Simulación del juego para el análisis tridimensional del aterrizaje del bloqueo en voleibol y sus posibles implicaciones en lesiones de tren inferior. Proyecto SAVIA

  1. Mercado Palomino, Elia
Supervised by:
  1. Aurelio Ureña Espá Director
  2. José Manuel Benítez del Castillo Sánchez Director

Defence university: Universidad de Granada

Fecha de defensa: 30 June 2020

Committee:
  1. Víctor Manuel Soto Hermoso Chair
  2. María Perla Moreno Arroyo Secretary
  3. Enrique Ortega Toro Committee member
  4. María Moreno Catalá Committee member
  5. Isabel María Ribeiro Mesquita Committee member

Type: Thesis

Abstract

The overall aim of the present International Doctoral Thesis is to analyse the landing technique during a volleyball three-step block approach simulating natural game conditions. Therefore, the dominance direction of the block jump-landing, limb role and planned and unplanned situations were studied to determine how limb movement strategies were affected. In this way, possible factors that affect performance can be identified and could be associated with the most common lower limb injuries. Thus, the principal objective is providing information that would enrich the review of technical learning models and physical and preventative training in volleyball block jump-landings. The findings from this International Doctoral Thesis, suggest that planned situations, apart from being away from a real game situation, may generate more musculoskeletal stress than unplanned situations. Moreover, as well as differences between dominant or non-dominant limbs, there are differences depending on the role which the limb performs, with the lead limb having more musculoskeletal stress than the trail limb, perhaps due to an increase in load. Therefore, this could provide relevant information about how to improve the performance of the players and how to plan the training in order to avoid an overload that could lead to risk of injury. Finally, it also raises questions about the learning model and if the variables that have been considered so far in science really are the most relevant and if the use of Machine Learning techniques could change the paradigm in the way of interpreting the risk of injury in sport-specific actions.