Objectives: The purpose of this study was twofold: (a) to profile body composition and physical fitness characteristics of collegiate American football starters and (b) to examine differences in key performance indicators across position groups. These indicators included select measures of body composition, joint kinematics, as well as muscular strength and power. Methods: Sixteen National Collegiate Athletic Association (NCAA) Division-II American football athletes (age: 22.25 ± 1.1 years; height: 183.75 ± 7.8 cm; and body mass: 97.22 ± 20.39 kg) volunteered to participate in this study. A Kruskal–Wallis one-way analysis of variance by ranks test with Dunn test post-hoc adjustments was used to examine position differences between Line (n = 3), Big Skill (n = 6), and Skill (n = 7) position groups with α priori set at p < 0.05. Results: The findings of this study suggest that significant differences in body composition (p = 0.004), muscular strength (p = 0.01), and muscular power (p = 0.03) exist between position groups. However, no significant differences were observed in joint kinematics as assessed by the bilateral squat test (p > 0.05). Conclusions: Therefore, key findings from this study suggest that although significant differences in body composition, muscular strength, and muscular power exist, an emphasis should be placed on the regular assessment, development, and maintenance of optimal joint kinematics within collegiate American football populations as this appears to be a shared key performance indicator among starters.

As neuromuscular performance assessment has become a fundamental component of athlete monitoring, ensuring strong measurement reliability is essential for supporting accurate data-driven decision-making. Thus, the purpose of this study was twofold: (i) to examine the reliability of countermovement vertical jump (CMJ) force-time metrics obtained using a portable force plate system (Hawkin Dynamics) and (ii) to determine whether absolute and relative reliability scores differ between well-trained individuals (i.e., athletes) and those less familiar with CMJ force-plate testing (i.e., non-athletes). Seventy-four participants volunteered to take part in this investigation, of whom thirty-nine were NCAA Division-I baseball and track-and-field athletes and thirty-five age-matched non-athletes with no prior CMJ testing experience on force plates. After performing a standardized dynamic warm-up, participants performed three CMJs without arm swing while standing on a dual uniaxial force plate system sampling at 1000 Hz. Each jump trial was separated by a 30 s rest interval. Absolute and relative reliability were assessed using the coefficient of variation (CV) and intraclass correlation coefficient (ICC), respectively. The results revealed that 75% of the variables demonstrated excellent reliability. Specifically, absolute (CV < 10%) and relative (ICC > 0.750) reliability values were good to excellent for most force-time metrics of interest, including braking and propulsive phase duration, peak braking force, average propulsive power, reactive strength index-modified, countermovement depth, and jump height. In contrast, average and peak landing force and inter-limb asymmetry measures during the braking and propulsive phases displayed moderate to good reliability, whereas asymmetry-related variables during the landing phase exhibited poor reliability. In addition, athletes demonstrated lower CV and greater ICC across most metrics compared to non-athletes.

The importance of quantifying maximal horizontal deceleration performance in athlete populations has received a considerable increase in interest over recent years. However, research is still scarce investigating movement characteristics of maximal horizontal decelerations outside of measures derived from instantaneous horizontal velocity of the centre of mass, using technologies such as radar or laser-based devices. Therefore, this study aimed to explore the biomechanical differences for measures of deceleration ability between a novel deceleration task, and the 505 change of direction test, using an inertial measurement unit-based technology. Primary findings suggested differences across several biomechanical characteristics quantified during the deceleration phase, with moderate to large between-test effect sizes. Specifically, subjects were found to exhibit significantly greater reductions in velocity and horizontal braking forces in the 505. Further, subjects showed significantly shorter stopping times and distances in the acceleration-deceleration assessment, however, these displayed insufficient levels of reliability across both assessments, which should be interpreted as a limitation. Therefore, it may be speculated that based on our data, the 505 test, which possesses a predetermined stopping/turning point, presents a greater or different biomechanical challenge to individuals, which must be met with the appropriate neuromuscular and skill-related qualities to efficiently reduce whole-body momentum. These findings may be relevant to practitioners interested in choosing the right assessment to quantify athletes’ maximal horizontal deceleration performance, which can have implications for both health and performance.

Lacrosse players are required to perform multiple sprints and changes of direction over the course of a game. These skills are reliant on the ability to rapidly produce lower-body force to be successful. Currently, little research examining the relationship between specific performance indicators and relative strength within this population exists. The purpose of this study was to investigate relationships between measures of lower-body strength and power to sprinting and change of direction speed (CODS) among male lacrosse players. Archived data for (n= 18) NCAA Division II male lacrosse athletes were used for this analysis. Lower-body strength was assessed using a one-repetition maximum back squat. Power was assessed using a countermovement jump (CMJ), squat jump (SJ), and standing long jump (SLJ). Sprint speed at 10 and 30 yds (i.e., 9.14 and 27.43 m) and CODS (i.e., T-Test (TT) and modified T-Test (MTT) were also assessed. Pearson’s correlation was used to determine relationships between lower-body strength and power to sprint speed and CODS. Significant relationships (r = -0.51 - -0.64, p ≤ 0.05) were discovered between all measures of power and CODS, as well as SLJ and sprint speed (r = -0.51; p = 0.05 and -0.67; p ≤-0.01, respectively). No significant relationships between relative strength and any measures of sprint speed or CODS were discovered. Although relative strength was not directly related to sprint speed or CODS performance, it may indirectly affect these measures based on its relationship to power, and power’s relationship to sprint and CODS performance.

The strength and conditioning literature examining neuromuscular physiology, bioenergetics, neuroendocrine factors, nutrition and metabolic factors, and the use of ergogenic aids, as well as physical and physiological responses and adaptations, have clearly identified the benefits of participating in regular resistance training programs for athletic populations, especially as it relates to improving muscular strength. Beyond evidence-based research, models for resistance training program implementation are of considerable value for optimizing athletic performance. In fact, several have been provided that address general to specific characteristics of athleticism (i.e., strength endurance, muscular strength, and muscular power) through resistance training over the decades. For instance, a published model known as the strength–endurance continuum that enhances dynamic correspondence (i.e., training specificity) in athletic populations by developing structural, metabolic, and neural capacities across a high-load, low-repetition and low-load, high-repetition range. Further models have been developed to enhance performance approaches (i.e., optimum performance training model) and outcomes (i.e., performance pyramid), even within specific populations, such as youth (i.e., youth physical development model). The ten, five, three, or 10-5-3 (TFT) model for strength and conditioning professionals synthesizes currently available information and provides a framework for the effective implementation of resistance training approaches to suit the needs of athletes at each stage of development. The model includes three key components to consider when designing strength and conditioning programs, denoted by the acronym TFT (ten, five, three). Over recent years, the model has gained much support from teams, coaches, and athletes, mainly due to the ability to streamline common knowledge within the field into an efficient and effective resistance training system. Furthermore, this model is distinctly unique from others as it prioritizes the development of strength–endurance, muscular strength, and muscular power concurrently. This paper explains the model itself and begins to provide recommendations for those interested in implementing TFT-based approaches, including a summary of points as a brief take-home guide to implementing TFT interventions. It is the author’s hope that this paper encourages other performance professionals to share their models to appreciate human ingenuity and advance our understanding of individualized approaches and systems towards the physical development of the modern-day athlete.

Introduction: Despite an exponential development in performance monitoring technologies, the physical performance demands of sport remain an understudied topic in scientific literature. Thus, the primary purpose of this study was to quantify and compare the training loads (TL) of a collegiate American football team between in-season practices and official games by general position group, event type, and to assess the interaction between the two.Methods: Twenty-seven NCAA Division-II athletes volunteered to participate in this investigation. In-season TL during 32 practices (categorized as days before game day; GD minus) and 11 conference games were recorded using global positioning system technology. Collected data included total duration, total distance, yards traveled per minute, hard running distance, hard running efforts, 2-dimensional (2D) load, and 3-dimensional (3D) load.Results: A factorial analysis of variance revealed significant main effects in TL for event type (p < 0.001) and position groups (p < 0.001), and an interaction effect between the two (p < 0.001). Unique microcyclic characteristics were observed for each measure of interest. Relative to game values (100%), values for training duration (+25% to −12%; GD-4 to GD-1), yards per minute (+15% to −11%), total distance (+37% to −3%), hard running distance (+33% to −7%), hard running efforts (+33% to −12%), 2D-load (+40% to −7%), and 3D-load (+44% to −3%) were significantly greater than game values on distinct days during the week.Discussion: These findings can improve the current understanding of practice demands relative to games, which may support more optimal sport-specific periodization approaches within American football.