Steffi L. Colyer

Physical Predictors of Elite Skeleton Start Performance.

PURPOSE An extensive battery of physical tests is typically employed to evaluate athletic status and/or development, often resulting in a multitude of output variables. The authors aimed to identify independent physical predictors of elite skeleton start performance to overcome the general problem of practitioners employing multiple tests with little knowledge of their predictive utility. METHODS Multiple 2-d testing sessions were undertaken by 13 high-level skeleton athletes across a 24-wk training season and consisted of flexibility, dry-land push-track, sprint, countermovement-jump, and leg-press tests. To reduce the large number of output variables to independent factors, principal-component analysis (PCA) was conducted. The variable most strongly correlated to each component was entered into a stepwise multiple-regression analysis, and K-fold validation assessed model stability. RESULTS PCA revealed 3 components underlying the physical variables: sprint ability, lower-limb power, and strength-power characteristics. Three variables that represented these components (unresisted 15-m sprint time, 0-kg jump height, and leg-press force at peak power, respectively) significantly contributed (P < .01) to the prediction (R2 = .86, 1.52% standard error of estimate) of start performance (15-m sled velocity). Finally, the K-fold validation revealed the model to be stable (predicted vs actual R2 = .77; 1.97% standard error of estimate). CONCLUSIONS Only 3 physical-test scores were needed to obtain a valid and stable prediction of skeleton start ability. This method of isolating independent physical variables underlying performance could improve the validity and efficiency of athlete monitoring, potentially benefitting sport scientists, coaches, and athletes alike.

Skeleton sled velocity profiles:a novel approach to understand critical aspects of the elite athletes’ start phases

Abstract The development of velocity across the skeleton start is critical to performance, yet poorly understood. We aimed to understand which components of the sled velocity profile determine performance and how physical abilities influence these components. Thirteen well-trained skeleton athletes (>85% of athletes in the country) performed dry-land push-starts alongside countermovement jump and sprint tests at multiple time-points. A magnet encoder attached to the sled wheel provided velocity profiles, which were characterised using novel performance descriptors. Stepwise regression revealed four variables (pre-load velocity, pre-load distance, load effectiveness, velocity drop) to explain 99% variance in performance (β weights: 1.70, –0.81, 0.25, –0.07, respectively). Sprint times and jump ability were associated (r ± 90% CI) with pre-load velocity (–0.70 ± 0.27 and 0.88 ± 0.14, respectively) and distance (–0.48 ± 0.39 and 0.67 ± 0.29, respectively), however, unclear relationships between both physical measures and load effectiveness (0.33 ± 0.44 and –0.35 ± 0.48, respectively) were observed. Athletes should develop accelerative ability to attain higher velocity earlier on the track. Additionally, the loading phase should not be overlooked and may be more influenced by technique than physical factors. Future studies should utilise this novel approach when evaluating skeleton starts or interventions to enhance performance.

Kinetic demands of sprinting shift across the acceleration phase: novel analysis of entire force waveforms

A novel approach of analyzing complete ground reaction force waveforms rather than discrete kinetic variables can provide new insight to sprint biomechanics. This study aimed to understand how these waveforms are associated with better performance across entire sprint accelerations. Twenty‐eight male track and field athletes (100‐m personal best times: 10.88 to 11.96 seconds) volunteered to participate. Ground reaction forces produced across 24 steps were captured during repeated (two to five) maximal‐effort sprints utilizing a 54‐force‐plate system. Force data (antero‐posterior, vertical, resultant, and ratio of forces) across each contact were registered to 100% of stance and averaged for each athlete. Statistical parametric mapping (linear regression) revealed specific phases of stance where force was associated with average horizontal external power produced during that contact. Initially, antero‐posterior force production during mid‐late propulsion (eg, 58%‐92% of stance for the second ground contact) was positively associated with average horizontal external power. As athletes progressed through acceleration, this positive association with performance shifted toward the earlier phases of contact (eg, 55%‐80% of stance for the eighth and 19%‐64% for the 19th ground contact). Consequently, as athletes approached maximum velocity, better athletes were more capable of attenuating the braking forces, especially in the latter parts of the eccentric phase. These unique findings demonstrate a shift in the performance determinants of acceleration from higher concentric propulsion to lower eccentric braking forces as velocity increases. This highlights the broad kinetic requirements of sprinting and the conceivable need for athletes to target improvements in different phases separately with demand‐specific exercises.

A review of the evolution of vision-based motion analysis and the integration of advanced computer vision methods towards developing a markerless system

BackgroundThe study of human movement within sports biomechanics and rehabilitation settings has made considerable progress over recent decades. However, developing a motion analysis system that collects accurate kinematic data in a timely, unobtrusive and externally valid manner remains an open challenge.Main bodyThis narrative review considers the evolution of methods for extracting kinematic information from images, observing how technology has progressed from laborious manual approaches to optoelectronic marker-based systems. The motion analysis systems which are currently most widely used in sports biomechanics and rehabilitation do not allow kinematic data to be collected automatically without the attachment of markers, controlled conditions and/or extensive processing times. These limitations can obstruct the routine use of motion capture in normal training or rehabilitation environments, and there is a clear desire for the development of automatic markerless systems. Such technology is emerging, often driven by the needs of the entertainment industry, and utilising many of the latest trends in computer vision and machine learning. However, the accuracy and practicality of these systems has yet to be fully scrutinised, meaning such markerless systems are not currently in widespread use within biomechanics.ConclusionsThis review aims to introduce the key state-of-the-art in markerless motion capture research from computer vision that is likely to have a future impact in biomechanics, while considering the challenges with accuracy and robustness that are yet to be addressed.

How sprinters accelerate beyond the velocity plateau of soccer players: Waveform analysis of ground reaction forces

Forces applied to the ground during sprinting are vital to performance. This study aimed to understand how specific aspects of ground reaction force waveforms allow some individuals to continue to accelerate beyond the velocity plateau of others. Twenty‐eight male sprint specialists and 24 male soccer players performed maximal‐effort 60‐m sprints. A 54‐force‐plate system captured ground reaction forces, which were used to calculate horizontal velocity profiles. Touchdown velocities of steps were matched (8.00, 8.25, and 8.50 m/s), and the subsequent ground contact forces were analyzed. Mean forces were compared across groups and statistical parametric mapping (t tests) assessed for differences between entire force waveforms. When individuals contacted the ground with matched horizontal velocity, ground contact durations were similar. Despite this, sprinters produced higher average horizontal power (15.7‐17.9 W/kg) than the soccer players (7.9‐11.9 W/kg). Force waveforms did not differ in the initial braking phase (0%‐~20% of stance). However, sprinters attenuated eccentric force more in the late braking phase and produced a higher antero‐posterior component of force across the majority of the propulsive phase, for example, from 31%‐82% and 92%‐100% of stance at 8.5 m/s. At this velocity, resultant forces were also higher (33%‐83% and 86%‐100% of stance) and the force vector was more horizontally orientated (30%‐60% and 95%‐98% of stance) in the sprinters. These findings illustrate the mechanisms which allowed the sprinters to continue accelerating beyond the soccer players’ velocity plateau. Moreover, these force production demands provide new insight regarding athletes’ strength and technique training requirements to improve acceleration at high velocity.

The effect of altering loading distance on skeleton start performance: Is higher pre-load velocity always beneficial?

ABSTRACT Athletes initiating skeleton runs differ in the number of steps taken before loading the sled. We aimed to understand how experimentally modifying loading distance influenced sled velocity and overall start performance. Ten athletes (five elite, five talent; 67% of all national athletes) underwent two to four sessions, consisting of two dry-land push-starts in each of three conditions (preferred, long and short loading distances). A magnet encoder on the sled wheel provided velocity profiles and the overall performance measure (sled acceleration index). Longer pre-load distances (12% average increase from preferred to long distances) were related to higher pre-load velocity (r = 0.94), but lower load effectiveness (r = −0.75; average reduction 29%). Performance evaluations across conditions revealed that elite athletes’ preferred distance push-starts were typically superior to the other conditions. Short loading distances were generally detrimental, whereas pushing the sled further improved some talent-squad athletes’ performance. Thus, an important trade-off between generating high pre-load velocity and loading effectively was revealed, which coaches should consider when encouraging athletes to load later. This novel intervention study conducted within a real-world training setting has demonstrated the scope to enhance push-start performance by altering loading distance, particularly in developing athletes with less extensive training experience.

Influence of serum testosterone on start performance and lean mass accrual in male skeleton athletes

Within athlete variation in circulating testosterone has been associated with changes in strength-power performance across a training season (Crewther and Cook, 2010, Journal of Sports Medicine and Physical Fitness, 50, 371 375). Accordingly, testosterone could conceivably be implicated in long term adaptation by regulating training performance via non-genomic pathways, and not simply through genomic processes (Crewther et al., 2011, Sports Medicine, 41, 103-123). We investigated the association between serum testosterone and both start performance changes and lean mass accrual across a training season in male skeleton athletes. Ethical approval was obtained from a local university ethics committee. Multiple (seven to nine) dry-land push-track testing sessions were undertaken by seven male skeleton athletes across two 24-week training seasons. Fingertip blood samples taken immediately before testing were used to determine serum testosterone concentration at each session. Subsequently, athletes performed three maximal-effort push starts and average start performance (15-m sled velocity) was calculated. Within-athlete relationships between testosterone and start performance were firstly explored using Pearson correlations and 90% confidence intervals (CI). Individual coefficients were then combined via Fisher transformation to obtain a group correlation coefficient. Lean mass was estimated using dual-energy X-ray absorptiometry at the beginning and end of one 24-week training season only. Associations between lean mass accrual and several testosterone variables across this period (baseline testosterone, mean testosterone and mean testosterone relative to baseline) were then assessed using Pearson correlations and 90% CI. Combined within-athlete correlations revealed clear positive relationships between serum testosterone and start performance (r = 0.27, 90% CI = -0.01 to 0.51). Lean mass change across the training season had a negative association with baseline testosterone (r = -0.70, 90% CI = 0.93 to 0.04) and an unclear association with mean testosterone (r = -0.33, 90% CI = 0.84 to 0.40). However, a positive relationship between mean testosterone relative to baseline and lean mass accrual was observed (r = 0.81, 90% CI = 0.30 to 0.96). The results suggest that fluctuations in normal baseline testosterone concentration could influence the expression of start performance. Additionally, maintaining an elevated concentration of testosterone above baseline could potentially be important for lean mass gain, perhaps by regulating training performance across a season. These findings provide some support for the short-term effects of testosterone and the inclusion of hormonal analyses in longitudinal athlete monitoring programmes. Although more work is certainly required, training or warm-up interventions which elevate circulating testosterone could potentially be beneficial to skeleton athletes’ performances.