The aim of this study was to assess differences in fundamental motor skills (FMS) proficiency between boys and girls of each age group, independently, across the entire preschool period. Using the Movement Assessment Battery for Children–second edition, FMS proficiency was tested in 325 preschoolers (4.9 ± 1.1 y, range 3–6) using a cross-sectional design. Compared to boys of the same age, 3- and 4-year-old girls had greater total (p < .01), fine motor skill (p < .01), and balance scores (p < .05). There were no sex differences for total test or balance scores in 5- and 6-year-olds, but 6-year-old boys outperformed girls in aiming and catching (p < .001). These data not only agree with previous research in that sex differences in FMS proficiency exist in preschool children, but the data also show that differences may not be uniform throughout the whole preschool period when analyzing by age. To avoid under- or overestimating FMS proficiency and subsequently prescribing inaccurate motor intervention programs, FMS proficiency normative values should be age- and sex-specific throughout the entire preschool period.

Previous empirical research and reviews have suggested that the level of fundamental movement skills (FMS), motor competence (MC), physical activity (PA), or physical fitness seem to directly influence the executive functions (EFs) in school aged children. However, there is no available comprehensive review of whether the exact links between motor constructs and EFs also exist in the preschool period, even though preschool age is the critical period for developing EFs. Therefore, this study aimed to systematically review the evidence on the association between FMS, MC, PA, PF, and EFs. To conduct the systematic review, we utilized searches using Web of Science, PubMed, and EBSCO (including SPORTDiscus and Academic Search Premier). We included studies that examined associations between one or all of the four motor constructs with EFs among typically developing children aged 3–6 years, published between January 2010 and October 2021. A total of 15 studies met the inclusion criteria, of which four were randomized controlled trials, three were longitudinal studies, four were cohort studies, and four were cross-sectional studies. We found weak correlations or insufficient evidence for associations between FMS, PA, PF, and EFs. However, there was strong evidence for a moderately strong association between MC and working memory, a moderately weak association between MC and inhibition, and inadequate evidence for a weak to moderate association between MC and shifting. In addition, only half of the included studies were methodologically high-quality studies. Specifically, a questionable design selection of research samples might bias the strength of evaluated associations. We also found significant diversity in the diagnostic tools used for assessing and measuring motor and EFs domains. Our findings support the assumption that motor competencies level, which contains physical capacity and cognitive components, could be significantly linked to EF development from a preschool age. Therefore, we suggest that future studies focus more on clinical trial design, combining movement interventions with different levels of cognitive components, for the purposive development of EFs in preschool-aged children.

Background: Determining somatic models and profiles in young athletes has recently become a fundamental element in selecting basketball playing positions. The aim of this study was to assess the relationship between the body build of young and adult elite male basketball players at different playing positions. Methods: Participants consisted of 35 young (age: 14.09 ± 0.30 years, n = 35) and 35 adult professional basketball players (age: 24.45 ± 5.40 years, n = 35) competing in elite leagues. The anthropometric characteristics assessed included body mass, body height, skinfolds, somatotypes, girths, and breadths. Results: The centers in both age groups were significantly taller and heavier (p < 0.001) compared to forwards and guards. The greatest difference between categories were in the guards’ personal height (from 169.36 to 186.68 = 17.32 cm). The guards from the professional team were closest in height to the forwards (difference = 7.17 cm) compared to young players where the difference between guards and forwards was 13.23 cm. Young competitors were more ectomorphic (2.12-3.75-4.17), while professional players were more mesomorphic (2.26-4.57-3.04). Significant criteria for center selection at professional level seems to be personal height and arm span ratio. Conclusions: The results indicate that the selection for basketball playing positions should include the analysis of body height and mass, shoulder breadth, humerus breadth, femur breadth and specifically for centers the difference between personal the height and arm span.

While tests of basic motor abilities such as speed, maximum strength or endurance are well recognized, testing of complex motor functions such as agility remains unresolved in current literature. Therefore, the aim of this review was to evaluate which main factor or factor structures quantitatively determine agility. In methodological detail, this review focused on research that explained or described the relationships between latent variables in a factorial model of agility using approaches such as principal component analysis, factor analysis and structural equation modeling. Four research studies met the defined inclusion criteria. No quantitative empirical research was found that tried to verify the quality of the whole suggested model of the main factors determining agility through the use of a structural equation modeling (SEM) approach or a confirmatory factor analysis. From the whole structure of agility, only change of direction speed (CODS) and some of its subtests were appropriately analyzed. The combination of common CODS tests is reliable and useful to estimate performance in sub-elite athletes; however, for elite athletes, CODS tests must be specific to the needs of a particular sport discipline. Sprinting and jumping tests are stronger factors for CODS than explosive strength and maximum strength tests. The authors suggest the need to verify the agility factorial model by a second generation data analysis technique such as SEM.

Background: The Bruininks-Oseretsky Test of Motor Proficiency Second Edition (BOT-2) assesses the psychomotor development. It is available in two forms. According to several studies the BOT-2 short form (SF) provides significantly higher results than the BOT-2 complete form (CF). This might be due to the use of an inadequate type of scores when comparing results of the SF and the CF. Objective: To verify whether the degree of psychomotor development assessed by the BOT-2 SF is comparable to the results of the BOT-2 CF in middle-age school children when using standard scores considering age and sex. Methods: The research sample consisted of n = 153 neurotypical children (n = 69 girls, n = 84 boys) from 8 to 11 years (9.53 ± 0.85). The degree of psychomotor development was determined by the standard scores of the BOT-2 CF and BOT-2 SF—both considering sex and age. The conformity in results between the CF and the SF, the sensitivity and specificity of the BOT-2 SF and the relations between the results of each sub-test within the BOT-2 CF and the BOT-2 SF were analyzed. Results: The BOT-2 SF provided a significantly lower standard score x = 45.87 (±5.41) compared to the BOT-2 CF x = 47.57 (±8.29) with middle effect size value, Hays ω² = 0.09. The ROC analysis showed that the BOT-2 SF obtains sufficient sensitivity (84%) but poor specificity (42.9%) and AUC = 0.484 CI95% (0.31–0.62). Moreover, only 57% of total variance of the BOT-2 CF is explained by the relation between the results of the CF and the SF. Conclusion: The BOT-2 SF does not provide significantly different results compared to the BOT-2 CF when using a proper scale for comparing both versions. In addition, poor specificity of the BOT-SF suggests that the BOT-2 SF might be a useful tool to reveal mainly psychomotorically delayed but not above average (psychomotorically advanced) children. Further, due to the weak portion of a shared common factor, it remains still unclear whether the BOT-2 CF and the BOT-2 SF measure the same behavioral domain.