The Multidisciplinary Physical Preparation of a Multiple Paralympic Medal-Winning Cyclist

Autor: Dajo Sanders, David J. Spindler, Jamie Stanley
Přispěvatelé: RS: NUTRIM - R1 - Obesity, diabetes and cardiovascular health, Nutrition and Movement Sciences, Sanders, Dajo, Spindler, David J., Stanley, Jamie
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: International Journal of Sports Physiology and Performance, 17(8), 1316-1322. Human Kinetics Publishers
ISSN: 1555-0265
Popis: Purpose: This case study aims to describe the multidisciplinary preparation of a multiple medal-winning Paralympic cyclist active in the C5 class. Specifically, it describes the 12-month preparation period toward the Tokyo 2020 Paralympic Games. Method: The participant (height 173 cm; weight approximately 63 kg) is active in the C5 para-cycling class (right arm impairment) and was preparing for the individual pursuit, road time trial, and mass-start race in the Tokyo Paralympic Games. The participant was supported by a multidisciplinary practitioner team focusing on multiple facets of athletic preparation. Morning resting heart rate (HR) and HR variability, as well as daily training data, were collected during the 12 months prior to Tokyo. Weekly and monthly trends in training, performance, and morning measures were analyzed. Training intensity zones were divided into zone 1 (lactate threshold, critical power). Results: The participant won a silver (individual pursuit) and a bronze (time trial) medal at the Paralympic Games. Annual sums of volume and total work (in kilojoules) were, respectively, 1039 hours and 620,715 kJ. Analyzing all road sessions, 85% was spent in zone 1, 9% in zone 2, and 6% in zone 3. Physiological (eg, high training loads, hypoxic stimuli) and psychological stressors (ie, significant life events) were clearly reflected in morning HR and HR-variability responses. Conclusions: This case study demonstrates how a multidisciplinary team of specialist practitioners successfully prepared an elite Paralympic cyclist utilizing a holistic approach to training and health using data to manage allostatic load.
Databáze: OpenAIRE