Comparison of Different Recovery Strategies After High-Intensity Functional Training: A Crossover Randomized Controlled Trial.

We aimed to determine whether voluntary exercise or surface neuromuscular electrical stimulation (NMES) could enhance recovery after a high-intensity functional training (HIFT) session compared with total rest. The study followed a crossover design. Fifteen male recreational CrossFit athletes (29 ± 8 years) performed a HIFT session and were randomized to recover for 15 min with either low-intensity leg pedaling ("Exercise"), NMES to the lower limbs ("NMES"), or total rest ("Control"). Perceptual [rating of perceived exertion (RPE) and delayed-onset muscle soreness (DOMS) of the lower-limb muscles], physiological (heart rate, blood lactate and muscle oxygen saturation) and performance (jump ability) indicators of recovery were assessed at baseline and at different time points during recovery up to 24 h post-exercise. A significant interaction effect was found for RPE (p = 0.035), and although post hoc analyses revealed no significant differences across conditions, there was a quasi-significant (p = 0.061) trend toward a lower RPE with NMES compared with Control immediately after the 15-min recovery. No significant interaction effect was found for the remainder of outcomes (all p > 0.05). Except for a trend toward an improved perceived recovery with NMES compared with Control, low-intensity exercise, NMES, and total rest seem to promote a comparable recovery after a HIFT session.

Effects of an Injury Prevention Program in CrossFit Athletes: A Pilot Randomized Controlled Trial.

The present study aimed to assess the effects of an injury prevention program in CrossFit athletes. Thirty-two CrossFit athletes were randomized to either an intervention group (n=16), that performed mobility and stability exercises during the warm-up of all CrossFit sessions for a 10-week period or to a control group (n=16) that kept performing their usual warm-up. Incidence of injuries (primary outcome) as well as average training loads, fatigue and pain perception were registered during the study. The overall injury incidence rate was 0.04 per 1000 training hours, with no differences between groups (p>0.05). Similarly, no between-group differences were found for injury severity, nor for average training volume, intensity, training load, pain, or fatigue perception during the study (all p>0.05 with trivial-to-small effect sizes). In summary, a 10-week injury prevention program consisting of stability and mobility exercises provided no benefits on injury rates, fatigue and pain perception in recreational CrossFit athletes. Further research might corroborate the preliminary evidence reported here.

Physiological Predictors of Competition Performance in CrossFit Athletes.

The aim of this study was to determine the physiological variables that predict competition performance during a CrossFit competition. Fifteen male amateur CrossFit athletes (age, 35 ± 9 years; CrossFit experience, 40 ± 27 months) performed a series of laboratory-based tests (incremental load test for deep full squat and bench press; squat, countermovement and drop jump tests; and incremental running and Wingate tests) that were studied as potential predictors of CrossFit performance. Thereafter, they performed the five Workouts of the Day (WODs) corresponding to the CrossFit Games Open 2019, and we assessed the relationship between the laboratory-based markers and CrossFit performance with regression analyses. Overall CrossFit performance (i.e., final ranking considering the sum of all WODs, as assessed by number of repetitions, time spent in exercises or weight lifted) was significantly related to jump ability, mean and peak power output during the Wingate test, relative maximum strength for the deep full squat and the bench press, and maximum oxygen uptake (VO2max) and speed during the incremental test (all p < 0.05, r = 0.58-0.75). However, the relationship between CrossFit Performance and most laboratory markers varied depending on the analyzed WOD. Multiple linear regression analysis indicated that measures of lower-body muscle power (particularly jump ability) and VO2max explained together most of the variance (R2 = 81%, p < 0.001) in overall CrossFit performance. CrossFit performance is therefore associated with different power-, strength-, and aerobic-related markers.

Full-Squat as a Determinant of Performance in CrossFit.

This study analyzed the relationship between CrossFit performance and power and strength variables measured in the full-squat exercise. Twenty male trained subjects (33±7 years) performed an incremental load full-squat test for assessment of the 1-repetition maximum (1RM) and the mean (Pmean) and peak (Ppeak) power. Performance in 5 different Workouts of the Day (WODs) was measured on different days, and overall CrossFit performance was determined as the sum of the scores obtained in these WODs. Athletes were then assigned to a high (HP) or low (LP) performance group based on the median score for overall performance. Correlation analysis between squat variables and performance was performed and between-group differences were assessed. Moderate to strong (r=0.47-0.69, p<0.05) positive correlations were found between squat variables and performance in the different WODs. Overall CrossFit performance was strongly and positively associated with absolute (r=0.62, p=0.01) and relative 1RM (r=0.65, p=0.07), and relative Pmean (r=0.56, p=0.02) and Ppeak (r=0.53, p=0.03). Large differences (effect sizes ranging 1.1-1.7, all p<0.05) were observed between HP and LP for absolute and relative 1RM, relative Pmean, and absolute and relative Ppeak. In summary, strength and power indexes measured in a squat test are positively associated with CrossFit performance.