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The purpose was to create a systematic approach for analyzing data to improve predictive models for fatigue and neuromuscular performance in volleyball, with potential applications in other sports. The study aimed to assess whether average, peak, or peak-to-average ratios of countermovement jump (CMJ) force plate metrics exhibit stronger correlations and determine which metric most effectively predicts performance. Data were obtained from nine division I female volleyball athletes over a season, recording daily jump loads (total jumps, jump counts >38.1 cm (Jumps 38+), and >50.8 cm (Jumps 50+) in height) and comparing these with CMJ force metrics recorded the next day, both average and peak. Correlations and regressions were utilized to assess the relationship and predictive value for jump loads on CMJ test data. The findings revealed that the most significant (p < 0.001 for all) negative correlations (r ranged from −0.384 to −0.529) occurred between Jumps 50+ and the average CMJ test variables. Furthermore, there were no significant relationships between jump loads and peak-to-average ratios (p ≥ 0.233). Average CMJ force metrics and Jumps 50+ provide slightly more predictive (up to 28% of variability) potential for fatigue modeling of neuromuscular performance.

BackgroundIt is common practice for fight sport athletes to use a variety of weight manipulation strategies to compete in desired weight classes. Although numerous studies have highlighted rapid weight loss (RWL) strategies and the magnitude of weight loss, few have focused specifically on weight loss in female fighters. The purpose of this study was to provide descriptive information on professional UFC female fighters engaging in RWL in all women’s UFC weight divisions: strawweight (52.2 kg): flyweight (56.7 kg); bantamweight (61.2 kg); featherweight (65.8 kg).MethodsAll fighter’s weights were obtained at five separate time points: 72 hrs. pre-weigh-in, 48 hrs. pre-weigh-in, 24hrs. pre-weigh-in, official weigh-in, and 24 hrs. post-weigh-in (competition weight). Mixed effects models and random effects analysis were used to assess changes in weight and differences between weight divisions. All statistics were analyzed, and significance was set at p ≤0.05. Significant changes in weight between all time points were reported.ResultsNo statistical differences between weight divisions were observed. Female fighters lost 4.5–6.6% of their weight prior to the official weigh-in.ConclusionFemales engaged in RWL practices lose weight in a similar fashion irrespective of weight class.

Following an extensive literature review, the International Society of Sports Nutrition (ISSN) has developed an official position on nutritional and weight cut strategies for combat sports. The type of combat sport, length of the fight camp, and time between weigh-in and competition are factors influencing nutritional and weight cut strategies. The following 16 points constitute the Position Statement of the Society; the Research Committee has approved them. 1. Combat sports have differing weight categories, official weigh-in times, and competition frequencies, influencing the nutritional and weight cut strategies for training and competition. 2. As the duration of a combat match increases, >4 min, contribution of the aerobic system can rise to >70%, yet anaerobic alactic pathways and anaerobic glycolytic pathways support high-output bursts. 3. During the off camp/general preparation phase, athletes should maintain a weight ranging 12% to 15% above the weight division requirement. 4. Supplements including creatine, beta-alanine, beta-hydroxy-beta-methylbutyrate, and caffeine have been shown to enhance performance and/or recovery during preparation phases, competition, and post-competition. 5. During fight camp, strategic decreases in calorie intake are necessary for an efficient longitudinal weight descent. Individual caloric needs can be determined using indirect calorimetry or validated equations such as Mifflin St. Jeor or Cunningham. 6. Protein should be prioritized during longitudinal weight descents to preserve lean body mass, and the timely delivery of carbohydrates supports training demands. Macronutrients should not drop below the following: carbohydrates 3.0-4.0 g/kg, protein 1.2-2.0 g/kg, and fat 0.5 to 1.0 g/kg/day. 7. Suitable losses in body mass range from 6.7% at 72 h, 5.7% at 48 h, and 4.4% at 24 h, prior to weigh-in. 8. Sodium restriction and water loading are effective for inducing polyuria and acute water loss. 9. During fight week, water-bound glycogen stores can be depleted through exercise and carbohydrate restriction, facilitating a 1% to 2% loss in body mass, with equivalent losses from a low-fiber intake of <10 g/day for 4 days. 10. During fight week, acute water loss strategies, including sauna, hot water immersion, and mummy wraps, can be used effectively with appropriate supervision (optimally ~2-4% of body mass within 24 h of weigh-in). 11. Post-weigh-in, rapid weight gain strategies are utilized to recover lost body fluid/mass before competition with the intent of gaining a competitive advantage. 12. Oral rehydration solutions (1 to 1.5 liters/h) combined with a sodium range of 50-90 mmol/dL should take precedence immediately post-weigh-in. 13. Fast-acting carbohydrates at a tolerable rate of ≤ 60 g/h should follow oral rehydration solutions. Post weigh-in intake of fiber should be limited to avoid gastrointestinal distress. 14. Post-weigh-in carbohydrate intake at 8-12 g/kg may be appropriate for combat athletes that undertook significant glycogen depletion strategies during fight week. About 4-7 g/kg may be suitable for modest carbohydrate restriction. 15. Post weigh-in, rehydration/refueling protocols should aim to regain ≥10% of body mass to mitigate declines in performance and the negative effects of rapid weight loss. 16. The long-term effects of frequent weight cuts on health and performance are unknown, necessitating further research.

Background: Mixed martial arts (MMA) requires athletes to generate repeated bursts of high-intensity effort with minimal recovery time. Despite the sport’s reliance on anaerobic power, there are minimal data assessing pre-competition physiological capacity in MMA fighters. This study aimed to evaluate anaerobic performance using the Wingate Anaerobic Test (WAnT) and Countermovement Jump (CMJ) in professional MMA athletes, and to examine relationships between performance metrics across weight classes. Methods: Twelve professional male MMA fighters (age 29.00 ± 4.80 years, weight 85.60 ± 13.90 kg) completed both CMJ and WAnT assessments using sensor-integrated devices (Just Jump mat and Wattbike Pro). CMJ height and WAnT variables (peak power, average power, and fatigue index) were measured. Pearson correlations were used to examine the relationships between CMJ and Wingate outputs. Independent t-tests compared performance between lighter (<83.9 kg) and heavier (≥83.9 kg) weight groups. Results: CMJ performance showed significant positive correlations with both average power (r = 0.71, p < 0.001) and peak power (r = 0.61, p = 0.004). Peak power was also positively correlated with fatigue index (r = 0.84, p < 0.001), suggesting greater fatigue in higher power-producing athletes. Finally, the heavier weight group of fighters produced significantly (p = 0.03) more peak power when compared to the lighter weight group. Conclusions: The findings support the use of CMJ and WAnT testing as practical tools for evaluating anaerobic performance in MMA athletes. These assessments can help guide individualized training strategies, particularly when accounting for weight group specific differences in power and fatigue dynamics.

The purpose of this investigation was to determine the effects of a high protein diet over a one-year period. Fourteen healthy resistance-trained men completed the study (mean ± SD; age 26.3±3.9 yr; height 178.5±8.4 cm; and average years of training 8.9±3.4 yr). In a randomized crossover design, subjects consumed their habitual or normal diet for 2 months and 4 months and alternated that with a higher protein diet (>3 g/kg/d) for 2 months and 4 months. Thus, on average, each subject was on their normal diet for 6 months and a higher protein diet for 6 months. Body composition was assessed via the Bod Pod®. Each subject provided approximately 100–168 daily dietary self-reports. During the subjects’ normal eating phase, they consumed (mean ± SD) 29.94±5.65 kcals/kg/day and 2.51±0.69 g/kg/day of protein. This significantly increased (p<0.05) during the high protein phase to 34.37±5.88 kcals/kg/day and 3.32±0.87 g/kg/day of protein. Our investigation discovered that, in resistance-trained men that consumed a high protein diet (~2.51–3.32 g/kg/d) for one year, there were no harmful effects on measures of blood lipids as well as liver and kidney function. In addition, despite the total increase in energy intake during the high protein phase, subjects did not experience an increase in fat mass.

Previous research has demonstrated that professional mixed martial arts (MMA) athletes employ a variety of weight manipulation strategies to compete at given weight classes. Although there is much literature demonstrating weight manipulation methods, minimal research exists analyzing how much weight MMA athletes lose prior to the official weigh-in. Moreover, there is minimal research examining how much weight professional MMA athletes gain between the official weigh-in and competition. Therefore, the purpose of the current study was to analyze weight loss/regain in professional MMA athletes. Data collected from 616 professional MMA athletes (31.1 ± 4.0 yrs.; 177.1 ± 4.7 cm) competing for the Ultimate Fighting Championship (UFC) between 2020 and 2022 were used for the study. The athlete’s weight was obtained 72 h, 48 h, and 24 h prior to the official weigh-in, at the official weigh-in, and prior to competition. Random effects analysis was utilized to compare weight at a variety of time points between different weight classes. All statistics were analyzed, and significance was set at p ≤ 0.05. There is a significant (p ≤ 0.05) difference between weight classes and time points in professional MMA. MMA athletes decrease body weight significantly prior to the official weigh-in. MMA athletes increase body weight significantly between official weigh-in and competition. Based on these data, it appears that MMA athletes average a weight loss of nearly 7% within 72 h prior to the official weigh-in. The data also suggest that athletes gain nearly 10% of total weight between the official weigh-in and competition.

Background Variations in the fat mass and obesity-associated gene (FTO) are associated with obesity; however, it is unclear if changes in energy intake affect the adaptive response to caloric restriction in those with risk variants. The three FTO single nucleotide polymorphisms (SNPs), rs1421085, rs17817449 and rs9939609, are in strong linkage disequilibrium. Thus, the purpose of this investigation was to determine the role of these FTO SNPs vis-à-vis the effects of a 4-week hypocaloric diet on body composition in exercise-trained men and women. Two salivary biomarkers that associate with energy expenditure were also assessed (cortisol and salivary alpha-amylase, sAA). Methods Forty-seven exercise-trained men ( n  = 11) and women ( n  = 36) (mean ± SD: age 32 ± 9 years; height 169 ± 8 cm, body mass index 24.5 ± 2.9 kg/m 2 , hours of aerobic training per week 4.9 ± 3.8, hours of weight training per week 3.9 ± 2.4, years of training experience 13.4 ± 7.0) completed a 4-week hypocaloric diet (i.e., decrease total calories by ~ 20–25% while maintaining a protein intake of ~ 2.0 g/kg/d). Subjects were instructed to maintain the same training regimen and to decrease energy intake via carbohydrate and/or fat restriction during the treatment period. Body composition was assessed via dual-energy X-ray absorptiometry (DXA) (Model: Hologic Horizon W; Hologic Inc., Danbury CT USA). Total body water was determined via a multifrequency bioelectrical impedance (BIA) device (InBody 770). Saliva samples were collected pre and post intervention in order to genotype the participants as well as to determine the concentrations of cortisol and sAA. Results Of the 47 subjects, 15 were of normal risk for obesity whereas 32 were carriers of the FTO gene risk alleles. Subjects were grouped based on their genotype for the three FTO SNPs (i.e., rs1421085, rs17817449 and rs9939609) due to their strong linkage disequilibrium. We have classified those with the normal obesity risk as “non-risk allele” versus those that carry the “risk allele” (i.e., both heterozygous and homozygous). Both groups experienced a significant decrease in total energy intake ( p  < 0.01); non-risk allele: pre kcal 2081 ± 618, post kcal 1703 ± 495; risk allele: pre kcal 1886 ± 515, post kcal 1502 ± 366). Both groups lost a significant amount of body weight ( p  < 0.01); however, there was no difference between groups for the change (post minus pre) in each group (risk allele change: − 1.0 ± 1.2 kg, non-risk allele change: − 1.2 ± 1.4 kg). Additionally, both groups lost a significant amount of fat mass ( p  < 0.01) with no differences between groups for the change in fat mass (risk allele change for fat mass: 1.1 ± 0.7 kg, non-risk allele change − 0.9 ± 0.4 kg). There were no significant changes in either group for fat free mass or total body water. The change in salivary alpha-amylase or cortisol was not different between groups. Conclusions In the short-term (i.e., 4 weeks), exercise-trained men and women consuming a hypocaloric diet that is relatively high in protein experience similar changes in body composition due exclusively to a decrement in fat mass and independent of FTO allele status. Therefore, weight and fat loss on a hypocaloric diet is, at least in the short-term, unaffected by the FTO gene.

Background It has been posited that the consumption of extra protein (> 0.8 g/kg/d) may be deleterious to bone mineral content. However, there is no direct evidence to show that consuming a high-protein diet results in a demineralization of the skeleton. Thus, the primary endpoint of this randomized controlled trial was to determine if a high-protein diet affected various parameters of whole body and lumbar bone mineral content in exercise-trained women. Methods Twenty-four women volunteered for this 6-month investigation ( n  = 12 control, n = 12 high-protein). The control group was instructed to consume their habitual diet; however, the high-protein group was instructed to consume ≥2.2 g of protein per kilogram body weight daily (g/kg/d). Body composition was assessed via dual-energy x-ray absorptiometry (DXA). Subjects were instructed to keep a food diary via the mobile app MyFitnessPal ® . Exercise or activity level was not controlled. Subjects were asked to maintain their current levels of exercise. Results During the 6-month treatment period, there was a significant difference in protein intake between the control and high-protein groups (mean±SD; control: 1.5±0.3, high-protein: 2.8±1.1 g/kg/d); however, there were no differences in the consumption total calories, carbohydrate or fat. Whole body bone mineral density did not change in the control (pre: 1.22±0.08, post: 1.22±0.09 g/cm 2 ) or high-protein group (pre: 1.25±0.11, post: 1.24±0.10 g/cm 2 ). Similarly, lumbar bone mineral density did not change in the control (pre: 1.08±0.16, post: 1.05±0.13 g/cm 2 ) or high-protein group (pre: 1.07±0.11, post: 1.08±0.12 g/cm 2 ). In addition, there were no changes in whole body or lumbar T-Scores in either group. Furthermore, there were no changes in fat mass or lean body mass. Conclusion Despite an 87% higher protein intake (high-protein versus control), 6 months of a high-protein diet had no effect on whole body bone mineral density, lumbar bone mineral density, T-scores, lean body mass or fat mass.

The purpose of this investigation is to present observational data regarding sleep variables in professional Mixed Martial Arts (MMA) athletes. These sleep performance measures were related to physical performance and injury in MMA athletes. Eight professional athletes were placed into a quasi-controlled, multivariable fight-camp environment for a six-week period in preparation for fight competition. Throughout a six-week fight camp environment, athletes were continuously monitored for sleep performance measures (sleep latency, sleep efficiency, onset, and wake variances) via validated wearable sleep monitoring technology. Athletes were tested seven days prior to competition on measures of physical performance (vertical jump, VO2max, heart rate recovery, prowler sled push, and pull-ups). Multiple correlational analyses were utilized to assess relationships between all sleep and physical performance measures. There were significant (P < 0.05) correlations between sleep latency and VO2max, heart rate recovery, prowler sled push, vertical jump, and missed practice sessions. There were also significant (P < 0.05) correlations between average fall asleep time and heart rate recovery. Lastly, there were significant (P < 0.05) correlations between sleep efficiency, heart rate recovery, and missed practice sessions. MMA athletes who exhibited consistency in sleep demonstrated stronger relationships with performance testing during the fight-camp period.

The purpose of the study was to assess glycogen content of the rectus femoris (RF) muscles utilizing high-frequency ultrasound throughout an intensive, nine-day preseason training period in NCAA division I volleyball athletes. In the morning prior to the beginning of practice, athletes (n = 13) left and right RF muscles were assessed via ultrasound to quantify muscle fuel ratings (0–100 score range). The recommended location of the RF ultrasound scans were based on manufacturer guidelines, and the same technician recorded the daily measurements. To assess daily training load, session ratings of perceived exertion (s-RPE) were utilized. A paired t-test revealed a large significant difference between left (51.7 ± 17.9) and right (32.8 ± 17.4) RF muscle fuel ratings (p < 0.001). There was also a major effect of time on s-RPE (p < 0.001) and left (dominant) RF fuel rating (p = 0.001). s-RPE decreased from the beginning to the end of the training camp. However, left RF fuel ratings increased from the first to the second day, then remained elevated all throughout the preseason. In conclusion, all athletes were left-leg dominant and had a 57.6% bilateral asymmetry between their left and right RF muscle fuel ratings despite changes in training load. High-frequency ultrasounds are a noninvasive assessment tool that can determine glycogen replenishment asymmetries in the RF.