. This study aimed to elucidate whether movement velocity could also be used to estimate the relative load (i.e., % of the one-repetition maximum (1RM)) in older women. Methods:A total of 22 older women (age = 68.2 ± 3.6 years, bench press 1RM = 22.3 ± 4.7 kg, leg press 1RM = 114.6 ± 15.9 kg) performed an incremental loading test during the free-weight bench press and the leg press exercises on two separate sessions. The mean velocity (MV) was collected with a linear position transducer. Results:A strong linear relationship between MV and the relative load was observed for the bench press (%1RM = -130.4 MV + 119.3; r 2 = 0.827, standard error of the estimate (SEE) = 6.10%1RM, p < 0.001) and leg press exercises (%1RM = -158.3 MV + 131.4; r 2 = 0.913, SEE = 5.63%1RM, p < 0.001). No significant differences were observed between the bench press and leg press exercises for the MV attained against light-medium relative loads (?70%1RM), while the MV associated with heavy loads (?80%1RM) was significantly higher for the leg press. Conclusions:These results suggest that the monitoring of MV could be useful to prescribe the loads during resistance training in older women. However, it should be noted that the MV associated with a given %1RM is significantly lower in older women compared to young healthy individuals.
Project description:PURPOSE:To compare the effect of 4-week unknown vs known loads strength training intervention on power output performance and throwing velocity in junior team handball players. METHODS:Twenty-eight junior team-handball players (17.2 ± 0.6 years, 1.79 ± 0.07 m, 75.6 ± 9.4 kg)were divided into two groups (unknown loads: UL; known loads: KL). Both groups performed two sessions weekly consisting of four sets of six repetitions of the bench press throw exercise, using the 30%, 50% and 70% of subjects' individual 1 repetition maximum (1RM). In each set, two repetitions with each load were performed, but the order of the loads was randomised. In the KL group, researchers told the subjects the load to mobilise prior each repetition, while in the UL group, researchers did not provide any information. Maximal dynamic strength (1RM bench press), power output (with 30, 50 and 70% of 1RM) and throwing velocity (7 m standing throw and 9 m jumping throw) were assessed pre- and post-training intervention. RESULTS:Both UL and KL group improved similarly their 1RM bench press as well as mean and peak power with all loads. There were significant improvements in power developed in all the early time intervals measured (150 ms) with the three loads (30, 50, 70% 1RM) in the UL group, while KL only improved with 30% 1RM (all the time intervals) and with 70% 1RM (at certain time intervals). Only the UL group improved throwing velocity in both standing (4.7%) and jumping (5.3%) throw (p > 0.05). CONCLUSIONS:The use of unknown loads has led to greater gains in power output in the early time intervals as well as to increases in throwing velocity compared with known loads. Therefore unknown loads are of significant practical use to increase both strength and in-field performance in a short period of training.
Project description:The purpose of this study was to investigate differences in Froude efficiency (? F ) and active drag (D A ) between front crawl and backstroke at the same speed. ? F was investigated by the three-dimensional (3D) motion analysis using 10 male swimmers. The swimmers performed 50 m swims at four swimming speeds in each technique, and their whole body motion during one upper-limb cycle was quantified by a 3D direct linear transformation algorithm with manually digitized video footage. Stroke length (SL), stroke frequency (SF), the index of coordination (IdC), ? F , and the underwater body volume (UWV body ) were obtained. D A was assessed by the measuring residual thrust method (MRT method) using a different group of swimmers (six males) due to a sufficient experience and familiarization required for the method. A two-way repeated-measures ANOVA (trials and techniques as the factors) and a paired t-test were used for the outcomes from the 3D motion analysis and the MRT method, respectively. Swimmers had 8.3% longer SL, 5.4% lower SF, 14.3% smaller IdC, and 30.8% higher ? F in front crawl than backstroke in the 3D motion analysis (all p < 0.01), which suggest that front crawl is more efficient than backstroke. Backstroke had 25% larger D A at 1.2 m?s-1 than front crawl (p < 0.01) in the MRT trial. A 4% difference in UWV body (p < 0.001) between the two techniques in the 3D motion analysis also indirectly showed that the pressure drag and friction drag were probably larger in backstroke than in front crawl. In conclusion, front crawl is more efficient and has a smaller D A than backstroke at the same swimming speed.
Project description:BACKGROUND:The aim of this study was to compare the validity and reliability of a PUSH band device with a linear encoder to measure movement velocity with different loads during the push-up and bench press exercises. METHODS:Twenty resistance-trained athletes performed push-up and bench press exercises with four different loads: without weight vest, 10-20-30 kg weight vest, bench press: 50-82% of their assumed 1 repetition maximum (1 RM) in steps of 10 kg. A linear encoder (Musclelab) and the PUSH band measured mean and peak velocity during both exercises. Several statistical analyses were used to investigate the validity and reliability of the PUSH band with the linear encoder. RESULTS:The main findings of this study demonstrated only moderate associations between the PUSH band and linear encoder for mean velocity (r = 0.62, 0.70) and peak velocity (r = 0.46, 0.49) for both exercises. Furthermore, a good level of agreement (peak velocity: ICC = 0.60, 0.64; mean velocity: ICC = 0.77, 0.78) was observed between the two measurement devices. However, a significant bias was found with lower velocity values measured with the PUSH band in both exercises. In the push-up, both the linear encoder and PUSH band were deemed very reliable (ICC > 0.98; the coefficient of variation (CV): 5.9-7.3%). Bench press reliability decreased for the PUSH band (ICC < 0.95), and the coefficient of variance increased to (12.8-13.3%) for the velocity measures. Calculated 1 RM with the two devices was the same for the push-up, while in bench press the PUSH band under-estimated the 1 RM by 14 kg compared to the linear encoder. CONCLUSIONS:It was concluded that the PUSH band will show decreased reliability from velocity measures in a bench press exercise and underestimate load-velocity based 1 RM predictions. For training, the PUSH band can be used during push-ups, however caution is suggested when using the device for the purposes of feedback in bench press at increasing loads.
Project description:Although several studies have examined the effects of performing resistance training with different percentages of one-repetition maximum (1-RM), little is known of the neuromuscular effects and kinematics of lifting low to heavy loads with maximal movement velocity. The aim of this study is to compare muscle activation and kinematics in free-weight back squats with different loads. Thirteen resistance-training males (aged 24.2 ± 2.0 years, body mass 81.5 ± 9.1 kg, height 1.78 ± 0.06 m) with 6 ± 3 years of resistance-training experience conducted squats with 30%-100% of 1-RM. Barbell kinematics and electromyographic (EMG) activity of the vastus lateralis, vastus medialis, rectus femoris, semitendinosus, biceps femoris, and gluteus maximus were measured in the upward phase of each load. With increasing loads, the barbell velocity decreased, the upward phase duration increased, and the peak velocity occurred later. The muscle activation in all muscles increased with increasing loads but was not linear. In general, similar muscle activation in the prime movers was observed for loads between 40% and 60% of 1-RM and between 70% and 90% of 1-RM, with 100% of 1-RM being superior to the other loads when the loads were lifted at maximal intended velocity. However, the timing of maximal muscle activations was not affected by the different loadings for the quadriceps, but the timing was sequential and independent of loading (rectus femoris before vastus medial before vastus lateral). Maximal activation in the gluteus and semitendinosus increased with increasing loads. This means that for muscle activation, maximal lifting velocity may compensate for increased loads, which may allow resistance-trained athletes and individuals in rehabilitation to avoid heavy loads but still get the same muscle activation.
Project description:The load-depended loss of vertical barbell velocity at the end of the acceleration phase limits the maximum weight that can be lifted. Thus, the purpose of this study was to analyze how increased barbell loads affect the vertical barbell velocity in the sub-phases of the acceleration phase during the snatch. It was hypothesized that the load-dependent velocity loss at the end of the acceleration phase is primarily associated with a velocity loss during the 1st pull. For this purpose, 14 male elite weightlifters lifted seven load-stages from 70-100% of their personal best in the snatch. The load-velocity relationship was calculated using linear regression analysis to determine the velocity loss at 1st pull, transition, and 2nd pull. A group mean data contrast analysis revealed the highest load-dependent velocity loss for the 1st pull (t = 1.85, p = 0.044, g = 0.49 [-0.05, 1.04]) which confirmed our study hypothesis. In contrast to the group mean data, the individual athlete showed a unique response to increased loads during the acceleration sub-phases of the snatch. With the proposed method, individualized training recommendations on exercise selection and loading schemes can be derived to specifically improve the sub-phases of the snatch acceleration phase. Furthermore, the results highlight the importance of single-subject assessment when working with elite athletes in Olympic weightlifting.