Testing and training of the eggbeater kick movement in water polo: applicability of a new method

Giovanni Melchiorri, Valerio Viero, Tamara Triossi, Virginia Tancredi, Christel Galvani, Marco Bonifazi

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

In water polo many of the technical actions and the contacts with the opponent take place in quasi-vertical floating position, using two types of lower limb actions: the eggbeater kick is used most often in fighting and passing and the breaststroke kick in jumping and throwing. The aim of this study was to identify a new system to evaluate and to train the eggbeater kick movement and to verify its applicability. Twenty amateur players and twenty-two elite players participated in the study. A jacket, homemade and easy to make, allowing the application of an overload submerged in water but not hindering breathing or mobility, was used. Standard anthropometry and a test consisting of different trials of the eggbeater kick action until exhaustion with an increasing overload (5, 7.5, 10, 12.5, 15 and 17.5 kg) were collected. Time to exhaustion and the overload estimated maximum value (OEMV) at second two were determined for each load. Body weight, height and lower limb muscle performance of the elite and non-elite players were significantly different from each other (p < 0.05). The effectiveness of the different measured variables in both sub-groups and that of the OEMV was evaluated with ROC curve analysis. Areas under the ROC curve for the different overloads were 0.72 (0.53-0.92) for 5 kg; 0.80 (0.68-0.90) for 7.5 kg; 0.87 (0.77-0.91) for 10 kg and 0.88 (0.84-0.92) for 12.5 kg overload. Our results show that the test is sensitive enough and therefore can be used to plan and control training and injury recovery.
Original languageEnglish
Pages (from-to)2758-2764
Number of pages7
JournalJournal of Strength and Conditioning Research
DOIs
Publication statusPublished - 2015

Keywords

  • exhaustion test
  • lower limb performance
  • overload estimated maximum value
  • overload training

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