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Recent concerns have been raised regarding the ethical considerations of conducting body composition assessments in sports. Specific apprehensions pertain to the inappropriate use of percent body fat and the limited application of the results to performance and recovery. Fat-free mass index (FFMI), a height-adjusted assessment of FFM, can serve as an alternative body composition metric to focus on in sports. Fat-free mass index provides valuable context regarding an optimal amount of FFM, accounting for skeletal frame and height while helping to qualify an athlete's FFM as low, moderate, or high. This review posits that shifting the focus of body composition measures to FFM can support more ideal targets across athletic seasons, careers, and the return to play after injury. In addition, a FFM focus may help change the perception of body composition assessment and how athletes perceive their current body because of the increased focus on the FFM compartment and the goal of maximizing tissue accrual, rather than focusing on fat loss. Fat-free mass index is calculated by dividing FFM (kg) by height (m²) and can serve to normalize FFM, relative to height, and enable comparisons across athletes, sport types, and sex. Previous research has identified differences in FFMI across sex and among sport categories. Still, there is a need for more published data to develop optimal ranges for FFMI across sex, sports, and positions. As more data become available, FFMI has the potential to provide normative guidelines for optimal FFM development, performance, and injury risk reduction. The purpose of the current review was to summarize FFMI values across collegiate sport categories and competitive status to provide normative profiles, according to sex and sport type. [ABSTRACT FROM AUTHOR]

To cross-validate bioelectrical impedance devices for the determination of body fat percentage (BF%) in firefighters. Twenty-eight structural firefighters were evaluated (female, n = 2; male, n = 26 [mean ± SD] age: 38.2 ± 8.3 years; height: 180.2 ± 7.5 cm; body mass: 86.7 ± 20.8 kg; body mass index: 25.8 ± 7.8 kg⋅m-2) using multifrequency bioelectrical impedance analysis (MFBIA) hand-to-foot device, and single- frequency BIA foot scale (F2FBIA), and a single-frequency handheld BIA device (HHBIA). Dual X-ray absorptiometry served as the criterion. Validity metrics were examined to establish each method's performance. Body fat % values produced by MFBIA (r = 0.913), F2FBIA (r = 0.695), and HHBIA (r = 0.876) were strongly associated (p < 0.001) with criterion BF% measures. However, MFBIA, F2FBIA, and HHBIA all significantly (p < 0.001) underestimated BF% when compared with the criterion measure. Constant error ranged between 4.0 and 5.5% across all BIA devices. Despite strong associations between the BIA devices included in the current study and the criterion measure, all BIA devices underestimated BF%, which resulted in an overestimation of fat-free mass. In addition, proportional bias was observed in which BF% was overestimated at lower values and underestimated at higher values. [ABSTRACT FROM AUTHOR]

The purpose of this study was to examine seasonal changes in match demands in a collegiate women's soccer team. Forty-eight NCAA Division III women soccer athletes (age: 19.5 ± 1.2 years; height: 1.67 ± 0.05 m; body mass: 64.8 ± 7.4 kg; fat-free mass: 50.0 ± 4.5 kg; body fat %: 22.6 ± 6.0) were equipped with wearable global positioning systems with inertial sensors and heart rate (HR) monitors during matches throughout the 2019 (n = 22) and 2021 seasons (n = 26). Players were classified by position: flank player (FP; n = 28), center midfielder (CM; n = 11), and center back fielder (CB; n = 9) and as starters (S, n = 17) or reserves (R, n = 31). Variables included HR, training load, total distance, high-speed distance, distance per minute, and weighted distance. Differences in match and practice session demands were analyzed using linear mixed-effects models with season (2 levels; 2019 and 2021) as a fixed factor, with alpha set to p = 0.05. Data across all matches and training sessions were collapsed and presented as mean ± SD for descriptive purposes and then grouped by session type (i.e., match or training) and position. Athletes traveled more distance at high speeds during match play in the 2021 season compared with 2019 (mean difference, 95% confidence intervals [CI]) (200,95% CI: 104,304 km; p < 0.05) but had a lower training load in 2021 compared with 2019 (-50,95% CI: -63, -36; p < 0.05) during match play. For training sessions, mean HR (4, 95% CI: 2, 5 bpm), total distance (0.5, 95% CI: 0.4, 0.7), distance per minute (5.6, 95% CI: 4.5, 6.7 m⋅min-1), high-speed distance (43,95% CI: 43,18,67 m), high accelerations (8.6,95% CI: 5.4,11.8 n), and high accelerations per minute (0.1, 95% CI: 0.1, 0.1 n⋅min-1) were all higher in 2021 compared with 2019 (p < 0.05). As a team, several differences in measures of external workload were found between seasons in both session types (training and matches). Variations in positional demands of match play appear to fluctuate by year. [ABSTRACT FROM AUTHOR]

Rehabilitation from musculoskeletal injuries focuses on reestablishing and monitoring muscle activation patterns to accurately produce force. The aim of this study is to explore the use of a novel low-powered wearable distributed Simultaneous Musculoskeletal Assessment with Real-Time Ultrasound (SMART-US) device to predict force during an isometric squat task. Participants (N = 5) performed maximum isometric squats under two medical imaging techniques; clinical musculoskeletal motion mode (m-mode) ultrasound on the dominant vastus lateralis and SMART-US sensors placed on the rectus femoris, vastus lateralis, medial hamstring, and vastus medialis. Ultrasound features were extracted, and a linear ridge regression model was used to predict ground reaction force. The performance of ultrasound features to predict measured force was tested using either the Clinical M-mode, SMART-US sensors on the vastus lateralis (SMART-US: VL), rectus femoris (SMART-US: RF), medial hamstring (SMART-US: MH), and vastus medialis (SMART-US: VMO) or utilized all four SMART-US sensors (Distributed SMART-US). Model training showed that the Clinical M-mode and the Distributed SMART-US model were both significantly different from the SMART-US: VL, SMART-US: MH, SMART-US: RF, and SMART-US: VMO models (p < 0.05). Model validation showed that the Distributed SMART-US model had an R2 of 0.80 ± 0.04 and was significantly different from SMART-US: VL but not from the Clinical M-mode model. In conclusion, a novel wearable distributed SMART-US system can predict ground reaction force using machine learning, demonstrating the feasibility of wearable ultrasound imaging for ground reaction force estimation. [ABSTRACT FROM AUTHOR]

High levels of fat-free mass (FFM) are favorable for athletes and are related to sport performance. However, fat-free mass index (FFMI), which includes adjustments for height, may offer a better way to characterize FFM beyond raw values. As FFMI is understudied relative to sport, the purpose of the current study was to assess position and age group differences in FFMI among collegiate American football players. National Collegiate Athletic Association DIII (n=111) football players underwent body composition assessment via bioelectrical impedance analysis. FFMI was calculated by dividing FFM by height squared. One-way analyses of variance with Bonferroni post-hoc tests were conducted to evaluate differences in FFMI by position and age groups (α<0.05). The overall mean FFMI was 23.50 ± 2.04 kg· m−2, with values ranging from 18.1–27.7 kg· m−2. FFMI was highest in linemen (24.8 ± 1.5 kg· m−2) and lowest in specialty players (20.6 ± 1.4 kg· m−2) (p<0.05). No differences in FFMI were apparent across age groups (p>0.05). Current findings demonstrate that an athlete’s upper limit for FFMI may exceed 25 kg· m−2, and differences exist across positions, likely due to position-specific demands. These measurements serve as a foundation for tailoring nutritional and exercise plans, forecasting athletic performance, and supplying coaches with standardized data about the potential for additional FFM accretion in collegiate American football players. [ABSTRACT FROM AUTHOR]

The strength of the shoulder musculature involved with internal rotation and arm extension plays an important role in the overhead throwing motion for baseball athletes, both for throwing-related performance and injury risk. The maintenance of shoulder strength is a high priority for baseball athletes throughout a season; however, little is known in regards to the expected changes in strength throughout a season. To examine pre-post changes in shoulder strength, lower body power, and body composition among collegiate baseball players after the completion of a summer baseball league season. Amateur baseball players (n = 12; age: 20.9 ± 1.0 years.; height: 181.6 ± 5.6 cm; body mass: 86.4 ± 11.1 kg; BMI: 26.0 ± 2.6 kg/m2) participated in the current study. Pre- and post-competitive season, the participants completed shoulder strength assessments and body composition and countermovement vertical jump (CMJ) tests. An upper-body isometric test (athletic shoulder [ASH] test) was used to evaluate shoulder strength for each arm. Each subject completed maximal isometric contractions for both the throwing and non-throwing arms at four separate angles of abduction (180°, 'I'; 135°, 'Y'; 90°, 'T'; and −180°, 'A') while lying in a prone position. For shoulder strength, the primary dependent variable of interest was a composite measure that represented the average of the forces produced across all four positions of the ASH test (I, Y, T, A). For the ASH test composite measure, there was a trend toward a significant arm-by-time interaction effect (p = 0.08), as shoulder strength decreased by 9.03% for the throwing arm (ES = 0.72; 95% CI = [−0.27, −0.01]), compared to only 2.03% for the non-throwing arm (ES = 0.15; 95% CI = [−0.16, 0.09]), over the course of the season. The main effects of time (p = 0.16) and arm (p = 0.58) were not significant for the ASH test composite measure. There was no relationship between lower body power and throwing arm strength at baseline (r = 0.20, p = 0.56), and only a non-significant weak relationship at post-test (r = 0.28, p = 0.41). Throughout a season, baseball players may experience reductions in shoulder strength of the throwing arm with minimal changes in shoulder strength in the non-throwing arm. [ABSTRACT FROM AUTHOR]

Brown, FSA, Fields, JB, Jagim, AR, Baker, RE, and Jones, MT. Analysis of in-season external load and sport performance in women's collegiate basketball. J Strength Cond Res 38(2): 318-324, 2024--Quantifying and monitoring athlete workload throughout a competitive season is a means to manage player readiness. Therefore, the purpose of the current study was to quantify practice and game external loads and to assess the relationship between such loads and basketball-specific performance metrics across a women's collegiate basketball season. Thirteen National Collegiate Athletic Association Division I women basketball athletes (age 20.08 6 1.55 years) wore Global Positioning Systems sensors equipped with triaxial accelerometers for 29 games and 66 practices during the 2019-20 season. A multivariate analysis of variance was used to assess differences in external load between high- and low-minute players and across quarters within games (p < 0.05). Bivariate Pearson correlation coefficients were run to determine relationships between external loads and metrics of basketball performance. Findings indicated that highand low-minute athletes experienced different loads during games and practices (p, 0.001). External loads differed by quarter, such that player load (PL) was highest in Q4 (p 5 0.007), PL·min21 was highest in Q1 and lowest in Q4 (p, 0.001), and explosive ratio (i.e., ratio of PL and explosive efforts) was lowest in Q3 (p50.45). Relationships existed between PL·min21 and field goals (r5 0.41; p50.02) and between the explosive ratio and free throws (r50.377 p50.04). These results can be used to inform design of training sessions with the intent to prepare athletes for the demands of the competitive season. It is recommended that future research continue to explore the relationship of sport-specific performance metrics and athlete external load. [ABSTRACT FROM AUTHOR]

Magee, MK, Fields, JB, Jagim, AR, and Jones, MT. Fat-free mass index in a large sample of National Collegiate Athletic Association men and women athletes from a variety of sports. J Strength Cond Res 38(2): 311-317, 2024--Fat-free mass index (FFMI) can be used to categorize fat-free mass (FFM) relative to height. Normative values have been established in a variety of sports, as has suggested lower and upper thresholds of FFMI. However, FFMI has not been reported in a large sample of athletes, representing both sexes and multiple sport types. The purpose of this study was to evaluate differences in FFMI and establish normative values across a large sample of collegiate sports. A total of 1,961 athletes (men: n 5 596, 10 sports; women: n 5 1,365, 8 sports) participated. Height and mass were measured using a stadiometer and calibrated digital scale, respectively. Fat-free mass was assessed with air displacement plethysmography and used to calculate FFMI. Kruskal-Wallis test and one-way analysis of variance evaluated differences in FFMI in women's and men's sports, respectively. When collapsed across sport type and stratified by sex, men had a higher FFMI (21.5 6 1.9 kg·m22 vs. 17.9 6 1.8 kg·m22; p, 0.001). Differences occurred in FFMI across sport. In women, basketball athletes had the highest FFMI (18.9 kg·m22) and highest 99th percentile for FFMI, whereas rowers had the lowest (16.9 kg·m22). In men, throwers had the highest FFMI (25.7 kg·m22) and highest 99th percentile, whereas volleyball athletes had the lowest (19.9 kg·m22). Differences in FFMI may be attributable to dietary habits and physiological demands of respective sports. These results can provide information relative to differences in FFMI values across sports. In addition, sport-specific normative values can be used as benchmarks and targets for training, nutrition, and goal setting. [ABSTRACT FROM AUTHOR]

Fields, JB, Kuhlman, NM, Jagim, AR, Dulak-Sigler, C, and Jones, MT. Analysis of accumulated workloads and performance testing across a collegiate women's lacrosse season. J Strength Cond Res 37(11): 2213-2221, 2023--Monitoring accumulated workloads, acute:chronic workload ratios (ACWR), and training monotony (TM) are practical methods for monitoring athlete physical stress. Performance testing provides useful information about the changing nature of physical abilities. Therefore, the purpose was to examine differences in accumulated workloads based on session type, explore seasonal trends in ACWR and TM, and assess changes in performance assessments in collegiate women's lacrosse athletes. Athletes, who were identified as starters (n 5 12), wore positional monitoring technology during training sessions (n 5 61) and games (n 5 17) and completed preseason and postseason assessments of speed, agility, power (jump tests), strength, aerobic capacity, and body composition. Separate 1-way analyses of variance were used to determine differences in accumulated workloads for session type and differences in performance assessments from preseason to postseason (p,0.05). When compared with games, practice sessions elicited greater (p,0.001) accumulated total distance, player load, repeated high-intensity efforts, accelerations, change of direction, explosive efforts, highspeed efforts (p 5 0.002), and high-speed distance (p 5 0.002). Throughout the season, ACWR and TM ranged from 0.16 to 1.40 AU and 0.68-1.69 AU, respectively. The 40-yd sprint (p, 0.001) and pro-agility (p, 0.001) improved from preseason to postseason, whereas no changes in aerobic capacity, lower-body power, or strength were observed (p. 0.05). The monitoring of accumulated loads, ACWR and TM, and performance tests revealed novel information about the seasonal demands of collegiate women's lacrosse. Women lacrosse players are able to improve speed and agility throughout the season, while maintaining strength, power, and endurance, with minimal reductions in fat-free mass. [ABSTRACT FROM AUTHOR]

Askow, AT, Jennings, W, Jagim, AR, Fields, JB, Beaudoin, RG, Sanchez, GM, Weeks, JE, Oliver, JM, and Jones, MT. Athlete external load measures across a competitive season in high school basketball. J Strength Cond Res 37(11): 2206-2212, 2023--The purpose of this retrospective analysis was to quantify in-season external load and to determine if relationships existed between load metrics and basketball performance. Eleven male high school varsity basketball athletes (n 5 11; mass 80.5 6 9.6 kg, height 190.2 6 9.4 cm, age 17.6 6 0.7 years) were monitored across a season. PlayerLoad (PL), PL per minute (PL·min-1), total jumps, and explosive movements (EMs) were quantified using a commercially available local positioning unit. Basketball-specific performance metrics, including points scored, points allowed, point differentials, and shooting percentages for each quarter and game, were compiled. Data were analyzed using repeated-measure analysis of variance to evaluate differences in load by starting status, session type, game outcome, and game type. Pearson's correlation coefficients were used to assess relationships between load metrics and basketball performance. Statistical significance was set at p,0.05. Themean values across 23 games for PL, PL·min-1, total jumps, and EMs were 4576104 AU, 10.96 1.6 AU, 42.669.6, and 46.767.2, respectively. Relationships were observed (p,0.05) between PL and points scored (r50.38) and free throwpercentage (r50.21). Further relationshipswere observed between PL·min-1 and free throw shooting percentage (r520.27), and between points scored and total jumps (r 5 0.28), and EMs (r 5 0.26). Notable differences in game demands were observed for playing status. Meaningful differences in measures of external load were observed between each quarter of play, with the highest measures evident in quarters 1 and 3.Guards and forwards experienced minimal differences in external load during gameplay, and game outcome did not result in differences. Higher point totals corresponded with higher PL, total jumps, and EM. [ABSTRACT FROM AUTHOR]

The purpose was to examine relationships between external loads (ELs), perceived exertion, and soreness. Collegiate men soccer players (n = 19) were monitored for 72 sessions (training: n = 53; matches: n = 19). Likert scale assessments (0-6) of lower body soreness were collected prior to each session, and ELs were collected using positional monitoring technology. Session rate of perceived exertion (sRPE-load) was calculated by multiplying perceived exertion values (Borg CR-10 Scale) by respective session duration to determine internal load. Multiple analyses of variance were used to determine differences in ELs across seasons (preseason, in-season, post-season) and sessions (training, match). Bivariate Pearson correlation coefficients and linear regression analyses were used to evaluate relationships among soreness, ELs, and sRPE-load. Greatest ELs were observed during pre-season and post-season phases (p < 0.001). Sessions with high perceived exertion and low soreness were associated with higher ELs (p < 0.05). Duration (t = 16.13), total distance (t = 9.17), sprint distance (t = 7.54), player load (t = 4.22), top speed (t = 4.69), and acceleration (t = 2.02) positively predicted sRPE-load (F = 412.9, p < 0.001, R² = 0.75). Soreness was weakly and trivially correlated with ELs (p < 0.05). The very strong relationship between ELs and sRPE-load highlights the utility of sRPE-load as a practical means to estimate workload; however, more research into the relationship between soreness and workload is warranted. [ABSTRACT FROM AUTHOR]

Predictive resting metabolic rate (RMR) equations are widely used to determine total daily energy expenditure (TDEE). However, it remains unclear whether these predictive RMR equations accurately predict TDEE in the athletic populations. The purpose of this study was to examine the accuracy of 10 commonly used RMR prediction equations (Cunningham, De Lorenzo, Freire, Harris-Benedict, Mifflin St. Jeor, Nelson, Owen, Tinsley, Watson, Schofield) in collegiate men and women athletes. One-hundred eighty-seven National Collegiate Athletic Association Division III men (n = 97) and women (n = 90) athletes were recruited to participate in one day of metabolic testing. RMR was measured using indirect calorimetry and body composition was analyzed using air displacement plethysmography. A repeated measures ANOVA with Bonferroni post hoc analyses was selected to determine mean differences between measured and predicted RMR. Linear regression analysis was used to assess the accuracy of each RMR prediction method (p<0.05). All prediction equations significantly underestimated RMR (p<0.001), although there was no difference between the De Lorenzo and Watson equations and measured RMR (p = 1.00) for women, only. In men, the Tinsley and Freire equations were the most agreeable formulas with the lowest root-mean-square prediction error value of 404 and 412 kcals, respectively. In women, the De Lorenzo and Watson equations were the most agreeable equations with the lowest root-mean-squared error value of 171 and 211 kcals, respectively. The results demonstrate that such RMR equations may underestimate actual energy requirements of athletes and thus, practitioners should interpret such values with caution. Highlights All prediction equations significantly underestimated RMR in men athletes. All prediction equations, except for the De Lorenzo and Watson equations, significantly underestimated RMR in women athletes. Although a significant underestimation of RMR in men athletes, the Freire and Tinsley equations were the most agreeable prediction equations. In women athletes, the De Lorenzo and Watson equations were the most agreeable prediction equations. [ABSTRACT FROM AUTHOR]

Tracking and quantifying athlete workload may provide insight into best practice periodization strategies and workload management. Limited information exists detailing the external demands associated with collegiate men's lacrosse. Therefore, the purpose of this study was to investigate and compare practice, game, and positional differences across a lacrosse season. Male collegiate lacrosse athletes (n = 17; body mass: 79.9 kg ± 9.7 kg; body fat %: 14.7 ± 3.8%) wore a global positional system device during practices (n = 66) and games (n = 19). External load metrics were total distance (TD), sprint distance (SD), accelerations (>3 m⋅s-2), sprint efforts, player load (PL), PL/min, and top speed. Multiple analysis of variances assessed differences in external loads across session (practice versus game) and sport position (attackers, midfielders, and defenders). A3 x 4 analysis of variance was used to determine a position-by-time (first quarter [Q1], second quarter [Q2], third quarter [Q3], and fourth quarter [Q4]) interaction (p < 0.05). Total distance (p < 0.001, η²: 0.047), SD (p < 0.001, η²: 0.093), sprint efforts (p < 0.001, η²:0.077), PL (p < 0.001, η²:0.022), and top speeds (p < 0.001, η²:0.086) were all higher in games compared with practices. Attackers and defenders covered more TD (p < 0.001, η² = 0.0257), accelerations (p < 0.001, η² = 0.126), PL (p < 0.001, η² 5 0.233), and PL/min (p < 0.001, η² = 0.193) than midfielders. Attackers and midfielders covered moreSD (p = 0.002 η² 5 0.043), sprint efforts (p < 0.001, η² = 0.053), and achieved higher top speed (p < 0.001, η² = 0.0063) than defenders. Volume and intensity metrics declined by Q4 in attackers and defenders (p < 0.05), whereas external load measures did not differ across quarters for midfielders. Monitoring in-game external loads can assist coaches with individualizing training programs and preparing athletes for game demands. [ABSTRACT FROM AUTHOR]

Purpose: To identify acute effects of a single accentuated eccentric loading (AEL) repetition on subsequent back-squat kinetics and kinematics with different concentric loads. Methods: Resistance-trained men (N = 21) participated in a counterbalanced crossover design and completed 4 protocols (sets × repetitions at eccentric/concentric) as follows: AEL65, 3 × 5 at 120%/65% 1-repetition maximum (1-RM); AEL80, 3 × 3 at 120%/80% 1-RM; TRA65, 3 × 5 at 65%/65% 1-RM; and TRA80, 3 × 3 at 80%/80% 1-RM. During AEL, weight releasers disengaged from the barbell after the eccentric phase of the first repetition and remained off for the remaining repetitions. All repetitions were performed on a force plate with linear position transducers attached to the barbell, from which eccentric and concentric peak and mean velocity, force, and power were derived. Results: Eccentric peak velocity (−0.076 [0.124] m·s−1; P =.01), concentric peak force (187.8 [284.4] N; P =.01), eccentric mean power (−145.2 [62.0] W; P =.03), and eccentric peak power (−328.6 [93.7] W; P <.01) during AEL65 were significantly greater than TRA65. When collapsed across repetitions, AEL65 resulted in slower eccentric velocity and power during repetition 1 but faster eccentric and concentric velocity and power in subsequent repetitions (P ≤.04). When comparing AEL80 with TRA80, concentric peak force (133.8 [56.9] N; P =.03), eccentric mean power (−83.57 [38.0] W; P =.04), and eccentric peak power (−242.84 [67.3] W; P <.01) were enhanced. Conclusions: Including a single supramaximal eccentric phase of 120% 1-RM increased subsequent velocity and power with concentric loads of 65% 1-RM, but not 80% 1-RM. Therefore, AEL is sensitive to the magnitude of concentric loads, which requires a large relative difference to the eccentric load, and weight releasers may not need to be reloaded to induce performance enhancement. [ABSTRACT FROM AUTHOR]