Tania Spiteri, Nicolas H. Hart and Sophia Nimphius
The aim of this study was to compare biomechanical and perceptual-cognitive variables between sexes during an offensive and defensive agility protocol. Twelve male and female (n = 24) recreational team sport athletes participated in this study, each performing 12 offensive and defensive agility trials (6 left, 6 right) changing direction in response to movements of a human stimulus. Three-dimensional motion, ground reaction force (GRF), and impulse data were recorded across plant phase for dominant leg change of direction (COD) movements, while timing gates and high-speed video captured decision time, total running time, and post COD stride velocity. Subjects also performed a unilateral isometric squat to determine lower body strength and limb dominance. Group (sex) by condition (2 × 2) MANOVAs with follow-up ANOVAs were conducted to examine differences between groups (P ≤ .05). Male athletes demonstrated significantly greater lower body strength, vertical braking force and impulse application, knee and spine flexion, and hip abduction, as well as faster decision time and post COD stride velocity during both agility conditions compared with females. Differences between offensive and defensive movements appear to be attributed to differences in decision time between sexes. This study demonstrates that biomechanical and perceptual-cognitive differences exist between sexes and within offensive and defensive agility movements.
Timo Rantalainen, Nicolas H. Hart, Sophia Nimphius and Daniel W. Wundersitz
Inertial measurement units (IMU) provide a convenient tool for gait stability assessment. However, it is unclear how various gait characteristics relate to each other and whether gait characteristics can be obtained from resultant acceleration. Therefore, step duration variability was measured in treadmill walking from 39 young ambulant volunteers (age 24.2 [± 2.5] y; height 1.79 [± 0.09] m; mass 71.6 [± 12.0] kg) using motion capture. Accelerations and gyrations were simultaneously recorded with an IMU. Harmonic ratio, maximum Lyapunov exponents, and multiscale sample entropy (MSE) were calculated. Step duration variability was positively associated with MSE with coarseness levels = 3–6 (r = –.33 to –.42, P ≤ .045). Harmonic ratio and MSE with all coarseness levels were negatively associated (r = –.45 to –.57, P ≤ .004). The MSE with coarseness level = 2 was negatively associated with short-term maximum Lyapunov exponents (r = –.32, P = .047). The agreement between resultant and vertical acceleration derived gait characteristics was excellent (ICC = 0.97–0.99). In conclusion, MSE with varying coarseness levels was associated with the other gait characteristics evaluated in the study. Resultant and vertical acceleration derived results had excellent agreement, which suggests that resultant acceleration is a viable alternative to considering the acceleration dimensions independently.
Joseph O.C. Coyne, Sophia Nimphius, Robert U. Newton and G. Gregory Haff
Purpose: Criticisms of the acute to chronic workload ratio (ACWR) have been that the mathematical coupling inherent in the traditional calculation of the ACWR results in a spurious correlation. The purposes of this commentary are (1) to examine how mathematical coupling causes spurious correlations and (2) to use a case study from actual monitoring data to determine how mathematical coupling affects the ACWR. Methods: Training and competition workload (TL) data were obtained from international-level open-skill (basketball) and closed-skill (weightlifting) athletes before their respective qualifying tournaments for the 2016 Olympic Games. Correlations between acute TL, chronic TL, and the ACWR as coupled/uncoupled variations were examined. These variables were also compared using both rolling averages and exponentially weighted moving averages to account for any potential benefits of one calculation method over another. Results: Although there were some significant differences between coupled and uncoupled chronic TL and ACWR data, the effect sizes of these differences were almost all trivial (g = 0.04–0.21). Correlations ranged from r = .55 to .76, .17 to .53, and .88 to .99 for acute to chronic TL, acute to uncoupled chronic TL, and ACWR to uncoupled ACWR, respectively. Conclusions: There may be low risk of mathematical coupling causing spurious correlations in the TL–injury-risk relationship. Varying levels of correlation seem to exist naturally between acute and chronic TL variables regardless of coupling. The trivial to small effect sizes and large to nearly perfect correlations between coupled and uncoupled AWCRs also imply that mathematical coupling may have little effect on either calculation method, if practitioners choose to apply the ACWR for TL monitoring purposes.
Jeremy M. Sheppard, Sophia Nimphius, Greg G. Haff, Tai T. Tran, Tania Spiteri, Hedda Brooks, Gary Slater and Robert U. Newton
Appropriate and valid testing protocols for evaluating the physical performances of surfing athletes are not well refined. The purpose of this project was to develop, refine, and evaluate a testing protocol for use with elite surfers, including measures of anthropometry, strength and power, and endurance.
After pilot testing and consultation with athletes, coaches, and sport scientists, a specific suite of tests was developed. Forty-four competitive junior surfers (16.2 ± 1.3 y, 166.3 ± 7.3 cm, 57.9 ± 8.5 kg) participated in this study involving a within-day repeated-measures analysis, using an elite junior group of 22 international competitors (EJG), to establish reliability of the measures. To reflect validity of the testing measures, a comparison of performance results was then undertaken between the EJG and an age-matched competitive junior group of 22 nationally competitive surfers (CJG).
Percent typical error of measurement (%TEM) for primary variables gained from the assessments ranged from 1.1% to 3.0%, with intraclass correlation coefficients ranging from .96 to .99. One-way analysis of variance revealed that the EJG had lower skinfolds (P = .005, d = 0.9) than the CJG, despite no difference in stature (P = .102) or body mass (P = .827). The EJG were faster in 15-m sprint-paddle velocity (P < .001, d = 1.3) and had higher lower-body isometric peak force (P = .04, d = 0.7) and superior endurance-paddling velocity (P = .008, d = 0.9).
The relatively low %TEM of these tests in this population allows for high sensitivity to detect change. The results of this study suggest that competitively superior junior surfers are leaner and possess superior strength, paddling power, and paddling endurance.
Josh L. Secomb, Sophia Nimphius, Oliver R.L. Farley, Lina Lundgren, Tai T. Tran and Jeremy M. Sheppard
To identify whether there are any significant differences in the lower-body muscle structure and countermovement-jump (CMJ) and squat-jump (SJ) performance between stronger and weaker surfing athletes.
Twenty elite male surfers had their lower-body muscle structure assessed with ultrasonography and completed a series of lower-body strength and jump tests including isometric midthigh pull (IMTP), CMJ, and SJ. Athletes were separated into stronger (n = 10) and weaker (n = 10) groups based on IMTP performance.
Large significant differences were identified between the groups for vastus lateralis (VL) thickness (P = .02, ES = 1.22) and lateral gastrocnemius (LG) pennation angle (P = .01, ES = 1.20), and a large nonsignificant difference was identified in LG thickness (P = .08, ES = 0.89). Furthermore, significant differences were present between the groups for peak force, relative peak force, and jump height in the CMJ and SJ (P < .01−.05, ES = 0.90−1.47) and eccentric peak velocity, as well as vertical displacement of the center of mass during the CMJ (P < .01, ES = 1.40−1.41).
Stronger surfing athletes in this study had greater VL and LG thickness and LG pennation angle. These muscle structures may explain their better performance in the CMJ and SJ. A unique finding in this study was that the stronger group appeared to better use their strength and muscle structure for braking as they had significantly higher eccentric peak velocity and vertical displacement during the CMJ. This enhanced eccentric phase may have resulted in a greater production and subsequent utilization of stored elastic strain energy that led to the significantly better CMJ performance in the stronger group.
James J. Tufano, Jenny A. Conlon, Sophia Nimphius, Lee E. Brown, Laurent B. Seitz, Bryce D. Williamson and G. Gregory Haff
To compare the effects of a traditional set structure and 2 cluster set structures on force, velocity, and power during back squats in strength-trained men.
Twelve men (25.8 ± 5.1 y, 1.74 ± 0.07 m, 79.3 ± 8.2 kg) performed 3 sets of 12 repetitions at 60% of 1-repetition maximum using 3 different set structures: traditional sets (TS), cluster sets of 4 (CS4), and cluster sets of 2 (CS2).
When averaged across all repetitions, peak velocity (PV), mean velocity (MV), peak power (PP), and mean power (MP) were greater in CS2 and CS4 than in TS (P < .01), with CS2 also resulting in greater values than CS4 (P < .02). When examining individual sets within each set structure, PV, MV, PP, and MP decreased during the course of TS (effect sizes 0.28–0.99), whereas no decreases were noted during CS2 (effect sizes 0.00–0.13) or CS4 (effect sizes 0.00–0.29).
These results demonstrate that CS structures maintain velocity and power, whereas TS structures do not. Furthermore, increasing the frequency of intraset rest intervals in CS structures maximizes this effect and should be used if maximal velocity is to be maintained during training.
Tai T. Tran, Lina Lundgren, Josh Secomb, Oliver R.L. Farley, G. Gregory Haff, Robert U. Newton, Sophia Nimphius and Jeremy M. Sheppard
The purpose of this study was to develop and evaluate a drop-and-stick (DS) test method and to assess dynamic postural control in senior elite (SE), junior elite (JE), and junior development (JD) surfers. Nine SE, 22 JE, and 17 JD competitive surfers participated in a single testing session. The athletes completed 5 drop-and-stick trials barefoot from a predetermined box height (0.5 m). The lowest and highest time-to-stabilization (TTS) trials were discarded, and the average of the remaining trials was used for analysis. The SE group demonstrated excellent single-measures repeatability (ICC = .90) for TTS, whereas the JE and JD demonstrated good single-measures repeatability (ICC .82 and .88, respectively). In regard to relative peak landing force (rPLF), SE demonstrated poor single-measures reliability compared with JE and JD groups. Furthermore, TTS for the SE (0.69 ± 0.13 s) group was significantly (P = .04) lower than the JD (0.85 ± 0.25 s). There were no significant (P = .41) differences in the TTS between SE (0.69 ± 0.13 s) and JE (0.75 ± 0.16 s) groups or between the JE and JD groups (P = .09). rPLF for the SE (2.7 ± 0.4 body mass; BM) group was significantly lower than the JE (3.8 ± 1.3 BM) and JD (4.0 ± 1.1 BM), with no significant (P = .63) difference between the JE and JD groups. A possible benchmark approach for practitioners would be to use TTS and rPLF as a qualitative measure of dynamic postural control using a reference scale to discriminate among groups.
Tai T. Tran, Lina Lundgren, Josh Secomb, Oliver R.L. Farley, G. Gregory Haff, Laurent B. Seitz, Robert U. Newton, Sophia Nimphius and Jeremy M. Sheppard
To determine whether a previously validated performance-testing protocol for competitive surfers is able to differentiate between Australian elite junior surfers selected (S) to the national team and those not selected (NS).
Thirty-two elite male competitive junior surfers were divided into 2 groups (S = 16, NS = 16). Their age, height, body mass, sum of 7 skinfolds, and lean-body-mass ratio (mean ± SD) were 16.17 ± 1.26 y, 173.40 ± 5.30 cm, 62.35 ± 7.40 kg, 41.74 ± 10.82 mm, 1.54 ± 0.35 for the S athletes and 16.13 ± 1.02 y, 170.56 ± 6.6 cm, 61.46 ± 10.10 kg, 49.25 ± 13.04 mm, 1.31 ± 0.30 for the NS athletes. Power (countermovement jump [CMJ]), strength (isometric midthigh pull), 15-m sprint paddling, and 400-m endurance paddling were measured.
There were significant (P ≤ .05) differences between the S and NS athletes for relative vertical-jump peak force (P = .01, d = 0.9); CMJ height (P = .01, d = 0.9); time to 5-, 10-, and 15-m sprint paddle; sprint paddle peak velocity (P = .03, d = 0.8; PV); time to 400 m (P = .04, d = 0.7); and endurance paddling velocity (P = .05, d = 0.7).
All performance variables, particularly CMJ height; time to 5-, 10-, and 15-m sprint paddle; sprint paddle PV; time to 400 m; and endurance paddling velocity, can effectively discriminate between S and NS competitive surfers, and this may be important for athlete profiling and training-program design.
Lina E. Lundgren, Tai T. Tran, Sophia Nimphius, Ellen Raymond, Josh L. Secomb, Oliver R.L. Farley, Robert U. Newton, Julie R. Steele and Jeremy M. Sheppard
To develop and evaluate a multifactorial model based on landing performance to estimate injury risk for surfing athletes.
Five measures were collected from 78 competitive surfing athletes and used to create a model to serve as a screening tool for landing tasks and potential injury risk. In the second part of the study, the model was evaluated using junior surfing athletes (n = 32) with a longitudinal follow-up of their injuries over 26 wk. Two models were compared based on the collected data, and magnitude-based inferences were applied to determine the likelihood of differences between injured and noninjured groups.
The study resulted in a model based on 5 measures—ankle-dorsiflexion range of motion, isometric midthigh-pull lower-body strength, time to stabilization during a drop-and-stick (DS) landing, relative peak force during a DS landing, and frontal-plane DS-landing video analysis—for male and female professional surfers and male and female junior surfers. Evaluation of the model showed that a scaled probability score was more likely to detect injuries in junior surfing athletes and reported a correlation of r = .66, P = .001, with a model of equal variable importance. The injured (n = 7) surfers had a lower probability score (0.18 ± 0.16) than the noninjured group (n = 25, 0.36 ± 0.15), with 98% likelihood, Cohen d = 1.04.
The proposed model seems sensitive and easy to implement and interpret. Further research is recommended to show full validity for potential adaptations for other sports.