Layout 1 Thematic Section: Advances in Musculoskeletal and Neuromuscular Rehabilitation | Maccarone & Masiero Eur J Transl Myol 34 (3) 12309, 2024 doi: 10.4081/ejtm.2024.12309 Functional fitness training characterizes one of the main trends in exercise science and practice in the last years, a type of training that incorporates aerobic capacity, strength, bodyweight endurance, bodyweight skills, and power.1, 2 Functional fitness training continues to rank in the top 20 fitness trends of 2023 around the world.3 CrossFit® (CrossFit, Inc., Washington, DC, USA) is a type of functional fitness training.1 The growth of this fitness trend is exponential and can be explained due to psychological aspects,4, 5 including people who are interested in health and physical fitness but also performance, through competitions. The competitions of CrossFit® are based on a first stage – called The CrossFit® Open. This is an online competition Abstract There has been an increasing interest among CrossFit® coaches and practitioners in identifying indicators of sport performance. This study aimed to examine the correlation between anthropo- metric measures, cardiorespiratory capacity, power, local muscle endurance, and total athleticism score, with performance in the CrossFit® Open 2021. Fourteen male volunteers (aged 30.3±5.8 years) participated in the study and underwent a series of tests on separate weeks. These tests in- cluded assessments of body fat percentage (subcutaneous adipose thickness measured at seven sites), maximal oxygen consumption (2 km test in rowing ergometer), muscle power (one repeti- tion maximum in power clean), and muscle endurance (Tibana test, which included the conclusion of four distinct rounds of work). These results were used to calculate the total score of athleticism, which was then compared to the participants performance during the CrossFit® Open 2021. The athletes presented an average of body fat (8.6±2.0%), maximal oxygen consumption (53.3±2.4 mL. (kg.min)-1), 2km row time (07:00±00:21 mm:ss), 1-Repetition maximum in power clean (125.2±21.2 kg) and Tibana test performance (281.0±35.9 repetitions). Interestingly, the top five athletes with the highest scores also achieved the highest z-scores in the CrossFit® Open 2021. Conversely, the four athletes with the lowest TSA score had the lowest z-scores in the CrossFit® Open. Moreover, almost perfect correlation (r=0.91; p<0.01) was found between the total athlet- icism score and z-scores in the CrossFit® Open 2021. The total score may be a single measure and holistic indication of athleticism level in CrossFit®. Furthermore, coaches can potentially apply this useful tool for monitoring athletic performance and designing training sessions that ad- dress specific areas of CrossFit® performance. Key Words: high-intensity functional training; performance prediction; athleticism.. Eur J Transl Myol 34 (3) 12309, 2024 doi: 10.4081/ejtm.2024.12309 Exploring the relationship between Total Athleticism score and CrossFit® Open Performance in amateur athletes: single measure involving body fat percentage, aerobic capacity, muscle power and local muscle endurance Ramires Alsamir Tibana,1 Fábio Hech Dominski,2 Alexandro Andrade,2 Nuno Manuel Frade de Sousa,3 Fabricio Azevedo Voltarelli,1 Ivo Vieira de Sousa Neto4 1Graduate Program in Health Sciences, Faculty of Medicine, Federal University of Mato Grosso (UFMT), Cuiabá, Brazil; 2Laboratory of Sport and Exercise Psychology, Human Movement Sciences Graduate Program, College of Health and Sport Science of the Santa Catarina State University (UDESC), Florianópolis, Brazil; 3Research Unit for Sport and Physical Activity, Faculty of Sport Sciences and Physical Education, University of Coimbra, Portugal; 4School of Physical Education and Sport of Ribeirão Preto, University of São Paulo (USP), Ribeirão Preto, São Paulo, Brazil. This article is distributed under the terms of the Creative Commons Attribution Noncommercial License (CC BY-NC 4.0) which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited. - 97 - Non -co mmerc ial us e o nly Total Athleticism score and CrossFit® Open Performance in amateur athletes Eur J Transl Myol 34 (3) 12309, 2024 doi: 10.4081/ejtm.2024.12309 considered one of the largest sports events in the world.6 People at least 14 years old and with different levels of physical fitness could participate worldwide. There has been an increase in participation in the CrossFit® Open in the last five years: there were 239,106 participants in 2020, 263,529 in 2021, 294,980 in 2022, 302,240 in 20237 and 343,528 athletes in 2024. In 2021, only the top 10% of athletes advanced for the next stage of the competition (quarterfinals), and then number of athletes who advanced to the semifinals and finally the CrossFit® Games are de- pendent of the region. Despite the rising popularity of CrossFit® and some recent studies have endeavored to as- sess performance predictors and characteristics in both the open and CrossFit benchmark workouts,8-10 there is a lack of literature regarding the useful and measures that eval- uated global athletic performance in functional fitness training modality. In contrast to many conventional sports, classifying and determining the factors associated with success in Cross- Fit® open can be challenging due to its wide-ranging de- mands. CrossFit® open workouts exhibit a significant characteristic: they can vary greatly in terms of intensity, duration, skills required, and physiological demands.11 Some authors have found a relationship between markers of muscle strength,6, 11, 12 maximal aerobic capacity,13 body composition,11 and local muscle endurance6 with perform- ance in the CrossFit® Open. However, the degree of cor- relation appears to vary depending on the specific type of workout being analyzed. Consequently, certain workouts seem to exhibit a correlation with metrics related to aero- bic fitness, while others demonstrate a stronger association with measures of power and muscle strength. In accordance with Turner et al.,14 the Total Athleticism Score (TSA) is a comprehensive assessment that comprises various physical performance feats considered crucial for success in a specific sport. It employs standardized scores, such as z-scores and t-scores, derived from a series of test- ing batteries. This approach enables practitioners to gain in- sights into individual athletes’ performance within the context of their partners,15 besides to establishing a ranking for the team. Consequently, a benefit arises when the coach furnishes a consolidated score for the athlete’s physical fit- ness instead of dissecting each test result separately. This method can facilitate an efficient communication between coaches and athletes, optimizing the monitoring of athletic performance declines or evolutions.16 This assessment serves as a valuable tool to better understand and enhance athletes’ capabilities in their respective sports15 and different activities have their own specific criteria for assessing ath- leticism15 However, in CrossFit® there is no numerical score for athleticism; instead, coaches evaluate athletes based on a combination of skills, including local muscle endurance, speed, strength, power, and endurance. The unknown demands of the workouts, the varying nature of the past competitions, and the restricted opportunity for athletes to gain specific competition experiences.6 In con- trast to other individual or team sports, scores that deter- mined athleticism in CrossFit® are not yet known. To the best of our knowledge, no prior study investigated the TSA with CrossFit® performance in the context of actual com- petitions, rather than the standardized Workouts Of the Day (WODs) that athletes have been previously exposed. There- fore, the investigation represents a pioneering effort to ex- amine the correlation between anthropometric measures, cardiorespiratory capacity, power, local muscle endurance, and total athleticism score, with performance in the Cross- Fit® Open 2021. We hypothesize that athletes with the high- est TSA score achieved the highest z-scores in the CrossFit®, indicating that this single assessment can be helpful for screening the athletic performance. Materials and Methods Participants In total, 14 male volunteers with an average age of 30.3±5.8 years were recruited. Participants recruited for the study had been actively participating in CrossFit® training sessions more than four times per week, and they were recruited through personal contact. All subjects were free of injury or known illnesses, were not using perform- ance enhancing drugs, had at least 2 years of experience practicing with CrossFit®, and were familiar with the tests analyzed. Participants were advised to sleep six to eight hours the night before the tests, maintain regular nu- tritional and hydration habits, avoid intense exercise 48 h prior to the sessions, and avoid smoking, alcohol, and caf- feine consumption 24 h before. All subjects provided in- formed consent and the study was approved by the University Research Ethics Committee for Human Use (2.698.225/Universidade Estácio de Sá/UNESA/RJ and ethics ID Pro00110581) and conformed to the principles of the Helsinki Declaration on the use of human partici- pants for research. Experimental design The present study followed a cross-sectional design. All participants performed the baseline assessments two weeks prior to the CrossFit® Open 2021 (five workouts for 5 weeks) (February–March 2021). Figure 1 shows schematic illustration of the methodological steps in the present study. Anthropometric and body fat measurements Anthropometric measurements were conducted in the morning, with the subjects wearing light clothing and no shoes. The participants’ weight was recorded using a Fili- zola® digital scale (Curitiba, PR, Brazil), with a capacity of 180 kg and precision to the nearest 0.1 kg. Standard methods recommended by the International Society for the Advancement of Kinanthropometry 17 were employed for each subject’s measurements. Body composition was assessed via skinfold technique (Lange® caliper, Cam- bridge Scientific Industries, Inc, Cambridge, MD). Subcu- taneous adipose thickness was measured at seven sites (subscapular, chest, axilla, triceps, suprailiac, abdominal, and thigh) on the right side of the body. Once the fat thick- nesses were recorded for each of the seven sites, body den- sity was estimated using the Jackson-Pollock18 generalized skinfold equation and percent body fat was estimated using the Siri equation.19 - 98 - Non -co mmerc ial us e o nly Total Athleticism score and CrossFit® Open Performance in amateur athletes Eur J Transl Myol 34 (3) 12309, 2024 doi: 10.4081/ejtm.2024.12309 Maximal oxygen consumption Indirect maximal aerobic capacity (VO2 max) was as- sessed via a maximal 2-km rowing test.20 For all exercise tests, a consistent rowing ergometer (model E; Concept 2, Morrisville, VT, USA) was utilized. Each subject individ- ually adjusted their preferred stroke rate and drag factor during both the tests and the warm-up protocol. The stan- dardized warm-up for the 2 km time trial consisted of the following: i) 4 minutes of easy rowing; ii) 4 sets of 1-mi- nute rowing intervals with increasing intensity, including 10 hard strokes, 15 hard strokes, 20 hard strokes, and 10 hard strokes for each respective minute; iii) 2 minutes of easy rowing for recovery. After a short rest the 2 km all-out time trial was performed. During this trial, participants exerted maximal effort to complete the 2 km distance. Local muscle endurance The Tibana test was applied to assess local muscle endur- ance. The section is characterized by metabolic condition- ing demand and involves habitual functional fitness training exercises. The athletes were instructed to complete the max- imum number of repetitions possible for each round.21 Spe- cifically, this test consisted of four distinct rounds of work, each separated by 2 minutes of rest.6 The rounds were struc- tured as follows: Round 1: Participants performed 4 mi- nutes of As Many Rounds As Possible (AMRAP) of five thrusters (60 kg for men and 43 kg for women) and 10 box jumps; Round 2: Participants performed 4 minutes of AMRAP of 10 power cleans (60 kg for men and 43 kg for women) and 20 pull-ups; Round 3: Participants performed 4 minutes of AMRAP of 15 shoulder to overhead lifts (60 kg for men and 43 kg for women) and 30 toes to bar; Round 4: Participants performed 4 minutes of AMRAP of 20 cal- ories of rowing and 40 wall balls (9 kg for men and 6 kg for women). CrossFit® Open 2021 The specific details of the five workouts used in this study, known as 21.1, 21.2, 21.3, and 21.4, are briefly explained below: i) 21.1: Participants had 15 min to complete 1 wall walk, 10 double-unders, 3 wall walks, 30 double-unders, 6 wall walks, 60 double-unders, 9 wall walks, 90 double- unders, 15 wall walks, 150 double-unders, 21 wall walks, and 210 double-unders; ii) 21.2: Participants had 15 min to complete 10 dumbbell snatches (22.5 kg), 15 burpee box jump-overs (60 cm), 20 dumbbell snatches, 15 burpee box jump-overs, 30 dumbbell snatches, 15 burpee box jump-overs, 40 dumbbell snatches, 15 burpee box jump- overs, 50 dumbbell snatches, and 15 burpee box jump- overs; iii) 21.3: Participants had 15 min to complete 15 front squats (45 kg), 30 toes-to-bars, 15 thrusters. Then, rest 1 minute before continuing with: 15 front squats, 30 chest-to-bar pull-ups, 15 thrusters. Then, rest 1 minute be- fore continuing with: 15 front squats, 30 bar muscle-ups, and 15 thrusters; iv) 21.4: Participants had 7 min to com- plete the following complex for maximal load: 1 deadlift, 1 clean, 1 hang clean, and 1 jerk. Total score of athleticism and z-score during the CrossFit® Open 2021 The total score of athleticism is derived by averaging a set of standardized scores (z-scores) from a series of tests un- dertaken by an athlete.14, 22 A standardized score (of a single test or measure), and therefore the TSA (of a series of tests), allows coaches to examine contextualized data of individual athletes relative to their teammates and thus set benchmarks and training goals that are realistic to the demands placed on players by the club.14 In this study, the TSA was derived by averaging the z-scores of four tests or measures: percentage of body fat, time of 2 km row, power clean weight and Tibana test. To calculate the z-score for each test, the squad’s average test score - 99 - Figure 1. Description of study timeline. Non -co mmerc ial us e o nly Total Athleticism score and CrossFit® Open Performance in amateur athletes Eur J Transl Myol 34 (3) 12309, 2024 doi: 10.4081/ejtm.2024.12309 (n=14) is subtracted from the athlete’s test score, then this value is divided by the squad’s standard deviation (SD). Thus, the equation reads as follows: z-score=(athlete score – team mean)/team SD. The score of 2 km row test and body fat were multiplied by -1 to ensure positive z-scores for the best results. Finally, the TSA was calculated by aver- aging all z-scores (body fat z-score, 2 km row z-score, power clean z-score and Tibana test z-score). A z-score of the CrossFit® Open 2021 was also calculated using the same methodology as the TSA to rank the results of the athletes. Z-score of the CrossFit Open 2021 was calculate by aver- aging the z-cores of the 2021.1, 2021.2, 2021.3 and 2021.4 benchmarks. Statistical analysis The data are expressed as mean value±standard deviation (SD). Shapiro–Wilk test was used to check for parametric distribution of study variables. Simple Pearson’s r correla- tions were used to determine the associations between the results of CrossFit® Open 2021 and the athletic performance measures. The magnitude of the correlations was classified as: r ≤0.1 trivial; 0.1 0.9 almost per- fect.23 The power (1-ß) of the Pearson r coefficient of cor- relation was calculated afterward (post hoc) using the sam- ple size of this research (n=14), an alpha equal to 0.05 and the r coefficient effect size for each correlation. Calculation of values was performed using G*Power Software (version 3.0.10, Germany) and we detected values above 80% for most correlations (exact values for each correlation pre- sented in the results section). The level of significance was p ≤0.05 and SPSS version 20.0 (Somers, NY, USA) soft- ware was used. Results Anthropometric and performance data presentation The anthropometric profile, cardiorespiratory, and muscle strength values are reported in Table 1. As expected, the athletes have a low body fat percentage (8.6±2.0%) and proper performance metrics (aerobic capacity, muscle power and endurance). Table 2 reports the repetition values obtained in Open 2021.1, as well as the time performed in Open 2021.2 and Open 2021.3. Finally, the load (kg) per- formed Open 2021.4 is reported. Athlete values of the total score of athleticism Figure 2 displays the radar chart plot with a series of values - 100 - Table 1. Anthropometric and performance measurements of the athletes (mean±SD). n=14 Body weight, kg 84.2±6.2 Body fat, % 8.6±2.0 Maximal oxygen consumption, L.min-1 4.49±0.44 Maximal oxygen consumption, mL.(kg.min)-1 53.3±2.4 2 km row, time (mm:ss) 07:00±00:21 Power clean, kg 125.2±21.2 Tibana test, repetitions 281.0±35.9 Table 2. CrossFit® Open 2021 results. n=14 Open 2021.1, repetitions 407.3±58.4 Open 2021.2, time (mm:ss) 13:55±02:10 Open 2021.3, time (mm:ss) 12:25±02:05 Open 2021.4, kg 113.1±19.1 Non -co mmerc ial us e o nly Total Athleticism score and CrossFit® Open Performance in amateur athletes Eur J Transl Myol 34 (3) 12309, 2024 doi: 10.4081/ejtm.2024.12309 over multiple quantitative variables on axes starting from the same point. It is equivalent to a parallel coordinates plot, with the axes arranged radially, indicating t-scores of athlete as part of squad fitness testing. Dark colors represent higher values (green), while light colors represent lower values (red). Figure 3 shows each athlete’s TSA score (expressing as a z-score; Figure 1A) and the z-score achieved during the four workouts of the CrossFit® Open 2021. The five ath- letes with the highest TSA score were the five athletes with the highest z-score of the CrossFit® Open 2021(Figure 3A). On the other hand, the four athletes with the lowest TSA score were the four athletes with the lowest z-score of the CrossFit® Open (Figure 3B). Relationship between total athleticism score and CrossFit® Open performance There was no statistically significant correlation between body fat percentage, CrossFit® Open performance and z- score (p>0.05). However, 2 km row test, VO2 max, Power Clean, Tibana test and TSA had relationship with z-score in the CrossFit® Open 2021 (p<0.01). The specific r and p- values are shown in Table 3. Discussion The aim of this study was to examine the correlation be- tween anthropometric measures, cardiorespiratory capacity, power, local muscle endurance, and total athleticism score, with performance in the CrossFit® Open 2021. First, we ob- served that muscle strength and endurance had a strong re- lationship with CrossFit® Open 2021 performance. Confirming our initial hypothesis, the findings indicated that the top five athletes with the highest TSA score also achieved the highest z-scores in the CrossFit® Open 2021, and the four athletes with the lowest TSA score had the lo- west z-scores in the CrossFit Open. Moreover, almost per- fect correlation (r=0.91) was found between TSA score and z-scores in the CrossFit® Open 2021, suggesting that the change in value of one variable is exactly proportional to the change in value of the other. Thus, the total athleticism score may be a single measure and holistic indication of athleticism level in CrossFit®. The Figure 4 clarifies of the concept, main outcomes, and practical applications of TSA score in CrossFit® context. It has been reported that that when CrossFit® Open work- outs consist of multiple rounds, competitors should employ a fast and sustainable pace to improve performance.24 Fur- thermore, previous investigations found an association be- tween muscle strength,6, 11, 12 aerobic capacity,13, 25 body composition,11 and local muscle endurance6 with perform- ance in specific competitions. Nevertheless, the relationship between fitness measures and performance differs dramat- ically according to exercises that predominate in WOD, sug- gesting that isolated tests may not reflect the athletic profile. - 101 - Figure 2. The Total Score of Athleticism was derived by averaging the z-scores of four tests or measures: percent- age of body fat, time of 2 km row, power clean weight and Tibana test. To calculate the z-score for each test, the squad’s average test score (n=14) is subtracted from the athlete’s test score, then this value is divided by the squad’s standard deviation (SD); so, the equation reads as follows: z-score=(athlete score – team mean)/team SD. Figure 3. Plotting each athlete’s total score of athleticism (TSA) score (A) with the z-score of the CrossFit® Open 2021 (B). The TSA and the z-score have been ranked from highest to lowest. Non -co mmerc ial us e o nly Total Athleticism score and CrossFit® Open Performance in amateur athletes Eur J Transl Myol 34 (3) 12309, 2024 doi: 10.4081/ejtm.2024.12309 Considering that real-world sporting practice contemplates the different physical demands, athletic endeavors, and fit- ness components, a practical method that provides a single score of holistic fitness is required. Thus, TSA approach can help with planning and ranking, especially when there is team competition. It is significant to highlight that z-score fluctuations are in- fluenced by team mean or individual changes. Therefore, the values may not be directly transferable to all athlete levels. Furthermore, is recommended that coaches ration- alize the fitness tests utilized in TSA, since the strengths and performance weaknesses of each athlete can be differ- ent. Future studies that instigate different test battery, com- petitions, and athlete levels are required, to elucidate the TSA validity involved in the distinct contexts. Sports performance requires effective communication and interdivisional planning for the athlete. According to Turner et al.,14 the TSA scores is an easy way to compile a clean number to label athletes against one another.15 The histo- grams layouts may provide a logical and easy method to understand the ranking data, but not an end-all-be-all report. Adding other metric combinations that help explain multi- ple abilities in CrossFit®, the TSA report will become more robust in enhancing decision- making. Concerning practical applications, coaches can utilize the TSA rather than separately each individual test perform- ance, since the scores allow for the examination of individ- ual contextualized data relative to other athletes. As a result, there is an advantage when the coach provides a unified score for the athlete’s physical fitness rather than analyzing each test result independently. This approach can enhance communication efficiency between coaches and athletes, optimizing the tracking of changes or advancements in ath- letic performance. Hence, the TSA can be valuable for mon- itoring athlete development over time and longitudinally. Additionally, TSA can be useful in identifying possible de- ficient athletic performance, as well as designing realistic strategies in a particular competition. For example, the four athletes with the lowest TSA score in current study could have benefited from targeted multicomponent training, with a particular focus on restoring a several skills (muscle strength, cardiovascular, and local muscle endurance). - 102 - Table 3. Correlations between CrossFit® Open 2021 benchmarks and the body fat and performance measures (n=14). 2021.1 2021.2 2021.3 2021.4 z-score Body fat, % r (p-value) -0.27 (0.36) 0.41 (0.15) 0.42 (0.14) -0.25 (0.40) -0.40 (0.16) Power (1-ß) 0.14 0.30 0.31 0.13 0.29 2 km row, time r (p-value) -0.55 (0.04)* 0.76 (<0.01)** 0.78 (<0.01)** -0.75 (<0.01)** -0.85 (<0.01)** Power (1-ß) 0.55 0.96 0.98 0.95 1.00 VO2 max, L.min-1 r (p-value) 0.31 (0.27) -0.73 (<0.01)** -0.71 (0.01)** 0.71 (<0.01)** 0.73 (<0.01)** Power (1-ß) 0.18 0.92 0.89 0.89 0.92 VO2 max, mL.(kg.min)-1 r (p-value) 0.08 (0.78) -0.37 (0.19) -0.19 (0.51) 0.14 (0.62) 0.24 (0.42) Power (1-ß) 0.04 0.25 0.09 0.07 0.12 Power Clean, kg r (p-value) 0.25 (0.39) -0.63 (0.02)* -0.88 (<0.01)** 0.94 (0.01)*** 0.81 (<0.01)** Power (1-ß) 0.13 0.73 1.00 1.00 0.99 Tibana test, repetitions r (p-value) 0.62 (0.02)* -0.87 (<0.01)** -0.87 (<0.01)** 0.77 (0.01)** 0.94 (0.01)*** Power (1-ß) 0.71 1.00 1.00 0.97 1.00 TSA r (p-value) 0.51 (0.06) -0.81 (<0.01)** -0.90 (<0.01)*** 0.82 (<0.01)** 0.91; (<0.01)*** Power (1-ß) 0.47 0.99 1.00 1.00 1.00 VO2 max, maximal oxygen consumption; TSA, total score of athleticism; *large correlation; **very large correlation; ***almost perfect correlation. Non -co mmerc ial us e o nly Total Athleticism score and CrossFit® Open Performance in amateur athletes Eur J Transl Myol 34 (3) 12309, 2024 doi: 10.4081/ejtm.2024.12309 Therefore, the TSA screening might offer well-organized information for a guide training program, besides establish- ing the distribution of the training session based on the de- mands that athletes will be exposed to different WODs. Despite the transformation into a worldwide public sporting event, few studies were carried out on the appropriate pre- dictor parameters that have a significant impact on Cross- Fit® performance. In the CrossFit® Games, the WODs are declared shortly before or even during the competition.26 Consequently, the athletes are unable to prepare precisely for a particular performance. In this way, athletes should achieve full fitness to optimally cope with any conceivable challenge, including unknown physical demands. Hence, the continuous variation of the training program can be im- portant, which reinforces the real importance of employ- ment of the TSA score. It is important to acknowledge certain limitations in our in- vestigation. First, the regional athletes, amateur level and relatively small sample size may limit the generalizability of our findings. Second, the specific competition analyzed does not contain all powerlifting, weightlifting, and gym- nastics exercises, which may not be directly transferable to other competitions with different WODs. Lastly, the cross- sectional design avoids the ability to detect causal relation- ship between variables. Conclusions In summary, athletes with the highest TSA score achieved the highest z-scores in the CrossFit® Open 2021. Further- more, a strong correlation was found between TSA score and z-scores in the CrossFit® Open 2021, suggesting that this assessment can be helpful in screening the performance predictors in a particular competition. The findings of this investigation may be of interest to coaches working with CrossFit® athletes who aim to maximize their success by evaluating their physical fitness and designing training ses- sions that address their specific areas of improvement per- formance. List of acronyms AMRAP: as many rounds as possible. Kg: Kilogram. mL: Milliliter. - 103 - Figure 4. Schematic description of the concept, main outcomes and practical applications of total score of athleticism (TSA) score in CrossFit® context. Non -co mmerc ial us e o nly Total Athleticism score and CrossFit® Open Performance in amateur athletes Eur J Transl Myol 34 (3) 12309, 2024 doi: 10.4081/ejtm.2024.12309 SD: Standard Deviation. TSA: Total Athleticism Score. VO2 max: Maximal oxygen consumption. WODs: Workouts of the Day. Contributions All authors equally participated in developing this study and in writing the typescript. All authors read and approved the final edited typescript. Conflict of interest The authors declare they have no financial, personal, or other conflicts of interest. Ethics approval The Ethics Committee of Institution approved this study (2.698.225/Universidade Estácio de Sá/UNESA/RJ and ethics ID Pro00110581). The study is conformed with the Helsinki Declaration of 1964, as revised in 2013, concern- ing human and animal rights. Informed consent All patients participating in this study signed a written in- formed consent form for participating in this study. Patient consent for publication Written informed consent was obtained from a legally au- thorized representative(s) for anonymized patient infor- mation to be published in this article. Availability of data and materials All data generated or analyzed during this study are in- cluded in this published article. Funding This research received no external funding. Corresponding Author Ramires Alsamir Tibana Federal University of Mato Grosso (UFMT), Cuiabá, Brazil. Avenida Fernando Correa da Costa, 2367, Boa Esperança, Zip code 78060900. ORCID ID: 0000-0003-2395-4416 E-mail: ramirestibana@gmail.com Fábio Hech Dominski ORCID ID: 0000-0003-1767-6405 E-mail: fabiohdominski@hotmail.com Alexandro Andrade ORCID ID: 0000-0002-6640-9314 E-mail: alexandro.andrade.phd@gmail.com Nuno Manuel Frade de Sousa ORCID ID: 0000-0001-5854-616X E-mail: nunosfrade@gmail.com Fabricio Azevedo Voltarelli ORCID ID: 0000-0002-8077-8941 E-mail: voltarellifa@gmail.com Ivo Vieira de Sousa Neto ORCID ID: 0000-0002-1479-5866 E-mail: ivoneto04@hotmail.com References 1. Dominski FH, Tibana RA, Andrade A. "Functional Fit- ness Training", CrossFit, HIMT, or HIFT: What Is the Preferable Terminology? Front Sports Act Living 2022;4:882195. 2. Tibana RA, de Sousa Neto IV, de Sousa NMF, et al. Time-course effects of functional fitness sessions per- formed at different intensities on the metabolic, hor- monal, and BDNF responses in trained men. BMC Sports Sci Med Rehabil 2022;14:22. 3. 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