Prediction of Gymnastics Physical Profile Through an International Program Evaluation in Women Artistic Gymnastics

Abstract

Nassib, SH, Mkaouer, B, Riahi, SH, Wali, SM, and Nassib, S. Prediction of gymnastics physical profile through an international program evaluation in women artistic gymnastics. J Strength Cond Res 34(2): 577–586, 2020—The purpose of this study was to investigate the most appropriate aptitudes for top-level sporting results to identify physical profile of talent identified women's artistic gymnastics (WAG). Forty-eight women's artistic gymnasts in the provincial team (age 11.12 ± 1.22 years; height 1.35 ± 0.04 m; body mass 28.5 ± 4.04 kg) voluntarily participated in this study. Anthropometrics measures and the WAG battery physical tests were used to ensure a systematic approach for the WAG development worldwide. The present findings revealed that the strength (static strength, speed strength, and endurance strength), power and flexibility seem to be important and essential for good performance. Another characteristic that emerged from the results of the physical domain is coordination. This motor skill may seem relevant to gymnastics, they are applicable to the gymnasts' ability to perform all apparatus and more generally they relate to the ability to accurately perform whole-body skills supported by the leg on the floor, balance beam, and vault. Therefore, athletic performance can be boosted using combination of several characteristics that seems to be important for an elite gymnast. This reinforcing the view that systematic approach for the development and mufti-dimensional profile seems promising.

Postural sway in young female artistic and acrobatic gymnasts according to training experience and anthropometric characteristics

“…For example, female artistic gymnastics training leads to perfect performance of the routines on the vault, uneven bars, balance beam and floor. This discipline mainly requires phenomenal strength, power, flexibility, coordination and spatial awareness [16][17][18][19][20][21]. In turn, the effect of training in acrobatic gymnastics is the performance of the figures consisting of static and dynamic routines by the athletes working together.…”

Evaluating the physical and basic gymnastics skills assessment for talent identification in men’s artistic gymnastics proposed by the International Gymnastics

“…The factors were retained only if they were composed of two or more variables. Moreover, the first factor should be concentrated with the greatest part of the tests with factorial weight above 0.70 (i.e., the cutting point adopted for the definition of the connection force between tests) [20, 31]. A stepwise regression was established between the total apparatus score and physical parameters.…”

“…In artistic gymnastics, particularly, some models/programmes of talent identification are emerging in leading countries (e.g., International Gymnastics Federation [FIG] Age Group Development Programme, USA Gymnastics TOPs programme, Gymnastics Functional Measurement Tool [GFMT], and World Identification Systems for Gymnastics Talent [WISGT]). The most accepted programmes used by coaches and researchers are those of the International Gymnastics Federation and the USA Gymnastics [1, 5, 20-26].…”

“…In the literature, several studies [1, 5, 20-26] have investigated talent identification in women artistic gymnastics (WAG), including a recently published study by Nassib et al [20] on prediction of the women artistic gymnastics (WAG) physical fitness profile through the international evaluation programme “FIG Age Group Development” [27]. The main findings of this study were that elite level female gymnasts present greater muscular strength in its different forms (i.e., isometric, explosive, and endurance), power, and flexibility compared to the FIG [27] standards.…”

A development model to guide the recruiting of female shot putters at the NCAA Division I Championship level

“…The use of analytic models to determine future performance is well documented and has been embraced by coaches in individual sports such as swimming (Stanula et al, 2012), speed skating (Kuper & Sterken, 2003), and gymnastics (Nassib, Mkaouer, Riahi, Wali, & Nassib, 2017) as well as in the team sports of ice hockey (Roczniok et al, 2013), soccer (Arndt & Brefeld, 2016;Gonaus & Muller, 2012) and American football (Bergman & Logan, 2016). While the sport of track and field has also made an effort to use predictive analytics to determine future performance, most of that work has focused on the running events.…”