Search Results

You are looking at 11 - 13 of 13 items for

  • Author: Marco Cardinale x
  • Refine by Access: All Content x
Clear All Modify Search
Restricted access

Steffi L. Colyer, Keith A. Stokes, James L.J. Bilzon, Marco Cardinale, and Aki I.T. Salo

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 (R 2 = .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 R 2 = .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.

Restricted access

Andrew M. Murray, Joong Hyun Ryu, John Sproule, Anthony P. Turner, Phil Graham-Smith, and Marco Cardinale

Purpose:

Running performance is influenced by the interaction of biomechanical and physiological factors. Miniaturized accelerometers worn by athletes can be used to quantify mechanical aspects of running and as a noninvasive tool to assess training status and progression. The aim of this study was to define and validate a method to assess running regularity and allow the estimation of an individual’s oxygen uptake (V̇O2) and/or blood lactate—[La]b—based on data collected with accelerometers and heart rate.

Methods:

Male adolescent endurance athletes completed an incremental submaximal aerobic stage test where V̇O2 and [La]b were measured. The test was terminated when [La]b concentration at the end of the stage exceeded 4 mmol/L. Two wireless triaxial accelerometers were placed on participants’ right shank and lower back throughout the test. The root mean square (RMS) and sample entropy (SampEn) were calculated for the vertical, mediolateral, and anteroposterior components of acceleration.

Results:

There were significant positive correlations of acceleration and entropy variables with [La]b and V̇O2, with moderate to high coefficients (r = .43–.87). RMS of the shank acceleration was the most highly related with both physiological variables. When the accelerometer was attached on the trunk, SampEn of the vertical acceleration had the strongest relationship with V̇O2 (r = .76, P < .01).

Conclusions:

The described method analyzing running complexity may allow an assessment of gait variability, which noninvasively tracks V̇O2 and/or [La]b, allowing monitoring of fatigue or training readiness for trained adolescent individuals.

Open access

Pitre C. Bourdon, Marco Cardinale, Andrew Murray, Paul Gastin, Michael Kellmann, Matthew C. Varley, Tim J. Gabbett, Aaron J. Coutts, Darren J. Burgess, Warren Gregson, and N. Timothy Cable

Monitoring the load placed on athletes in both training and competition has become a very hot topic in sport science. Both scientists and coaches routinely monitor training loads using multidisciplinary approaches, and the pursuit of the best methodologies to capture and interpret data has produced an exponential increase in empirical and applied research. Indeed, the field has developed with such speed in recent years that it has given rise to industries aimed at developing new and novel paradigms to allow us to precisely quantify the internal and external loads placed on athletes and to help protect them from injury and ill health. In February 2016, a conference on “Monitoring Athlete Training Loads—The Hows and the Whys” was convened in Doha, Qatar, which brought together experts from around the world to share their applied research and contemporary practices in this rapidly growing field and also to investigate where it may branch to in the future. This consensus statement brings together the key findings and recommendations from this conference in a shared conceptual framework for use by coaches, sport-science and -medicine staff, and other related professionals who have an interest in monitoring athlete training loads and serves to provide an outline on what athlete-load monitoring is and how it is being applied in research and practice, why load monitoring is important and what the underlying rationale and prospective goals of monitoring are, and where athlete-load monitoring is heading in the future.