Performance prediction models based on anthropometric, genetic and psychological traits of Croatian sprinters

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During pre-adolescence, several variables connected to growth and weight status could influence physical performance and technical skills. This study aims to assess the influence of growth-related anthropometric changes, weight status, and basketball experience on physical performance in pre-adolescent basketball players. The sample consisted of 50 male basketball players (12.2 ± 0.4 years-old) included in the U-13 category. Anthropometric characteristics were collected using standard procedures. Physical performance was evaluated by 20 m Dash, T-test, squat jump, countermovement jump, and medicine ball throw. In order to assess growth-related changes, we conducted two surveys within a 10-week time span. Student’s t-test was used to compare the data collected in the two surveys and multiple regression analyses were performed to assess the effects of growth, weight status, and basketball experience on performance. After 10 weeks there was a significant increase in FFM (Fat-Free Mass) and a significant decrease in fat parameters. Moreover, between the two surveys, all motor tests significantly improved. The results of linear regression models showed that changes in %F (percentage of body fat) were significantly associated with speed and agility, while handgrip strength and weight status were associated with upper limb explosive strength. Basketball experience was a significant predictor of all three motor tests. In conclusion, body composition changes, years of experience, and weight status influenced physical performance and players’ motor skills ability, especially speed, agility, and upper limb explosive strength.

Section: Introductionmentioning

confidence: 99%

Effects of Anthropometric Growth and Basketball Experience on Physical Performance in Pre-Adolescent Male Players

Rinaldo

Toselli

Gualdi‐Russo

et al. 2020

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“…Its aim is to help the personalization of medical practice, so that it can be tailored for the patients [ 28 ]. In sport medicine, ML can be used for both performance and risk prediction [ 29 , 30 ]. Further, ML can identify molecular markers for cancer treatments, evaluate postoperative surgical outcomes, and supply an automated interpretation of an ECG or an automated detection of a lung nodule in a chest X-ray [ 31 ].…”

Section: Resultsmentioning

confidence: 99%

How Artificial Intelligence and New Technologies Can Help the Management of the COVID-19 Pandemic

Barbieri

Giuliani

Prete

et al. 2021

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The COVID-19 pandemic has worked as a catalyst, pushing governments, private companies, and healthcare facilities to design, develop, and adopt innovative solutions to control it, as is often the case when people are driven by necessity. After 18 months since the first case, it is time to think about the pros and cons of such technologies, including artificial intelligence—which is probably the most complex and misunderstood by non-specialists—in order to get the most out of them, and to suggest future improvements and proper adoption. The aim of this narrative review was to select the relevant papers that directly address the adoption of artificial intelligence and new technologies in the management of pandemics and communicable diseases such as SARS-CoV-2: environmental measures; acquisition and sharing of knowledge in the general population and among clinicians; development and management of drugs and vaccines; remote psychological support of patients; remote monitoring, diagnosis, and follow-up; and maximization and rationalization of human and material resources in the hospital environment.

“…In the same way, it would be useful to carry out more complex statistical techniques that make it possible to establish predictive models, as has been done in other sports contexts [ 30 , 37 ].…”

Section: Discussionmentioning

confidence: 99%

Relationship between Anthropometric Measures and Anxiety Perception in Soccer Players

Martínez-Rodríguez

Peñaranda-Moraga

Vicente-Martínez

et al. 2022

In the sports context, it has been corroborated that the physical demands of presenting an “ideal” body configuration have been associated with different psychological variables, such as self-esteem, anxiety and personality dimensions, such as perfectionism. Specifically, there is evidence that anthropometric measures may be closely related to psychological indicators. A total of 33 male soccer players (18.12 ± 1.24 years) participated in the investigation. Anthropometric assessments were carried out following the ISAK standards for the restricted profile. All of them completed the Competitive Trait Anxiety Inventory (CTAI-2D) in its Spanish version. The percent fat was calculated using Withers (density) and Siri equations. The ∑7 skinfolds were used to calculate this. After statistical analysis, significant mean differences were observed in the somatic anxiety dimension (valence) and a medium–large effect size. Regarding correlations, the significantly negative relationship between self-confidence (intentionality) and somatic anxiety (valence) was noteworthy. The relationship between psychological variables and anthropometric measurements was corroborated, showing the need for interdisciplinary work between psychologists and nutritionists who do not ignore the physical health and psychological well-being of the soccer player.