Comparison of Physiological Responses and Training Load between Different CrossFit® Workouts with Equalized Volume in Men and Women

Fatigue and Performance Rates as Decision-Making Criteria in Pacing Control During CrossFit®

We investigated fatigue and performance rates as decision-making criteria in pacing control during CrossFit®. Thirteen male regional-level competitors completed conditions of all-out (maximum physical work from beginning to end) and controlled-split (controlled physical work in the first two rounds but maximum work in the third round) pacing throughout the Fight Gone Bad workout separated by one week. We assessed benchmarks, countermovement jumps and ratings of fatigue after each round. Benchmarks were lower in round 1 (99 vs. 114, p < .001) but higher in rounds 2 (98 vs. 80, p < .001) and 3 (97 vs. 80, p < .001) for controlled-split compared with all-out pacing. Reductions in countermovement jumps were higher after rounds 1 (-12.6% vs. 1.6%, p < .001) and 2 (-12.7% vs. -4.0%, p = .014) but similar after round 3 (-13.2% vs. -11.3%, p = .571) for all-out compared with controlled-split pacing. Ratings of fatigue were higher after rounds 1 (7 vs. 5 a.u., p < .001) and 2 (8 vs. 7 a.u, p = .023) but similar after round 3 (9 vs. 9 a.u., p = .737) for all-out compared with controlled-split pacing. During all-out pacing, countermovement jump reductions after round 2 correlated with benchmark drops across rounds 1 and 2 (r = .78, p = .002) and rounds 1 and 3 (r = -.77, p = .002) and with benchmark workout changes between pacing strategies (r = -.58, p = .036), suggesting that the larger the countermovement jump reductions the higher the benchmark drops across rounds and workouts. Therefore, benchmarks, countermovement jumps and ratings of fatigue may assess exercise-induced fatigue as decision-making criteria to improve pacing strategy during workouts performed for as many repetitions as possible.

Differential improvements between men and women in repeated CrossFit open workouts

INTRODUCTION

The CrossFit® Open (CFO) acts a preliminary round that qualifies men and women for later stages of its annual Games competition. The CFO typically consists of 4-6 workouts that variably challenge an athlete's weightlifting strength, gymnastic skill, and endurance capacity. Except for differences in prescribed intensity loads, workouts are designed the same for men and women to elicit a similar challenge. While all workouts within a single year are unique to each other, one has been repeated from a previous CFO each year between 2012 and 2021. Because previous CFO workouts are often integrated into training, improvements are expected when a workout is officially repeated. However, besides documented record performances, it is unclear whether most athletes are improving, if these improvements affect ranking, or if differences exist between men and women.

PURPOSE

To examine sex-division differences and performance changes across repeated CFO workouts, as well as their effect on CFO and workout ranking.

METHODS

Eleven separate samples of 500 men and 500 women, who were representative of the same overall percent rank within each year involving one of the nine repeated CFO workouts (2011-2021) were drawn for this study. Each athlete's age (18-54 years), rank (overall and within each workout), and reported workout scores were collected from the competition's publicly-available leaderboard. Each sample had excluded any athlete who had not met minimum performance criteria (e.g., at least one completed round) for all prescribed (Rx) workouts within a given year (including those not analyzed). Since some workouts could be scored as repetitions completed or time-to-completion (TTC), and because programming was often scaled between men and women, all scores were converted to a repetition completion rate (repetitions divided by TTC [in minutes]).

RESULTS

Separate sex-division x time analyses of variance with repeated measures revealed significant (p < 0.05) interactions in all but one repeated workout comparison. Initially, men were faster in four workouts (~18.5%, range = 3.9-35.0%, p < 0.001), women in two (~7.1%, range = 5.2-9.0%, p < 0.001), and they tied in the remaining three workouts. When workouts were repeated in subsequent years, men were faster in three workouts (~5.4%, range = 0.9-7.8%, p < 0.05), while women were faster in two (~3.8%, range = 3.5-4.1%, p < 0.01). Though performance improved in seven of the nine workouts (~14.3%, p < 0.001) and percentile rank was controlled, athletes earned a lower rank (overall and within workout) on each repeated workout (p < 0.001).

CONCLUSIONS

Performance (measured as repetition completion rate) has improved in most repeated CFO workouts, particularly for women. However, improvements seen among all athletes, along with increased participation, have made it more difficult for athletes to improve their overall rank. To rank higher, individual athletes must improve their pace to a greater degree than the average improvements seen across the competitive field.

Musculoskeletal Injury Prevalence, Pain Perception, and Physical Activity Level Among Brazilian Strength and Cross-Training Practitioners

In this study, we sought to determine the prevalence of musculoskeletal injuries, perceived pain, and physical activity level among Brazilian practitioners of strength training (ST) and functional fitness (FF). Participants were 311 men and women who trained in 10 FF training centers and seven ST gyms. Each participant completed surveys of the prevalence of musculoskeletal injuries, their pain perception, and their physical activity level. A chi square test was used to analyze associations between groups and distributions of injuries. When any significant difference was observed, the difference score was analyzed through the adjusted residual values. Fisher's exact test was used to determined the associations between musculoskeletal injury prevalence and training modality (FF and ST) and between musculoskeletal injury prevalence and practice frequency (times/wk). To measure the magnitude of association between variables, the Phi coefficient was calculated for 2x2 associations and Cramer's V was used whenever the distributions were outside this standard. When the dependent variable presented a dichotomous characteristic, an Odds Ratio (OR) was calculated with a confidence interval of 95%. We found a higher musculoskeletal injury prevalence in the axial skeleton (n = 52; 83.88%) in FF practitioners and in the lower limbs of ST practitioners (n = 9; 52.96%). When the physical activity level cutoff point was set at 300 minutes per week, there was a significant relationship between physical activity and training modality (p = 0.005). There was also a significant association between pain perception and musculoskeletal injury (p < 0.001). Clinical follow-up was a protective factor to being injured (OR = 0.18; CI = 0.06-0.49), and, even after multivariate analysis this significant association was maintained (OR = 0.03; CI = 0.01 - 0.08). Thus, FF practitioners reported more musculoskeletal injuries than STs, and follow-up medical or physical therapy was a protective factor to these injuries. FF practitioners also had a higher level of weekly physical activity weekly than ST practitioners. Functional fitness practitioners may be at a higher risk of injuries than those who participate in traditional strength training.

Physiological effects of regular CrossFit® training and the impact of the COVID-19 pandemic—A systematic review

CrossFit® is a functional fitness training program known for its day-to-day varying “Workouts of the Day” (WOD). In accordance with the ‘CrossFit® Level 1 Training Guide’, regular CrossFit® training sessions consist of Warm-up, Mobility, Skill/Power training, WOD, and Cool-down. Despite the fast-growing and widespread popularity, data on the practical implementation of the training program based on scientific evidence are rare. Therefore, the purpose of this study is to systematically review the existing literature on the physiological effects of regular CrossFit® training in full extent instead of stand-alone WODs and to examine the impact of the COVID-19 pandemic on the training behavior of CrossFit® athletes. A systematic search was conducted following the PRISMA guidelines in April 2022 and updated in July 2022 using the following databases: PubMed, SPORTDiscus, Scopus, and Web of Science. Using the keyword “CrossFit”, 1,264 records were found. Based on the eligibility criteria, 12 studies are included and separated by topics: acute-short term physiological response (n = 8), and impact of the COVID-19 pandemic (n = 4). The results show that studies of regular training sessions were rarely conducted and contradicted the existing knowledge of the physiological demands [e.g., heart rate (HR)] of CrossFit®. In detail, included studies demonstrate that training sessions last 30–60 min and provide a progressive increase in cardiovascular load up to maximal effort activity (&gt;90% HRmax), differing from stand-alone WODs exclusively at high-intensity. Also, scarce research exists on COVID-19-pandemic-induced effects on training behavior, and studies are of moderate to low quality. There is still a lack of comprehensive analyses on the acute physiological effects of regular training sessions and the consequences of the COVID-19 pandemic in the scientific literature. Moreover, the inconsistent terminology used in CrossFit® research complicates generalized conclusions. Therefore, future research on the training methodology of CrossFit® needs to overcome terminological inequalities and examine scientifically the implementation of the concept by considering regular training sessions under practical settings.

Acute physiological outcomes of high-intensity functional training: a scoping review

Background

Systematic reviews and meta-analyses related to high-intensity functional training (HIFT) have been conducted. However, due to a restricted pool of available research, these investigations are often limited in scope. As such, a scoping review investigating the present literature surrounding the acute physiological response to HIFT-based exercise was chosen as a more appropriate structured review.

Methodology

A scoping review was conducted following Arksey and O'Malley's framework. Three large scale databases were searched to reveal any article pertaining to HIFT and related exercise terminology.

Results

A total of 2,241 articles were found during the initial search. Following this, titles, then abstracts, and full-texts were reviewed to determine inclusion eligibility. A total of 60 articles which investigated a combined total of 35 unique HIFT workouts were included within this review.

Conclusions

A variety of physiological parameters and HIFT workouts have been examined. Markers of intensity (e.g., blood lactate concentrations, heart rate) have been most consistently assessed across all studies, and these support the idea that HIFT workouts are typically performed at high-intensity. In contrast, the inclusion of most other measures (e.g., hormonal, markers of inflammation and damage, energy expenditure, performance) has been inconsistent and has thus, limited the possibility for making generalized conclusions. Differences in study methodologies have further impacted conclusions, as different studies have varied in sample population characteristics, workouts assessed, and time points. Though it may be impossible to comprehensively research all possible HIFT workouts, consistent adoption of population definitions and workload quantification may overcome this challenge and assist with future comparisons.

Quantifying CrossFit®: Potential solutions for monitoring multimodal workloads and identifying training targets

The design of high-intensity functional training (HIFT; e. g., CrossFit^®) workouts and targeted physiological trait(s) vary on any given training day, week, or cycle. Daily workouts are typically comprised of different modality and exercise combinations that are prescribed across a wide range of intensities and durations. The only consistent aspect appears to be the common instruction to maximize effort and workout density by either completing "as many repetitions as possible" within a time limit (e.g., AMRAP, Tabata) or a list of exercises as quickly as possible. However, because effort can vary within and across workouts, the impact on an athlete's physiology may also vary daily. Programming that fails to account for this variation or consider how targeted physiological systems interrelate may lead to overuse, maladaptation, or injury. Athletes may proactively monitor for negative training responses, but any observed response must be tied to a quantifiable workload before meaningful changes (to programming) are possible. Though traditional methods exist for quantifying the resistance training loads, gymnastic movements, and cardiorespiratory modalities (e.g., cycling running) that might appear in a typical HIFT workout, those methods are not uniform, and their meaning will vary based on a specific exercise's placement within a HIFT workout. To objectively quantify HIFT workloads, the calculation must overcome differences in measurement standards used for each modality, be able to account for a component's placement within the workout and be useful regardless of how a workout is commonly scored (e.g., repetitions completed vs. time-to-completion) so that comparisons between workouts are possible. This review paper discusses necessary considerations for quantifying various HIFT workout components and structures, and then details the advantages and shortcomings of different methods used in practice and the scientific literature. Methods typically used in practice range from being excessively tedious and not conducive for making comparisons within or across workouts, to being overly simplistic, based on faulty assumptions, and inaccurate. Meanwhile, only a few HIFT-related studies have attempted to report relevant workloads and have predominantly relied on converting component and workout performance into a rate (i.e., repetitions per minute or second). Repetition completion rate may be easily and accurately tracked and allows for intra- and inter-workout comparisons. Athletes, coaches, and sports scientists are encouraged to adopt this method and potentially pair it with technology (e.g., linear position transducers) to quantify HIFT workloads. Consistent adoption of such methods would enable more precise programming alterations, and it would allow fair comparisons to be made between existing and future research.

Predicting the Clean Movement Technique in Crossfit® Athletes Using an Optimal Upper-Limb Range of Motion: A Prospective Cohort Study

BACKGROUND

The aim of this study was to determine the optimal upper-limb range of motion (ROM) profile for the catch phase of the clean movement (CPCM) and to identify the key ROMs for performing the CPCM in CrossFit^® athletes.

METHODS

A prospective cohort study of twenty CrossFit^® athletes aged 20-36 years was conducted. Data were collected regarding age, anthropometrics, CrossFit^® training experience and upper-limb ROM. The ROM was measured using the ROM-SPORT method. After 7 months, athletes performed a clean movement with a load of 80% one repetition maximum. A Bayesian Student's t-analysis, binary logistic regression analysis and Receiver Operating Characteristic analysis were performed.

RESULTS

The optimal upper-limb ROM profile that predicted correct CPCM performance was 78° in shoulder extension, 173° in shoulder flexion, 107° in shoulder external rotation, 89° in shoulder internal rotation, 153° in elbow flexion, 99° in elbow pronation and 92° in wrist extension (area under the curve ≥ 651; positive predictive value ≥ 80%). Shoulder external rotation, elbow pronation and wrist extension were found to be the most important ROMs for the efficient and safe performance of CPCM (area under the curve ≥ 854; positive predictive value ≥ 85.7%).

CONCLUSION

The upper-limb ROM profile is associated with proper clean performance. Further studies are warranted to determine whether improving flexibility on upper-limb ROM may improve proper clean movement performance.

Time Course of Recovery Following CrossFit® Karen Benchmark Workout in Trained Men

The establishment of fatigue following the acute exercise stimulus is a complex and multi-factorial process, that might arise due to a range of distinct physiological mechanisms. However, a practical method of assessing CrossFit^® athletes’ recovery status has been neglected entirely in real-world sporting practice. The study describes the acute and delayed time course of recovery following the CrossFit^® Benchmark Workout Karen. Eight trained men (28.4 ± 6.4 years; 1RM back squat 139.1 ± 26.0 kg) undertook the Karen protocol. The protocol consists of 150 Wall Balls (9 kg), aiming to hit a target 3 m high. Countermovement jump height (CMJ), creatine kinase (CK), and perceived recovery status scale (PRS) (general, lower and upper limbs) were assessed pre, post-0h, 24, 48 and 72 h after the session. The creatine kinase concentration 24 h after was higher than pre-exercise (338.4 U/L vs. 143.3 U/L; p = 0.040). At 48h and 72 h following exercise, CK concentration had returned to baseline levels (p > 0.05). The general, lower and upper limbs PRS scores were lower in the 24-h post-exercise compared to pre-exercise (general PRS: 4.7 ± 1.5 and 7.7 ± 1.7; p = 0.013; upper limbs PRS: 6.6 ± 1.3 and 7.5 ± 1.3; p = 0.037; lower limbs PRS: 3.9 ± 2.5 and 7.3 ± 0.1; p = 0.046). Our findings provide insights into the fatigue profile and recovery in acute CrossFit^® and can be useful to coaches and practitioners when planning training programs. Moreover, recovery status can be useful to optimize training monitoring and to minimize the potential detrimental effects associated with the performance of repeated high-intensity sessions of CrossFit^®.

Effects of Introducing Rest Intervals in Functional Fitness Training

Background: Functional Fitness Training (FFT) is a new exercise modality prioritizing functional multi-joint movements executed at high intensity as a circuit. Objective: To examine the impacts of introducing rest intervals in a FFT workout compared to “rounds for time” (RFT) FFT. Materials and Methods: Participants were 25 resistance-trained adults who completed two FFT workouts 1 week apart. The study design was crossover such that in a given session half the participants completed the standard and the other half the adapted FFT (FFTadapted). The workouts consisted of the same exercises (circuit of four rounds of exercises), but one (FFTadapted) included preset rest intervals (three sets of 1 min after each completed round). Before and after the workouts, countermovement jump ability and blood lactate were measured. Heart rate (HR) and ratings of perceived exertion (RPE) were measured post-exercise. Results: For both the standard and adapted protocols, mean HR was 90% age-predicted maximum. Final RPE was also similar for both workouts (~15–15.5) and indicated a “hard” work intensity. Both FFTs took the same time to complete (~13 min). Furthermore, no significant differences were observed in jump ability between FFTs. In contrast, lactate (15.11 ± 3.64 vs. 13.48 ± 3.64 mmol·L−1, p < 0.05), measured 3 min post-exercise, was significantly lower in FFTadapted. Conclusions: In FFTadapted, there was a significant reduction in RPE and blood lactate concentrations after exercise, while there were no significant differences in either HR or jumping ability, compared to a FFT workout in RFT methodology.