Force velocity profiling for athletes

The concept of force-velocity (FV) profiling is inspired by the fundamental properties of skeletal muscles, where there is an inverse relationship between force and velocity. The measurement of force and the corresponding velocity during varying loads have been conducted since the start of the 20th century. Due to rapid advances in technology, devices that can measure forces and velocities in a variety of movements have increased rapidly in recent years. As a result, FV profiling has gained popularity among coaches, athletes, and scientists as a tool for performance assessment and individualized training prescriptions. The purpose of this Ph.D. thesis was to investigate the use of forcevelocity profiling as a tool for performance assessment and individualized training prescriptions in athletes. To achieve this aim, three experimental studies were conducted, each addressing a specific research question. Study I aimed to assess the reliability and agreement of commonly used measurement equipment for evaluating force-velocity profiles in well-trained and elite athletes. Study II investigated the effectiveness of an individualized training approach based on FV-profiling on jumping performance in well-trained athletes. Lastly, Study III aimed to investigate whether a placebo effect is present when participants are told they are receiving "optimal training" compared to "control training." The hypothesis was that FV-variables obtained from different measurement equipment would not be consistent, and the reliability would depend on the equipment and procedures used. The thesis also hypothesized that individualized training based on FV-profiling would lead to greater improvements in jump height compared to traditional power training. Additionally, a placebo effect was anticipated when participants were informed, they were receiving "optimal training."publishedVersio

Association Between Physical Performance Tests and External Load During Scrimmages in Highly Trained Youth Ice Hockey Players

Author's accepted manuscriptAccepted author manuscript version reprinted, by permission, from International Journal of Sports Physiology and Performance (IJSPP), 2023, 18(1): 47-54, https://doi.org/10.1123/ijspp.2022-0225. © Human Kinetics, Inc.Purpose: To investigate the relationship between physical performance tests and on-ice external load from simulated games (scrimmages) in ice hockey. Methods: A total of 14 players completed a physical performance test battery consisting of 30-m sprint test—run and 30-m sprint test—skate (including 10-m split times and maximum speed), countermovement jump, standing long jump, bench press, pull-ups, and trap bar deadlift and participated in 4 scrimmages. External load variables from scrimmages included total distance; peak speed; slow ( 24.0 km/h) speed skating distance; number of sprints; PlayerLoad™; number of high-intensity events (> 2.5 m/s); accelerations; decelerations; and changes of direction. Bayesian pairwise correlation analyses were performed to assess the relationship between physical performance tests and external load performance variables. Results: The results showed strong evidence (Bayes factor > 10) for associations between pull-ups and high-intensity events (τ = .61) and between maximum speed skate and peak speed (τ = .55). There was moderate evidence (Bayes factor >3 to <10) for 6 associations: both maximum speed skate (τ = .44) and countermovement jump (τ = .44) with sprint speed skating distance, countermovement jump with number of sprints (τ = .46), pull-ups with changes of direction (τ = .50), trap bar with peak speed (τ = .45), and body mass with total distance (τ = .49). Conclusion: This study found physical performance tests to be associated with some of the external load variables from scrimmages. Nevertheless, the majority of correlations did not display meaningful associations, possibly being influenced by the selection of physical performance tests.acceptedVersio

In-season autoregulation of one weekly strength training session maintains physical and external load match performance in professional male football players

The aim of this study was to compare the effects of autoregulating strength training volume based on an objective (external load match performance) versus a subjective (self-selected) method in professional male football players. Sixteen players completed a 10-week strength training programme where the number of sets was regulated based on football match high-intensity running distance (HIR >19.8 km/h, AUTO, n = 7), or self-selected (SELF, n = 9). In addition to traditional physical performance assessments (30-m sprint, countermovement jump, leg-strength, and body composition), external load match performance was assessed with five matches in the beginning and in the end of the study period. Both groups performed ~ 1 weekly bout of ~ 6 sets in leg extensor exercises during the 10-week period, and maintained physical performance during the competitive season, with no group differences detected after the training period. Non-overlap of all pairs (NAP) analysis showed weak-to-moderate effects in external load match performance from before to after the study period, suggesting that players maintained or improved their performance. In conclusion, no group differences were observed, suggesting that both external load autoregulated and self-selected, low-volume in-season strength training maintained physical, and external load match performance in professional male football players.publishedVersio

Should we individualize training based on force-velocity profiling to improve physical performance in athletes?

The present study aimed to examine the effectiveness of an individualized training program based on force-velocity (FV) profiling on jumping, sprinting, strength, and power in athletes. Forty national level team sport athletes (20 ± 4years, 83 ± 13 kg) from ice-hockey, handball, and soccer completed a 10-week training intervention. A theoretical optimal squat jump (SJ)-FV-profile was calculated from SJ with five different loads (0, 20, 40, 60, and 80 kg). Based on their initial FV-profile, athletes were randomized to train toward, away, or irrespective (balanced training) of their initial theoretical optimal FV-profile. The training content was matched between groups in terms of set x repetitions but varied in relative loading to target the different aspects of the FV-profile. The athletes performed 10 and 30 m sprints, SJ and countermovement jump (CMJ), 1 repetition maximum (1RM) squat, and a leg-press power test before and after the intervention. There were no significant group differences for any of the performance measures. Trivial to small changes in 1RM squat (2.9%, 4.6%, and 6.5%), 10 m sprint time (1.0%, −0.9%, and −1.7%), 30 m sprint time (0.9%, −0.6%, and −0.4%), CMJ height (4.3%, 3.1%, and 5.7%), SJ height (4.8%, 3.7%, and 5.7%), and leg-press power (6.7%, 4.2%, and 2.9%) were observed in the groups training toward, away, or irrespective of their initial theoretical optimal FV-profile, respectively. Changes toward the optimal SJ-FV-profile were negatively correlated with changes in SJ height (r = −0.49, p < 0.001). Changes in SJ-power were positively related to changes in SJ-height (r = 0.88, p < 0.001) and CMJ-height (r = 0.32, p = 0.044), but unrelated to changes in 10 m (r = −0.02, p = 0.921) and 30 m sprint time (r = −0.01, p = 0.974). The results from this study do not support the efficacy of individualized training based on SJ-FV profiling.publishedVersio

Associations between Power Training-Induced Changes in Body Composition and Physical Function in Older Men: A Pre-Test-Post-Test Experimental Study

Background: It is well-established that cross-sectional measurements of poor body composition are associated with impaired physical function and that power training effectively enhances total lean mass and physical function in older adults. However, it is unclear if power training-induced changes in body composition are associated with improved physical function in older adults. Aim: The present study investigated associations between body composition and physical function cross-sectionally and with power training-induced changes in older men. Methods: Forty-nine older men (68 ± 5 yrs) completed a 10-week biweekly power training intervention. Body composition was measured using dual-energy X-ray absorptiometry. Physical function was assessed as a composite Z-score combining measures from Sit-to-stand power, Timed up-and-go time, and loaded and unloaded Stair-climbing time (15 steps). Linear and quadratic regression analyses were performed to assess associations between body composition and physical function. Results: At baseline, total (R2 = 0.11, p < 0.05) and percentage body fat (R2 = 0.15, p < 0.05) showed a non-linear relationship with physical function. The apex of the quadratic regression for body composition was 21.5% body fat. Furthermore, there was a non-linear relationship between changes in body fat percentage and physical function from pre- to post-intervention (R2 = 0.15, p < 0.05). Conclusion: The present study’s findings indicate that participants with a body composition of ~20% body fat displayed the highest level of physical function at baseline. Furthermore, despite small pre–post changes in body fat, the results indicate that those who either preserved their body fat percentage or experienced minor alterations observed the greatest improvements in physical function.publishedVersio

Force-velocity profiling in athletes: Reliability and agreement across methods

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Effectiveness of individualized training based on force–velocity profiling on physical function in older men

The study aimed to investigate the effectiveness of an individualized power training program based on force–velocity (FV) profiling on physical function, muscle morphology, and neuromuscular adaptations in older men. Forty-nine healthy men (68 ± 5 years) completed a 10-week training period to enhance muscular power. They were randomized to either a generic power training group (GPT) or an individualized power training group (IPT). Unlike generic training, individualized training was based on low- or high-resistance exercises, from an initial force–velocity profile. Lower-limb FV profile was measured in a pneumatic leg-press, and physical function was assessed as timed up-and-go time (TUG), sit-to-stand power, grip strength, and stair-climbing time (loaded [20kg] and unloaded). Vastus lateralis morphology was measured with ultrasonography. Rate of force development (RFD) and rate of myoelectric activity (RMA) were measured during an isometric knee extension. The GPT group improved loaded stair-climbing time (6.3 ± 3.8 vs. 2.3% ± 7.3%, p = 0.04) more than IPT. Both groups improved stair-climbing time, sit to stand, and leg press power, grip strength, muscle thickness, pennation angle, fascicle length, and RMA from baseline (p < 0.05). Only GPT increased loaded stair-climbing time and RFD (p < 0.05). An individualized power training program based on FV profiling did not improve physical function to a greater degree than generic power training. A generic power training approach combining both heavy and low loads might be advantageous through eliciting both force- and velocity-related neuromuscular adaptions with a concomitant increase in muscular power and physical function in older men.publishedVersio

Strength and Power Testing of Athletes: A Multicenter Study of Test-Retest Reliability

Author's accepted manuscriptAccepted author manuscript version reprinted, by permission, from International Journal of Sports Physiology and Performance (IJSPP), 2022, 17 (7): 1103-1110, https://doi.org/10.1123/ijspp.2021-0558. © Human Kinetics, Inc.Purpose:This study examined the test–retest reliability of common assessments for measuring strength and power of the lowerbody in high-performing athletes.Methods:A total of 100 participants, including both male (n=83) and female (n=17) athletes(21 [4] y, 182 [9] cm, and 78 [12] kg), were recruited for this study, using a multicenter approach. The participants underwentphysical testing 4 times. Thefirst 2 sessions (1 and 2) were separated by∼1 week, followed by a period of 2 to 6 months, whereasthe last 2 sessions (3 and 4) were again separated by∼1 week. The test protocol consisted of squat jumps, countermovementjumps, jump and reach, 30-m sprint, 1-repetition-maximum squat, sprint cycling, and a leg-press test.Results:The typical error(%) ranged from 1.3% to 8.5% for all assessments. The change in means ranged from−1.5% to 2.5% for all assessments, whereasthe interclass correlation coefficient ranged from .85 to .97. The smallest worthwhile change (0.2 of baseline SD) ranged from1.2% to 5.0%. The ratio between the typical error (%) and the smallest worthwhile change (%) ranged from 0.5 to 1.2. Whenobserving the reliability across testing centers, considerable differences in reliability were observed (typical error [%] ratio: 0.44–1.44).Conclusions:Most of the included assessments can be used with confidence by researchers and coaches to measurestrength and power in athletes. Our results highlight the importance of controlling testing reliability at each testing center and notrelying on data from others, despite having applied the same protocol.acceptedVersio

The Force-Velocity Profile for Jumping:What It Is and What It Is Not

Introduction: Force–velocity profiling has been proposed in the literature as a method to identify the overall mechanical characteristics of lower extremities. A force–velocity profile is obtained by plotting for jumps at different loads the effective work as a function of the average push-off velocity, fitting a straight line to the results, and extrapolating this line to find the theoretical maximum isometric force and unloaded shortening velocity. Here we investigated whether the force–velocity profile and its characteristics can be related to the intrinsic force–velocity relationship. Methods: We used simulation models of various complexity, ranging from a simple mass actuated by a linearly damped force to a planar musculoskeletal model comprising four segments and six muscle–tendon complexes. The intrinsic force–velocity relationship of each model was obtained by maximizing the effective work during isokinetic extension at different velocities. Results Several observations were made. First, at the same average velocity, less effective work can be done during jumping than during isokinetic lower extremity extension at this velocity. Second, the intrinsic relationship is curved; fitting a straight line and extrapolating it seem arbitrary. Third, the maximal isometric force and the maximal velocity corresponding to the profile are not independent. Fourth, they both vary with inertial properties of the system. Conclusions: For these reasons, we concluded that the force–velocity profile is specific for the task and is just what it is: the relationship between effective work and an arbitrary estimate of average velocity; it does not represent the intrinsic force–velocity relationship of the lower extremities.publishedVersio