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Purpose: In this commentary, I present arguments against the use of the force–velocity profiling concept in design and adaptations of training programs targeting sprinting. The purpose of this commentary is to make sports practitioners more aware of the rationale behind the concept and explain why it does not work. Rationale: Force–velocity profiling is a mathematical way to present the velocity development during sprint behavior. Some details of this behavior may be accentuated by transforming it to other variables, but it does not add any new information about sprint performance. Thus, contrary to what is often claimed, the force–velocity profile does not represent maximal capacities (ability of force and velocity generation) of the athlete. It is claimed that through force–velocity profiling one may identify the optimal ratio of force and velocity capacities. Furthermore, proponents of the force–velocity profiling concept suggest that through directed training force and velocity capacities can be altered (inversely dependent) to obtain this optimal ratio, without changing the capacity to express power. Fundamentally, this idea is unfounded and implausible. Conclusion: At best, force–velocity profiling may be able to identify between-athletes differences. However, these can be more easily deduced directly from performance time traces.

Background: Exercise with blood-flow restriction (BFR) is being increasingly used by practitioners working with athletic and clinical populations alike. Most early research combined BFR with low-load resistance training and consistently reported increased muscle size and strength without requiring the heavier loads that are traditionally used for unrestricted resistance training. However, this field has evolved with several different active and passive BFR methods emerging in recent research. Purpose: This commentary aims to synthesize the evolving BFR methods for cohorts ranging from healthy athletes to clinical or load-compromised populations. In addition, real-world considerations for practitioners are highlighted, along with areas requiring further research. Conclusions: The BFR literature now incorporates several active and passive methods, reflecting a growing implementation of BFR in sport and allied health fields. In addition to low-load resistance training, BFR is being combined with high-load resistance exercise, aerobic and anaerobic energy systems training of varying intensities, and sport-specific activities. BFR is also being applied passively in the absence of physical activity during periods of muscle disuse or rehabilitation or prior to exercise as a preconditioning or performance-enhancement technique. These various methods have been reported to improve muscular development; cardiorespiratory fitness; functional capacities; tendon, bone, and vascular adaptations; and physical and sport-specific performance and to reduce pain sensations. However, in emerging BFR fields, many unanswered questions remain to refine best practice.

Purpose: One hundred years ago, Hill and Lupton introduced the concept of maximal oxygen uptake ( $\dot{\mathrm{V}}{\mathrm{O}}_2\text{max}$ ), which is regarded as “the principal progenitor of sports physiology.” We provide a succinct overview of the evolvement of research on $\dot{\mathrm{V}}{\mathrm{O}}_2\text{max}$ , from Hill and Lupton‘s initial findings to current debates on limiting factors for $\dot{\mathrm{V}}{\mathrm{O}}_2\text{max}$ and the associated role of convective and diffusive components. Furthermore, we update the current use of $\dot{\mathrm{V}}{\mathrm{O}}_2\text{max}$ in elite endurance sport and clinical settings. Practical Applications and Conclusions: $\dot{\mathrm{V}}{\mathrm{O}}_2\text{max}$ is a healthy and active centenarian that remains a very important measure in elite endurance sports and additionally contributes as an important vital sign of cardiovascular function and fitness in clinical settings. Over the past 100 years, guidelines for the test protocols and exhaustion criteria, as well as the understanding of limiting factors for $\dot{\mathrm{V}}{\mathrm{O}}_2\text{max}$ , have improved dramatically. Presently, possibilities of accurate and noninvasive determination of the convective versus diffusive components of $\dot{\mathrm{V}}{\mathrm{O}}_2\text{max}$ by wearable sensors represent an important future application. $\dot{\mathrm{V}}{\mathrm{O}}_2\text{max}$ is not only an indicator of cardiorespiratory function, fitness, and endurance performance but also represents an important biomarker of cardiovascular function and health to be included in routine assessment in clinical practice.

Purpose: In sprint biathlon, a J-shaped pacing pattern is commonly used. We investigated whether biathletes with a fast-start pacing pattern increase time-trial skiing and shooting performance by pacing more evenly. Methods: Thirty-eight highly trained biathletes (∼21 y, 27 men) performed an individual 7.5 (3 × 2.5 km for women) or 10-km (3 × 3.3 km for men) time trial on roller skis with a self-selected pacing strategy (day 1). Prone (after lap 1) and standing shooting (after lap 2) stages were performed using paper targets. Based on their pacing strategy in the first time trial (ratio between the initial ∼800-m segment pace on lap 1 and average ∼800-m segment pace on laps 1–3), participants were divided into an intervention group with the fastest starting pace (INT, n = 20) or a control group with a more conservative starting pace (CON, n = 18). On day 2, INT was instructed to reduce their starting pace, while CON was instructed to maintain their day 1 strategy. Results: INT increased their overall time-trial performance more than CON from day 1 to day 2  (mean ± 95% CI; 1.5% ± 0.7% vs 0.0% ± 0.9%, P = .02). From day 1 to day 2, INT reduced their starting pace (5.0% ± 1.5%, P < .01), with reduced ratings of perceived exertion during lap 1 (P < .05). For CON, no change was found for starting pace (−0.8% ± 1.2%) or ratings of perceived exertion between days. No differences were found for shooting performance for either group. Conclusion: Highly trained biathletes with a pronounced fast-start pattern improve skiing performance without any change in shooting performance by pacing more evenly.

Background: Maximal lower-body strength can be assessed both dynamically and isometrically; however, the relationship between the changes in these 2 forms of strength following resistance training is not well understood. Purpose: To systematically review and analyze the effects of resistance training on changes in maximal dynamic (1-repetition-maximum back squat, deadlift, and power clean) and position-matched isometric strength (isometric midthigh pull and the isometric squat). In addition, individual-level data were used to quantify the agreement and relationship between changes in dynamic and isometric strength. Methods : Databases were systematically searched to identify eligible articles, and meta-analysis procedures were performed on the extracted data. The raw results from 4 studies were acquired, enabling bias and absolute reliability measures to be calculated using Bland–Altman test of agreement. Results: Eleven studies met the inclusion criteria, which resulted in 29 isometric–dynamic change comparisons. The overall pooled effect was 0.13 in favor of dynamic testing; however, the prediction interval ranged from g = −0.49 to 0.75. There was no evidence of bias (P = .825) between isometric and dynamic tests; however, the reliability coefficient was estimated to be 16%, and the coefficient of variation (%) was 109.27. Conclusions: As a range of future effects can be expected when comparing isometric to dynamic strength changes following resistance training, and limited proportionality exists between changes in these 2 strength qualities, there is strong evidence that isometric and dynamic strength represent separate neuromuscular domains. These findings can be used to inform strength-assessment models in athlete populations.