Field-Based Performance Tests Are Related to Body Fat Percentage and Fat-Free Mass, But Not Body Mass Index, in Youth Soccer Players.

The primary aim of this study was to determine the association between body composition and performance outcomes in youth soccer players. Twenty-five competitive male youth soccer players (age = 13.7 ± 0.8 years, height = 167.4 ± 9.7 cm, weight = 57.6 ± 12.1 kg) volunteered to participate in this study. Height and weight were used to calculate body mass index (BMI). Body fat percentage (BF%) and fat-free mass (FFM) were determined with dual-energy X-ray absorptiometry. Each athlete performed the Pacer test, vertical jump, and t-test drill. Participants were predominantly normal weight (20.4 ± 2.7 kg·m-2). The body composition results were 20.3 ± 4.9% for BF% and 46.5 ± 8.7 kg for FFM. The results of the performance tests indicated a mean ± standard deviation (SD) of 1418 ± 332 m for Pacer, 57.2 ± 7.4 cm for vertical jump, 11.6 ± 0.7 s for t-test. Body mass index was not associated with any performance measure (r = 0.02 to -0.21, all p > 0.05). Body fat percentage was associated with the Pacer, vertical jump, and t-test (r = -0.62, -0.57, 0.61, respectively; all p < 0.01) and remained after accounting for BMI. Fat-free mass was only significantly related to t-test (r = -0.43, p < 0.01). However, after controlling for BMI, FFM was related to all three performance tests. Body fat percentage and FFM are associated with performance in youth soccer players, with stronger relationships reported in the former metric. The findings highlight the need for accurate body composition measurements as part of an assessment battery in young athletes.

Age-Predicted Maximal Heart Rate Equations Are Inaccurate for Use in Youth Male Soccer Players.

PURPOSE: The purpose of this study was to compare the differences between measured (MHRobt) and predicted (MHRpred) maximal heart rate (MHR) in youth athletes. METHODS: In total, 30 male soccer players [14.6 (0.6) y] volunteered to participate in this study. MHRobt was determined via maximal-effort graded exercise test. Age-predicted MHR (MHRpred) was calculated for each participant using equations by Fox, Tanaka, Shargal, and Nikolaidis. Mean differences were compared using Friedman's 2-way analysis of variance and post hoc pairwise comparisons. Agreement between MHRobt and MHRpred values was calculated using the Bland-Altman method. RESULTS: There were no significant differences between MHRobt and MHRpred from the Fox (P = .777) and Nikolaidis (P = .037) equations. The Tanaka and Shargal equations significantly underestimated MHRobt (P < .001). All 4 equations produced 95% limits of agreement of ±15.0 beats per minute around the constant error. CONCLUSIONS: The results show that the Fox and Nikolaidis equations produced the smallest mean difference in predicting MHRobt. However, the wide limits of agreement suggests that none of the equations adequately account for individual variability in MHRobt. Practitioners should avoid applying these equations in youth athletes and utilize a lab or field testing protocol to obtain MHR.

College students' perspectives, goals, and strategies in sport education.

We examined the perspective, goals, and strategies of students enrolled in collegiate physical education courses. Our aim was to determine the extent to which a model developed by Allen (1986) describing student-social systems in high schools would approximate those in a collegiate setting. Forty-six students from two elective volleyball classes completed online surveys and participated in group interviews. It was determined that while specific parts of the original model were appropriate for describing college students' agendas for physical education, participation in the Sport Education model provided a more complimentary (in contrast to adversarial) link between the students' quest for good grades and their socializing strategies. A more appropriate model is presented.