Although strong core muscles are believed to help athletic performance, few scientific studies have been conducted to identify the effectiveness of core strength training (CST) on improving athletic performance. The aim of this study was to determine the effects of 6 weeks of CST on ground reaction forces (GRFs), stability of the lower extremity, and overall running performance in recreational and competitive runners. After a screening process, 28 healthy adults (age, 36.9 +/- 9.4 years; height, 168.4 +/- 9.6 cm; mass, 70.1 +/- 15.3 kg) volunteered and were divided randomly into 2 groups (n = 14 in each group). A test-retest design was used to assess the differences between CST (experimental) and no CST (control) on GRF measures, lower-extremity stability scores, and running performance. The GRF variables were determined by calculating peak impact, active vertical GRFs (vGRFs), and duration of the 2 horizontal GRFs (hGRFs), as measured while running across a force plate. Lower-extremity stability was assessed using the Star Excursion Balance Test. Running performance was determined by 5000-m run time measured on outdoor tracks. Six 2 (pre, post) x 2 (CST, control) mixed-design analyses of variance were used to determine the influence of CST on each dependent variable, p < 0.05. Twenty subjects completed the study (nexp = 12 and ncon = 8). A significant interaction occurred, with the CST group showing faster times in the 5000-m run after 6 weeks. However, CST did not significantly influence GRF variables and lower-leg stability. Core strength training may be an effective training method for improving performance in runners.

Functional Movement Screen (FMS) scores of ≤14 have been used to predict injury in athletic populations. Movement asymmetries and poor-quality movement patterns in other functional tests have been shown to predict musculoskeletal injury (MSI). Therefore, movement asymmetry or poor-quality movement patterns on the FMS may have more utility in predicting MSI than the composite score.Context: To determine if an asymmetry or score of 1 on an individual FMS test would predict MSI in collegiate athletes.Objective: Cohort study.Design: National Collegiate Athletic Association Division II university athletic program.Setting: A total of 84 Division II rowers, volleyball players, and soccer players (men: n = 20, age = 20.4 ± 1.3 years, height = 1.77 ± 0.04 m, mass = 73.5 ± 4.8 kg; women: n = 64, age = 19.1 ± 1.2 years, height = 1.69 ± 0.09 m, mass = 64.8 ± 9.4 kg).Patients or Other Participants: The FMS was administered during preseason preparticipation examinations. Injury-incidence data were tracked for an academic year by each team's certified athletic trainer via computer software. An MSI was defined as physical damage to the body secondary to athletic activity or an event for which the athlete sought medical care, and resulted in modified training or required protective splitting or taping. Composite FMS scores were categorized as low (≤14) or high (>14). Pearson χ² analyses were used to determine if MSI could be predicted by the composite FMS score or an asymmetry or score of 1 on an individual FMS test (P < .05).Main Outcome Measure(s): Athletes with FMS scores of ≤14 were not more likely to sustain an injury than those with higher scores (relative risk = 0.68, 95% confidence interval = 0.39, 1.19; P = .15). However, athletes with an asymmetry or individual score of 1 were 2.73 times more likely to sustain an injury than those without (relative risk = 2.73, 95% confidence interval = 1.36, 5.4; P = .001).Results: Asymmetry or a low FMS individual test score was a better predictor of MSI than the composite FMS score.Conclusions:

E of a competitive season in collegiate athletes. Movement pattern quality as measured by the functional movement screen (FMS) has recently been linked to performance and injury risk. The purpose of this study was to document the changes in functional movement patterns over a competitive season. Fifty-seven National Collegiate Athletic Association Division II athletes were screened using the FMS as part of the pre and post participation examination for their competitive seasons in 2012. Composite and individual FMS test scores for the preseason and postseason were compared with identified significant changes. The scores were also analyzed for changes in the number of asymmetries present and the frequency of a score of 1 in any of the tests. There were no significant interactions in the main effects for time or sport in the composite FMS scores. However, 4 individual tests did show significant change. The deep squat (Z = −3.260, p = 0.001) and in-line lunge scores (Z = −3.498, p < 0.001) improved across all athletes, and the active straight leg raise (Z = −2.496, p = 0.013) and rotary stability scores (Z = −2.530, p = 0.011) worsened across all athletes. A reduction in the number of asymmetries (χ2 = 4.258, p = 0.039) and scores of 1 (χ2 = 26.148, p < 0.001) were also found. Changes in individual fundamental movement patterns occur through the course of a competitive season....

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Background/Objectives: Using advanced methodologies may enhance athlete profiling. This study profiled morphological and laboratory-derived performance biomechanics by position of American-style football players training for the draft. Methods: Fifty-five players were categorized into three groups: Big (e.g., lineman; n = 17), Big–skill (e.g., tight end; n = 11), and Skill (e.g., receiver; n = 27). Body fat (BF%), lean body mass (LBM), and total body mass were measured using a bioelectrical impedance device. Running ground reaction force (GRF) and ground contact time (GCT) were obtained using an instrumented treadmill synchronized with a motion capture system. Dual uniaxial force plates captured countermovement jump height (CMJ-JH), normalized peak power (CMJ-NPP), and reactive strength. Asymmetry was calculated for running force, GCT, and CMJ eccentric and concentric impulse (IMP). MANOVA determined between-group differences, and radar plots for morphological and performance characteristics were created using Z-scores. Results: There was a between-group difference (F(26,80) = 5.70, p < 0.001; Wilk’s Λ = 0.123, partial η² = 0.649). Fisher’s least squares difference post hoc analyses showed that participants in the Skill group had greater JH, CMJ-NPP, reactive strength, and running GRF values versus Big players but not Big–skill players (p < 0.05). Big athletes had greater BF%, LBM, total body mass, and GCT values than Skill and Big–skill athletes (p < 0.05). Big–skill players had greater GCT asymmetry than Skill and Big players (p < 0.05). Asymmetries in running forces, CMJ eccentric, and concentric IMP were not different (p > 0.05). Morphological and performance biomechanics differences are pronounced between Skill and Big players. Big–skill players possess characteristics from both groups. Laboratory-derived metrics offer precise values of running and jumping force strategies and body composition that can aid sports science researchers and practitioners in refining draft trainee profiles.