Documentation of the lower extremity motion patterns of adolescent pitchers is an important part of understanding the pitching motion and the implication of lower extremity technique on upper extremity loads, injury and performance. The purpose of this study was to take the initial step in this process by documenting the biomechanics of the lower extremities during the pitching cycle in adolescent pitchers and to compare these findings with the published data for older pitchers. Three-dimensional motion analysis using a comprehensive lower extremity model was used to evaluate the fast ball pitch technique in adolescent pitchers. Thirty-two pitchers with a mean age of 12.4 years (range 10.5–14.7 years) and at least 2 years of experience were included in this study. The pitchers showed a mean of 49 ± 12° of knee flexion of the lead leg at foot contact. They tended to maintain this position through ball release, and then extended their knee during the follow through phase (ball release to maximal internal glenohumeral rotation). The lead leg hip rapidly progressed into adduction and flexion during the arm cocking phase with a range of motion of 40 ± 10° adduction and 30 ± 13° flexion. The lead hip mean peak adduction velocity was 434 ± 83°/s and flexion velocity was 456 ± 156°/s. Simultaneously, the trailing leg hip rapidly extended approaching to a mean peak extension of –8 ± 5° at 39% of the pitch cycle, which is close to passive range of motion constraints. Peak hip abduction of the trailing leg at foot contact was –31 ± 12°, which also approached passive range of motion constraints. Differences and similarities were also noted between the adolescent lower extremity kinematics and adult pitchers; however, a more comprehensive analysis using similar methods is needed for a complete comparison.
Matthew D. Milewski, Sylvia Õunpuu, Matthew Solomito, Melany Westwell, and Carl W. Nissen
Andrea Stracciolini, Caitlin M. McCracken, William P. Meehan III, and Matthew D. Milewski
Purpose: To study mental health, sleep duration, and daytime sleepiness in young athletes. Methods: A cross-sectional questionnaire study was conducted. The main outcome measures included sleep duration and daytime sleepiness. Results: Study participants included 756 athletes with a mean age of 13.5 years. A total of 39% (n = 296/756) reported not meeting current sleep recommendations for age. Athletes >12 years and with a self-reported anxiety and/or depression history were less likely to meet sleep recommendations and showed higher daytime sleepiness (adjusted odds ratio [aOR] = 1.29, 95% confidence interval [CI] [1.2, 1.4], β [SE] = 3.06 [0.74], respectively). Athletes with goal-oriented reasons for playing versus enjoyment (52% vs. 35%, aOR = 1.70, 95% CI [1.12, 2.58]) were less likely to meet sleep recommendations. Night time internet access and weeknight homework hours were negatively associated with sleep recommendations (aOR = 1.68, 95% CI [1.68, 2.47] and aOR = 3.11, 95% CI [1.82, 5.3]) and positively associated with daytime sleepiness (β [SE] = 1.44 [0.45] and 2.28 [0.59]). Conclusions: Many young athletes are not meeting sleep recommendations. Associated factors include mental health, reasons for play, internet access, and homework demand.