Home > Journals > Medicina dello Sport > Past Issues > Medicina dello Sport 2014 September;67(3) > Medicina dello Sport 2014 September;67(3):513-26

CURRENT ISSUE
 

ARTICLE TOOLS

Reprints

MEDICINA DELLO SPORT

A Journal on Sports Medicine


Official Journal of the Italian Sports Medicine Federation
Indexed/Abstracted in: BIOSIS Previews, EMBASE, Science Citation Index Expanded (SciSearch), Scopus
Impact Factor 0,163


eTOC

 

FORUM  


Medicina dello Sport 2014 September;67(3):513-26

language: English, Italian

Periodization of strength training: from traditional to daily undulating periodized models

Merni F., Bartolomei S., Ciacci S.

Dipartimento di Scienze Biomediche e Neuromotorie, Alma Mater Studiorum Università di Bologna, Bologna, Italia


PDF  


Training periodization, defined as a planned distribution of workload over time, has been used for several decades in strength and power sport training. The early model proposed by Matveev at the beginning of the 1960s has been deeply changed in subsequent development by other eastern european scientists. The aim of the study was to describe the origin and the fundamental characteristics of the most important periodization models to avoid misunderstandings found in western literature. At the end of the 1970s some alternative models to the traditional one, were proposed in order to optimize the training process and adapt the workload to the different needs of athletes. One of these new interpretations of training theory was the block periodization model which is based upon a concentration of a specific workload and a large use of special strength exercises. At the end of the 1980s in the United States researchers developed a highly varied periodization which was diametrically opposed to the block concepts of concentration of stimuli. This new approach was called Daily Undulating Periodization and was based upon the variation of the strength training goal in each training session. Understanding and classifying the different periodization models on a historical and methodological basis can help us to understand and correctly apply the different workload distributions in order to obtain best results.

top of page

Publication History

Cite this article as

Corresponding author e-mail