Individualized Training Based on the Force-Velocity Profile: A Systematic Review with Meta-Analysis examining the Effects on Motor Performance

Individualized Training Based on the Force-Velocity Profile: A Systematic Review with Meta-Analysis examining the Effects on Motor Performance | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Individualized Training Based on the Force-Velocity Profile: A Systematic Review with Meta-Analysis examining the Effects on Motor Performance Christofer Wolte, Thomas Gronwald, Marcelle Schaffarczyk, Jan Wilke This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5135420/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Exercise has numerous benefits for health, well-being and performance. However, due to factors such as genetics or training status, the individual response can be highly different. Force-velocity (FV) based training is a popular method to individualize exercise programs aiming to improve speed and power. This systematic review investigated the effects of FV based training on motor performance. Methods A systematic literature search was conducted by two independent examiners using PubMed, Web of Science, and Google Scholar. We included randomized controlled trials involving healthy adults and comparing individualized (FV) to non-individualized training programs with a minimal duration of four weeks. Study quality was evaluated using the PEDro scale, publication bias was checked by inspection of funnel plots. We used robust variance estimation to pool the effects of individualized vs. non-individualized training for sprint time, strength, and jump height. Results Searches returned 684 articles, and n = 10 papers were included. Study quality was good (5.3 ± 0.8 / 7 points on the PEDro scale) and no indication of publication bias was found. Meta-analysis did not reveal differences between FV based and non-individualized training for strength (SMD: -0.04, 95%CI: -0.34 to 0.26, p = 0.72, I2: 0%), sprint time (SMD: 0.28, 95%CI: -0.75 to 1.32, p = 0.49, I2: 69,7%), and jump height (SMD: 1.8, 95%CI: -0.57 to 4.2, p = 0.11, I2: 90.8%). Conclusion Although FV profiling represents a plausible approach to individualize speed and power training, our meta-analysis does not support its application for performance reasons at present. Future research should investigate more specific conditions and homogenous populations such as elite athletes. Strength sprint jump height individualization exercise Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Background It is well established that exercise has a variety of benefits, increasing motor performance, preventing musculoskeletal injury, reducing the risk of non-communicable diseases, and improving mental health [ 1 – 7 ]. However, the response to training can be highly variable. Hubal et al. [ 8 ] submitted 585 participants to a 12-week progressive resistance training program [ 9 ]. Although the mean improvement in the 1-Repetition Maximum (1RM) was 54%, individual changes ranged from 0 to + 250%. Similarly, pre-post differences in maximal voluntary contraction force varied from − 32 to + 149%. High inter-individual variability has also been observed in the adaptation to endurance-type exercise [ 10 ]. These examples illustrate that some participants may respond strongly to training programs, while others are poor or non-responders. The factors contributing to variability in the training response have been the subject of contentious discussion. In 1999, Bouchard [ 11 ] investigated the role of genetics in the adaptation to chronic endurance training. A total of 481 sedentary individuals from 98 families exercised on a cycle ergometer for 20 weeks. Interestingly, the variance of changes in maximal oxygen uptake (VO2max) was 2.5 times higher between families than within families. Although this may indicate that the responsiveness to exercise is heritable to a certain extent, Mann and colleges (2014) described additional factors potentially affecting the training response. These included the homeostatic stress produced by the training, recovery and readiness to exercise, and nutrition [ 12 ]. In view of the substantial inter-individual differences in exercise effects and the numerous influencing factors, researchers have proposed that training should be individualized, as implied by the principle of individualization [ 13 ]. Indeed, the development of individualized training methods and programs has experienced a recent surge in popularity [ 14 ]. Briefly, the idea of related approaches is to tailor training parameters, such as intensity, volume, or exercise selection, to the individual's specific needs and characteristics (e.g., age, sex, recovery status, fitness level) [ 15 ]. This personalized approach is believed to achieve superior results compared to non-individualized training programs. Among the many methods suggested to individualize training, force-velocity (FV) profiling has received particular attention [ 16 ][ 17 ]. It is based on the assumption that speed or jump height are dependent on both, force and movement velocity [ 18 ]. To determine the FV profile, the outcome of interest (e.g., sprint speed or jump height) is measured repeatedly but with increasing resistance (e.g., unloaded sprint, sprint with a sledge at increasing weights). From the generated data, a FV profile is constructed plotting force against velocity and using linear regression. The comparison of the obtained and optimal FV profiles reveals a force deficit, velocity deficit, or balance between both components. In case of a deficit, exercises selected to improve speed or jump height should address the FV imbalance. For instance, FV based training in individuals with a velocity deficit would focus on movement speed while athletes with a force deficit would be trained towards improving maximal power output. Although several studies have examined the effectiveness of individualized training based on the FV profile, there is no systematic evaluation of the available evidence. Our systematic review with meta-analysis aimed to provide an overview of the current literature, examining the hypothesis that individualization of exercise training programs based on the FV profile is superior to non-individualized training regarding markers of speed and power. Methods A systematic review with meta-analysis was performed adhering to the PRIMSA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines [ 19 ]. The study followed the recommendations for ethical publishing of systematic reviews proposed by Wagner and Wiffen [ 20 ] and was prospectively registered in the PROSPERO database (CRD42024501418). Search strategy and inclusion criteria Two independent examiners (CW and MS) conducted a systematic literature search in PubMed and Web of Science. The search term was “(individual* OR personal* OR optimiz*) AND force-velocity AND (train* OR exercise)”. In addition to the systematic search, an additional search was performed in Google Scholar, screening the first 100 hits produced by the same search term [ 21 , 22 ] [ 23 ]. Furthermore, references from all included studies were checked [ 24 ]. Studies were included when (1) having a randomized controlled trial design (RCT), (2) investigating healthy adults, (3) applying an individualized training intervention (minimum 4 weeks) based on the force-velocity profile, and (4) having a control group with an active but non-individualized training program. Any studies involving patients with chronic diseases or individuals experiencing pain, as well as studies using a crossover design and including children and adolescents were excluded. Methodological quality, reporting bias and certainty about the evidence The Physiotherapy Evidence Database (PEDro) scale [ 25 ] was used by two independent reviewers (TG and MS) in order to assess the methodological quality of the articles included. The PEDro scale consists of 11 different items related to scientific rigor; item 1 is captures external validity (yes/no), items 2 to 11 internal validity. The items are rated using `0` as absent or unclear, and `1` as present. The highest score in the PEDro scale is 10 because item 1 is not included in the total score (lowest score: 0). Given that the assessors are rarely blinded, and that it is impossible to blind the participants and investigators in supervised exercise interventions, the items 5–7 related to blinding were removed from the total score for our study [ 26 ]. The highest score, therefore, was 7 points. To facilitate interpretation, the total score can be interpreted as follows: 6 to 7 = “excellent“, 5 = “good“, 4 = “moderate“, and 0 to 3 = “poor“. To evaluate the risk of a reporting bias, we constructed and visually inspected funnel plots of standard error and effect size. To assess the certainty about the evidence, we used the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) method for each individual outcome [ 27 ]. Due to the randomized controlled trial design, ratings started with the outcome (strength, jump height, sprint time) being classified as ‘high certainty about the evidence’. In case of a) risk of bias (PEDro score < 4), b) imprecision (wide 95% CI), c) inconsistency (high heterogeneity), d) indirectness of evidence (measured outcome does not represent suggested construct), and e) publication bias (funnel plot asymmetry), certainty was rated down by one category for each weakness (e.g., from high to moderate). Quality was rated up by one category in case of a large-magnitude effects or dose-response gradients. This resulted in final certainty rating being high, moderate, low, or very low. Data extraction The following data were extracted by two examiners (CW and MS): sample size, participant characteristics, intervention details, measured outcomes and results (pre and post means and SD as well as pre-post changes and SD per intervention arm). The outcomes of the meta-analyses encompassed measures of strength (e.g., maximum voluntary force), jump height (counter-movement jump/CMJ, squat jump/SJ, and both pooled), and sprint time (e.g., 5m, 10m, 20m, 30m). Biomechanical information was gathered from each study. If a study assessed more than one parameter of the same outcome (e.g., 10 and 20 m sprint, or CMJ and SJ height), all effect sizes (ES) were extracted. Data processing and statistics Per trial arm, changes from pre to post were computed as Mean post – Mean pre and standard deviations (SD) were pooled as In addition to pre-post differences, differences between groups and related SD were calculated. The authors of the primary studies were contacted if data (e.g., SD of changes) were missing and could not be read from figures. To account for within-study outcome dependency resulting from multiple outcomes (e.g., 1RM of squat and leg press), we used robust variance estimation to pool the effect sizes [ 28 ]. Standardized mean differences (SMD) and 95% confidence intervals (CI) were calculated for measures of strength, jump height, and sprint time. We used R (R Foundation for Statistical Computing, Vienna, Austria) with the robumeta (version 2.0, Fisher & Tipton, 2015) and meta packages. Effect sizes (ES) were interpreted as 0 ≤ d < 0.2 trivial, 0.2 ≤ d < 0.5 small, 0.5 ≤ d < 0.8 moderate, or d ≥ 0.8 large [ 29 ]. Heterogeneity was quantified as τ². P values ≤ 0.05 were considered as statistically significant. Results Search results and study characteristics The search returned a total of 684 articles (Fig. 1 ). After removal duplicates and application of the exclusion criteria, n = 10 studies were found eligible for inclusion. The 10 papers [ 16 , 17 , 30 – 37 ] collectively evaluated 417 participants (120 men, 198 women; no sex reported by one study [ 33 ]) with a mean age of 29 ± 17 years. While 6 of the included studies examined the effect of force-velocity training (FVT) on jump capacities, 5 focused on sprint time, and 6 assessed strength. The training duration ranged from 8 to 12 weeks and training frequency varied between two and three sessions per week (Table 1 ). Table 1 Characteristics of the studies included into quantitative synthesis. Study Sample Performance Level Individualization parameter Intervention Duration Outcome Lindberg et al. (2021) 40 male handball, ice hockey, and football players; 20 ± 4 years; Professional (national team) Theoretical SJ FV profile was calculated using SJ with five different weights (0, 20, 40, 60, and 80 kg). 10 weeks 10 and 30 m sprints, SJ and CMJ, 1 repetition maximum (1RM) squat and a leg press performance test Escobar Álvarez et al. (2019) 46 female ballet dancers; 18,9 years Not reported Multiple series of loaded vertical jumps, CMJ. 9 weeks CMJ Barrera-Domínguez et al. (2023) 30 male basketball players; 22,8 ± 5,68 years Not reported CMJ, unilateral drop jumps, triple hop test, sprint, and change of direction. 8 weeks Jumping ability CMJ, Drop Jump, sprint 10m, change of direction (COD) Rodriguez-Lopez et al. (2021) 45 men and women; ≥ 65 years old Not reported FV used to determine 1-RM, F0, V0, and Pmax. Power-oriented resistance training with either light (LL-PT, 40% 1-RM) or heavy (HL-PT, 80% 1-RM) weight on leg press. 12 weeks 1-RM, F0 (force at zero velocity), V0 (maximum unloaded velocity), Pmax (maximum muscle force), RFD), muscle activation, muscle cross-sectional area (CSA), pennation angle (muscle architecture) Jiménez-Reyes et al. (2017) 84 male football and rugby players; 23,1 ± 4,4 years Semi-professional FV imbalance: focused on the FV curve range, where both high loads for strength exercises (> 80% of a repetition maximum in squats) and speed exercises (with bodyweight at high speed) were used. 9 weeks Jumping performance (unloaded SJ height) Zabaloy et al. (2020) 34 male rugby players; 22,17 ± 3,32 years Professional Not reported 7 weeks Sprint performance, 1RM-SQ strength (maximum squat), jump height, (CMJ SJ), Pmax Rakovic et al. (2018) 17 female handball players; IG = 23 ± 3 years, CG 23 ± 3 years Semi-professional /professional Not reported 8 weeks Changes in maximum velocity (V0) and improvements in 0–30 m sprint time Lindberg et al. (2022) 56 healthy males; 68 ± 5 years Recreational FV profile determined by leg press. 10 weeks Stair climb, loaded stair climb, sit to stand, grip strength Cross et al. (2018) 15 male soccer players (27 ± 5 years) and 21 (12 females, 9 males) rugby players (27 ± 2 years) Semi-professional/ professional FV profile determined by sprint. 10 weeks Sprint performance 30-m unresisted, 30-m at 25%; 20-m at 50%; 20-m at 75%; 15-m at 100% BM or its ́ 1080 Sprint equivalents Simpson et al. (2021) 29 male rugby players; 24 ± 3 years Professional Not reported 8 weeks 10-m and 20-m sprint, squats with 3 repetitions, SJ under five load conditions SJ = squat jump, CMJ = counter-movement jump, FV = force-velocity, 1RM = one repetition maximum, CG = control group, IG = intervention group, Risk of bias Ratings of study qualities revealed a low risk of bias for all papers as the mean PEDro score was 5.3 ± 0.8, with values ranging from 4 to 6 (Table 2 ). Visual inspection of funnel plots suggested absence of a reporting bias for strength level and speed while some asymmetry (i.e., lack of small studies with negative effect) was identified for jump height (Fig. 3 ). Quantitative synthesis FVT was not superior to non-individualized training with regard to all tested parameters as no differences to control were found for strength (SMD: -0.04, 95% CI: -0.34 to 0.26, p = 0.72 I 2 : 0%, 6 studies, 14 effect sizes), sprint time (SMD: 0.28, 95% CI: -0.75 to 1.32, p = 0.49, I 2 : 70%, 5 studies, 22 effect sizes), general jump height (SMD: 1.8, 95% CI: -0.57 to 4.16, p = 0.11, I 2 : 90%, 6 studies, 14 effect sizes), CMJ height (SMD: 0.96, 95% CI: -0.49 to 2.41, p = 0.13, Tau 2 : 0.48, 4 studies, 6 effect sizes), and SJ height (SMD: 0.12, 95% CI: -0.67 to 0.92, p = 0.58, Tau 2 : 0, 3 studies, 5 effect sizes). The certainty about the evidence was high for strength, low for sprint time, and very low for jump height. Table 2 PEDro ratings of the included studies. Item score Study 1 2 3 4 5 6 7 8 9 10 11 Total Lindberg et al. (2021) No 1 0 1 0 0 0 1 1 1 1 6 Lindberg et al. (2022) No 1 0 0 0 0 0 1 1 1 1 5 Jiménez-Reyes et al. (2017) No 0 0 0 0 0 0 1 1 1 1 4 Cross et al. (2018) Yes 1 0 1 0 0 0 1 1 1 1 6 Rakovic et al. (2018) Yes 1 0 1 0 0 0 1 1 1 1 6 Rodriguez-Lopez et al. (2021) Yes 1 0 1 0 0 0 1 1 1 1 6 Simpson et al. (2021) No 0 0 0 0 0 0 1 1 1 1 4 Zabaloy et al. (2020) No 1 0 0 0 0 0 1 1 1 1 5 Escobar Àlvarez et al. (2020) No 1 0 0 0 0 0 1 1 1 1 5 Barrera-Domínguez et al. (2023) No 1 0 1 0 0 0 1 1 1 1 6 1 = eligibility criteria specified; 2 = subjects randomly allocated; 3 = concealed allocation; 4 = groups similar at baseline regarding important prognostic indicators; 5 = subject blinding; 6 = therapist blinding; 7 = assessor blinding; 8 = measures of 1 key outcome from 85% of subjects initially allocated to groups; 9 = subjects for whom outcome measures were available received treatment/control as allocated or data analyzed “intention to treat”; 10 = between-group statistical comparisons reported; 11 = point measures and measures of variability Discussion Individualization plays an instrumental role in the design of training programs, which is mainly due to the variability in the exercise response. Non-modifiable factors such as genomic predictors [ 38 ] or the influence of sex hormones [ 39 ] have been proposed to explain different adaptations to the same intervention [ 12 ]. In addition, Pickering et al. [ 40 ] suggested that considering training variables including volume, duration, and intensity may help to reduce heterogeneity. This systematic review investigated the effects of training based on the FV profile, a highly popular approach for exercise-based individualization of interventions aiming to improve speed and power [ 35 ] [ 37 ]. Of note, our meta-analysis of the available literature did not show superiority of FV based training over non-individualized training regimes. The lack of FV based training effects partly contrasts with previous research on methods for exercise-based individualization. Evaluating a total of 58 original studies, Fleckstein et al. [ 41 ] found personalized training to slightly better combat chronic-nonspecific low back pain than standard training. Other recent reviews examining individualization [ 42 ] [ 43 ]) focused on exercise prescription based on heart rate variability (HRV). The authors reported improvements in submaximal physiological parameters, a lower number of non-responders, as well as a higher number of high responders with HRV-based training when compared to predefined training regimes. Regarding performance, however, effects seemed small or of questionable relevance. Non-superiority of FV based individualization may be attributed to several aspects. First, an athlete’s FV profile is significantly influenced by numerous factors such as body mass, joint range of motion, and gravity or friction [ 44 ]. These variables interact in a non-linear way, impacting performance differently and potentially limiting the effectiveness of purely FV based individualization approaches. Additionally, methodological differences in the individual studies (e.g., variation in measurement tools such as smartphone apps or linear transducers) and inadequate adjustments to the specific conditions (e.g., ground) may have impacted the results [ 44 ]. In sum, individualization may need to go beyond FV profiling and include a more comprehensive consideration of both personal and environmental constraints. A second issue does not relate to the individualization method, but the available evidence itself. It needs to be acknowledged that the number of RCTs on FV based training is still small and that the certainty about the evidence of the present meta-analysis was low and very low for sprint time and jump height, respectively. The populations of the primary studies included healthy older persons and athletes, as well as individuals from a number of different sports such as handball, basketball, football, rugby, ice hockey, and ballet dancing. The latter is noteworthy because the nature and magnitude of FV imbalance could be sports specific. For instance, Escobar Álvarez et al. [ 32 ] found a large force deficit of more than 40% in both, their experimental and control groups. Against this background, using more homogenous populations in upcoming trials may help to better delineate the potential of FV based training. Finally, it may be that the potential of FV based training is direction dependent. While effect sizes for sprint time and strength were small or trivial, we found a non-significant, but large effect size for jump height. In view of the comparatively small number of available studies, additional research may help clarify if FV based training is only effective in jumping and/or other vertically directed movements. Conclusion Although FV profiling represents a plausible approach to individualize speed and power training, our meta-analysis does not support its application for performance optimization (particularly regarding strength and sprint time) at present. Future research should investigate more specific conditions and homogenous populations such as elite athletes. Abbreviations FV Force–Velocity 1RM 1–Repetition Maximum CMJ Counter–Movement Jump SJ Squat Jump PEDro Physiotherapy Evidence Database RCT Randomized Controlled Trial CI Confidence Interval SMD Standardized Mean Difference I² I–squared (a statistic measuring heterogeneity) Pmax Maximum Power Output F0 Force at Zero Velocity V0 Maximum Unloaded Velocity RFD Rate of Force Development CSA Cross–Sectional Area GRADE Grading of Recommendations Assessment, Development, and Evaluation PRISMA Preferred Reporting Items for Systematic Reviews and Meta–Analyses PROSPERO International Prospective Register of Systematic Reviews IG Intervention Group CG Control Group COD Change of Direction BM Body Mass HRV Heart Rate Variability LL PT–Light Load Power–Oriented Training HL PT–Heavy Load Power–Oriented Training Declarations Ethics approval and consent to participate Not applicable Consent for publication Not applicable Availability of data and material The data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request. Data are located in controlled access data storage at University of Klagenfurt. Competing interests The authors have no relevant financial or non-financial interests to disclose. Funding No funds, grants, or other support was received. Author contributions: All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by MS, TG and CW. The first draft of the manuscript was written by CW and JW. JW had the idea for the article. CW and MS performed literature search. JW and CW made the analyses and drafted manuscript, all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Acknowledgments - References Gordon BR, McDowell CP, Lyons M, Herring MP. The Effects of Resistance Exercise Training on Anxiety: A Meta-Analysis and Meta-Regression Analysis of Randomized Controlled Trials. Sports Med. 2017;47:2521–32. Lum D, Barbosa TM. Brief Review: Effects of Isometric Strength Training on Strength and Dynamic Performance. Int J Sports Med. 2019;40:363–75. Amiri S, Hasani J, Satkin M. Effect of exercise training on improving sleep disturbances: a systematic review and meta-analysis of randomized control trials. Sleep Med. 2021;84:205–18. Hortobágyi T, Lesinski M, Gäbler M, VanSwearingen JM, Malatesta D, Granacher U. Effects of Three Types of Exercise Interventions on Healthy Old Adults’ Gait Speed: A Systematic Review and Meta-Analysis. Sports Med. 2015;45:1627–43. Granacher U, Hortobágyi T. Exercise to Improve Mobility in Healthy Aging. Sports Med. 2015;45:1625–6. Burton I, McCormack A. The implementation of resistance training principles in exercise interventions for lower limb tendinopathy: A systematic review. Phys Ther Sport. 2021;50:97–113. Levin O, Netz Y, Ziv G. The beneficial effects of different types of exercise interventions on motor and cognitive functions in older age: a systematic review. Eur Rev Aging Phys Act. 2017;14:20. Hubal MJ, Gordish-Dressman H, Thompson PD, Price TB, Hoffman EP, Angelopoulos TJ, et al. Variability in Muscle Size and Strength Gain after Unilateral Resistance Training. Med Sci Sports Exerc. 2005;37:964. Hecksteden A, Kraushaar J, Scharhag-Rosenberger F, Theisen D, Senn S, Meyer T. Individual response to exercise training - a statistical perspective. J Appl Physiol Bethesda Md. 1985. 2015;118:1450–9. Meyler S, Bottoms L, Wellsted D, Muniz-Pumares D. Variability in exercise tolerance and physiological responses to exercise prescribed relative to physiological thresholds and to maximum oxygen uptake. Exp Physiol. 2023;108:581–94. Bouchard C, An P, Rice T, Skinner JS, Wilmore JH, Gagnon J, et al. Familial aggregation ofV˙o 2 max response to exercise training: results from the HERITAGE Family Study. J Appl Physiol. 1999;87:1003–8. Mann TN, Lamberts RP, Lambert MI. High Responders and Low Responders: Factors Associated with Individual Variation in Response to Standardized Training. Sports Med. 2014;44:1113–24. Bouchard C, Rankinen T. Individual differences in response to regular physical activity. Med Sci Sports Exerc. 2001;33:S446. Gronwald T, Törpel A, Herold F, Budde H. Perspective of Dose and Response for Individualized Physical Exercise and Training Prescription. J Funct Morphol Kinesiol. 2020;5:48. Haugen T, Seiler S, Sandbakk Ø, Tønnessen E. The Training and Development of Elite Sprint Performance: an Integration of Scientific and Best Practice Literature. Sports Med - Open [Internet]. 2019 [cited 2024 Apr 17];5. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6872694/ Simpson A, Waldron M, Cushion E, Tallent J. Optimised force-velocity training during pre-season enhances physical performance in professional rugby league players. J Sports Sci. 2021;39:91–100. Lindberg K, Lohne-Seiler H, Fosstveit SH, Sibayan EE, Fjeller JS, Løvold S, et al. Effectiveness of individualized training based on force–velocity profiling on physical function in older men. Scand J Med Sci Sports. 2022;32:1013–25. Samozino P, Rejc E, Di Prampero PE, Belli A, Morin J-B. Optimal force-velocity profile in ballistic movements–altius: citius or fortius? Med Sci Sports Exerc. 2012;44:313–22. Page MJ, Moher D, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. BMJ. 2021;372:n160. Wager E, Wiffen PJ. Ethical issues in preparing and publishing systematic reviews. J Evid-Based Med. 2011;4:130–4. Wilke J, Krause F, Vogt L, Banzer W. What Is Evidence-Based About Myofascial Chains: A Systematic Review. Arch Phys Med Rehabil. 2016;97:454–61. Giesche F, Stief F, Groneberg DA, Wilke J. Effect of unplanned athletic movement on knee mechanics: a systematic review with multilevel meta-analysis. Br J Sports Med. 2021;55:1366–78. Wilke J, Giesche F, Klier K, Vogt L, Herrmann E, Banzer W. Acute Effects of Resistance Exercise on Cognitive Function in Healthy Adults: A Systematic Review with Multilevel Meta-Analysis. Sports Med Auckl NZ. 2019;49:905–16. Horsley T, Dingwall O, Sampson M. Checking reference lists to find additional studies for systematic reviews. Cochrane Database Syst Rev. 2011;2011:MR000026. de Morton NA. The PEDro scale is a valid measure of the methodological quality of clinical trials: a demographic study. Aust J Physiother. 2009;55:129–33. Maher CG, Sherrington C, Herbert RD, Moseley AM, Elkins M. Reliability of the PEDro Scale for Rating Quality of Randomized Controlled Trials. Phys Ther. 2003;83:713–21. Guyatt G, Oxman AD, Akl EA, Kunz R, Vist G, Brozek J, et al. GRADE guidelines: 1. Introduction—GRADE evidence profiles and summary of findings tables. J Clin Epidemiol. 2011;64:383–94. Fisher Z, Tipton E. robumeta: An R-package for robust variance estimation in meta-analysis [Internet]. arXiv; 2015 [cited 2024 May 13]. http://arxiv.org/abs/1503.02220 Faraone SV. Interpreting Estimates of Treatment Effects. Pharm Ther. 2008;33:700–11. Barrera-Domínguez FJ, Almagro BJ, Sáez De Villarreal E, Molina‐López J. Effect of individualised strength and plyometric training on the physical performance of basketball players. Eur J Sport Sci. 2023;23:2379–88. Cross MR, Lahti J, Brown SR, Chedati M, Jimenez-Reyes P, Samozino P et al. Training at maximal power in resisted sprinting: Optimal load determination methodology and pilot results in team sport athletes. Sandbakk Ø, editor. PLOS ONE. 2018;13:e0195477. Escobar Álvarez JA, Fuentes García JP, Da Conceição FA, Jiménez-Reyes P. Individualized Training Based on Force–Velocity Profiling During Jumping in Ballet Dancers. Int J Sports Physiol Perform. 2020;15:788–94. Jiménez-Reyes P, Samozino P, Brughelli M, Morin J-B. Effectiveness of an Individualized Training Based on Force-Velocity Profiling during Jumping. Front Physiol [Internet]. 2017 [cited 2024 Apr 17];7. http://journal.frontiersin.org/article/ 10.3389/fphys.2016.00677/full Lindberg K, Solberg P, Rønnestad BR, Frank MT, Larsen T, Abusdal G, et al. Should we individualize training based on force-velocity profiling to improve physical performance in athletes? Scand J Med Sci Sports. 2021;31:2198–210. Rakovic E, Paulsen G, Helland C, Eriksrud O, Haugen T. The effect of individualised sprint training in elite female team sport athletes: A pilot study. J Sports Sci. 2018;36:2802–8. Rodriguez-Lopez C, Alcazar J, Sanchez‐Martin C, Baltasar‐Fernandez I, Ara I, Csapo R, et al. Neuromuscular adaptations after 12 weeks of light‐ vs. heavy‐load power‐oriented resistance training in older adults. Scand J Med Sci Sports. 2021;32:324–37. Zabaloy S, Pareja-Blanco F, Giráldez JC, Rasmussen JI, González JG. Effects of individualised training programmes based on the force-velocity imbalance on physical performance in rugby players. Isokinet Exerc Sci. 2020;28:181–90. Bouchard C. Genomic predictors of trainability. Exp Physiol. 2012;97:347–52. de Jonge XJ, Thompson B, Drover K, Almarjawi A. Effect of female sex hormones on muscle function and resistance training regimens. J Sci Med Sport. 2017;20:S15. Pickering C, Kiely J. Do Non-Responders to Exercise Exist-and If So, What Should We Do About Them? Sports Med Auckl NZ. 2019;49:1–7. Fleckenstein J, Floessel P, Engel T, Krempel L, Stoll J, Behrens M, et al. Individualized Exercise in Chronic Non-Specific Low Back Pain: A Systematic Review with Meta-Analysis on the Effects of Exercise Alone or in Combination with Psychological Interventions on Pain and Disability. J Pain. 2022;23:1856–73. Düking P, Zinner C, Trabelsi K, Reed JL, Holmberg H-C, Kunz P, et al. Monitoring and adapting endurance training on the basis of heart rate variability monitored by wearable technologies: A systematic review with meta-analysis. J Sci Med Sport. 2021;24:1180–92. Düking P, Zinner C, Reed JL, Holmberg H-C, Sperlich B. Predefined vs data-guided training prescription based on autonomic nervous system variation: A systematic review. Scand J Med Sci Sports. 2020;30:2291–304. Haug WB, Pain MTG. Using a simple model to systematically examine the influence of force-velocity profile and power on vertical jump performance with different constraints. Sports Biomech. 2024;0:1–28. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5135420","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":371692005,"identity":"f7748fde-d82d-442f-82c7-84e4efb446a3","order_by":0,"name":"Christofer Wolte","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9UlEQVRIiWNgGAWjYDACCQaGA0CKH8IrgLMIaUlgkGwA8wwM4Cy8WhhQtBgcIKCFf3bvw4M/f9hI8EsfYJP4YPBHzvj44WcSDDV/cFty57jBYZ6ENAnJvgQ2yRkGBsZmZ9LMJBiO4bbFQCKN4TBDwuE6gzMMbLd5DAwStx1IAGphw6/l4I+EwxL2UC31m/uff5Ng+IdfywEeoBYDHoiWBAOJHDMJxjbcWiRuAB3Gk5YmIXGGsf3nDANjwxk33hRbJPYZ49TCPyON+eMPG2CI9TAfNvhQISfP35++8caHb3I4tSABxgYEO4EYDaNgFIyCUTAKcAIAgFFMWjsyVGYAAAAASUVORK5CYII=","orcid":"https://orcid.org/0009-0005-0466-9830","institution":"University of Klagenfurt","correspondingAuthor":true,"prefix":"","firstName":"Christofer","middleName":"","lastName":"Wolte","suffix":""},{"id":371692006,"identity":"9c3755de-cfa4-401f-a75f-003e3932f424","order_by":1,"name":"Thomas Gronwald","email":"","orcid":"","institution":"Medical School Hamburg","correspondingAuthor":false,"prefix":"","firstName":"Thomas","middleName":"","lastName":"Gronwald","suffix":""},{"id":371692007,"identity":"2a8c7ceb-755d-4e10-81f3-0c14ed6c30be","order_by":2,"name":"Marcelle Schaffarczyk","email":"","orcid":"","institution":"Medical School Hamburg","correspondingAuthor":false,"prefix":"","firstName":"Marcelle","middleName":"","lastName":"Schaffarczyk","suffix":""},{"id":371692008,"identity":"03fde030-dcb4-4036-85f2-f1541952054d","order_by":3,"name":"Jan Wilke","email":"","orcid":"","institution":"University of Bayreuth","correspondingAuthor":false,"prefix":"","firstName":"Jan","middleName":"","lastName":"Wilke","suffix":""}],"badges":[],"createdAt":"2024-09-23 06:02:42","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5135420/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5135420/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":68569197,"identity":"2d1e42e5-d23d-47b2-9349-93e1aabf5d40","added_by":"auto","created_at":"2024-11-08 15:24:44","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":200393,"visible":true,"origin":"","legend":"\u003cp\u003eFlow of the literature search\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-5135420/v1/7f3acead0de7e1cbf49b0eaa.png"},{"id":68568210,"identity":"c2d7e46e-c715-46dd-9fae-632ec65c277b","added_by":"auto","created_at":"2024-11-08 15:16:44","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":276201,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of training individualization with the FV profile vs. non individualized group on strength\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-5135420/v1/403ee40568192601bfeac771.png"},{"id":68568216,"identity":"1ebc4fde-a681-4298-b02b-6ffe0fa7b768","added_by":"auto","created_at":"2024-11-08 15:16:44","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":23874,"visible":true,"origin":"","legend":"\u003cp\u003eFunnel plot of the effects of individualization with the FV profile vs non individualized group on jump height\u0026nbsp;\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-5135420/v1/18c62976d89ff9fd7c1a4e13.png"},{"id":68568215,"identity":"91ac11ae-5d9e-4b10-acd6-becb694985cd","added_by":"auto","created_at":"2024-11-08 15:16:44","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":303070,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of individualization with the FV profile vs. non individualized group on jump height.\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5135420/v1/52717bbf7ba3262f406cf8a8.jpeg"},{"id":68569198,"identity":"9b5c7566-7088-4d50-a3c3-c7f657f4295e","added_by":"auto","created_at":"2024-11-08 15:24:44","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":354544,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of individualization with the FV profile vs. non individualized group on sprint time.\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5135420/v1/b6ee60df57113ef793b97103.jpeg"},{"id":68568212,"identity":"76520a46-eee5-46cf-a879-b388bb29662d","added_by":"auto","created_at":"2024-11-08 15:16:44","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":172237,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of individualization with the FV profile vs. non individualized group on countermovement jump height.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-5135420/v1/f86894e4f015dfce2662c313.png"},{"id":68568214,"identity":"56092880-9770-4c9b-8731-1b677d8e5255","added_by":"auto","created_at":"2024-11-08 15:16:44","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":157741,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of individualization with the FV profile vs. non individualized group on squat jump height.\u003c/p\u003e","description":"","filename":"floatimage8.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5135420/v1/f68295612e4bf28849139008.jpeg"},{"id":76312423,"identity":"2de396c2-a540-427c-8b28-f9e2f74e8d82","added_by":"auto","created_at":"2025-02-14 15:55:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2211885,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5135420/v1/c108b369-4d12-452e-918f-545af06e3b14.pdf"}],"financialInterests":"","formattedTitle":"Individualized Training Based on the Force-Velocity Profile: A Systematic Review with Meta-Analysis examining the Effects on Motor Performance","fulltext":[{"header":"Background","content":"\u003cp\u003eIt is well established that exercise has a variety of benefits, increasing motor performance, preventing musculoskeletal injury, reducing the risk of non-communicable diseases, and improving mental health [\u003cspan additionalcitationids=\"CR2 CR3 CR4 CR5 CR6\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. However, the response to training can be highly variable. Hubal et al. [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] submitted 585 participants to a 12-week progressive resistance training program [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Although the mean improvement in the 1-Repetition Maximum (1RM) was 54%, individual changes ranged from 0 to +\u0026thinsp;250%. Similarly, pre-post differences in maximal voluntary contraction force varied from \u0026minus;\u0026thinsp;32 to +\u0026thinsp;149%. High inter-individual variability has also been observed in the adaptation to endurance-type exercise [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. These examples illustrate that some participants may respond strongly to training programs, while others are poor or non-responders.\u003c/p\u003e \u003cp\u003eThe factors contributing to variability in the training response have been the subject of contentious discussion. In 1999, Bouchard [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] investigated the role of genetics in the adaptation to chronic endurance training. A total of 481 sedentary individuals from 98 families exercised on a cycle ergometer for 20 weeks. Interestingly, the variance of changes in maximal oxygen uptake (VO2max) was 2.5 times higher between families than within families. Although this may indicate that the responsiveness to exercise is heritable to a certain extent, Mann and colleges (2014) described additional factors potentially affecting the training response. These included the homeostatic stress produced by the training, recovery and readiness to exercise, and nutrition [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn view of the substantial inter-individual differences in exercise effects and the numerous influencing factors, researchers have proposed that training should be individualized, as implied by the principle of individualization [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Indeed, the development of individualized training methods and programs has experienced a recent surge in popularity [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Briefly, the idea of related approaches is to tailor training parameters, such as intensity, volume, or exercise selection, to the individual's specific needs and characteristics (e.g., age, sex, recovery status, fitness level) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. This personalized approach is believed to achieve superior results compared to non-individualized training programs.\u003c/p\u003e \u003cp\u003eAmong the many methods suggested to individualize training, force-velocity (FV) profiling has received particular attention [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e][\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. It is based on the assumption that speed or jump height are dependent on both, force and movement velocity [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. To determine the FV profile, the outcome of interest (e.g., sprint speed or jump height) is measured repeatedly but with increasing resistance (e.g., unloaded sprint, sprint with a sledge at increasing weights). From the generated data, a FV profile is constructed plotting force against velocity and using linear regression. The comparison of the obtained and optimal FV profiles reveals a force deficit, velocity deficit, or balance between both components. In case of a deficit, exercises selected to improve speed or jump height should address the FV imbalance. For instance, FV based training in individuals with a velocity deficit would focus on movement speed while athletes with a force deficit would be trained towards improving maximal power output.\u003c/p\u003e \u003cp\u003eAlthough several studies have examined the effectiveness of individualized training based on the FV profile, there is no systematic evaluation of the available evidence. Our systematic review with meta-analysis aimed to provide an overview of the current literature, examining the hypothesis that individualization of exercise training programs based on the FV profile is superior to non-individualized training regarding markers of speed and power.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eA systematic review with meta-analysis was performed adhering to the PRIMSA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The study followed the recommendations for ethical publishing of systematic reviews proposed by Wagner and Wiffen [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] and was prospectively registered in the PROSPERO database (CRD42024501418).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSearch strategy and inclusion criteria\u003c/h2\u003e \u003cp\u003eTwo independent examiners (CW and MS) conducted a systematic literature search in PubMed and Web of Science. The search term was \u0026ldquo;(individual* OR personal* OR optimiz*) AND force-velocity AND (train* OR exercise)\u0026rdquo;. In addition to the systematic search, an additional search was performed in Google Scholar, screening the first 100 hits produced by the same search term [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Furthermore, references from all included studies were checked [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eStudies were included when (1) having a randomized controlled trial design (RCT), (2) investigating healthy adults, (3) applying an individualized training intervention (minimum 4 weeks) based on the force-velocity profile, and (4) having a control group with an active but non-individualized training program. Any studies involving patients with chronic diseases or individuals experiencing pain, as well as studies using a crossover design and including children and adolescents were excluded.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMethodological quality, reporting bias and certainty about the evidence\u003c/h3\u003e\n\u003cp\u003eThe Physiotherapy Evidence Database (PEDro) scale [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] was used by two independent reviewers (TG and MS) in order to assess the methodological quality of the articles included. The PEDro scale consists of 11 different items related to scientific rigor; item 1 is captures external validity (yes/no), items 2 to 11 internal validity. The items are rated using `0` as absent or unclear, and `1` as present. The highest score in the PEDro scale is 10 because item 1 is not included in the total score (lowest score: 0). Given that the assessors are rarely blinded, and that it is impossible to blind the participants and investigators in supervised exercise interventions, the items 5\u0026ndash;7 related to blinding were removed from the total score for our study [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The highest score, therefore, was 7 points. To facilitate interpretation, the total score can be interpreted as follows: 6 to 7 = \u0026ldquo;excellent\u0026ldquo;, 5 = \u0026ldquo;good\u0026ldquo;, 4 = \u0026ldquo;moderate\u0026ldquo;, and 0 to 3 = \u0026ldquo;poor\u0026ldquo;.\u003c/p\u003e \u003cp\u003eTo evaluate the risk of a reporting bias, we constructed and visually inspected funnel plots of standard error and effect size. To assess the certainty about the evidence, we used the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) method for each individual outcome [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Due to the randomized controlled trial design, ratings started with the outcome (strength, jump height, sprint time) being classified as \u0026lsquo;high certainty about the evidence\u0026rsquo;. In case of a) risk of bias (PEDro score\u0026thinsp;\u0026lt;\u0026thinsp;4), b) imprecision (wide 95% CI), c) inconsistency (high heterogeneity), d) indirectness of evidence (measured outcome does not represent suggested construct), and e) publication bias (funnel plot asymmetry), certainty was rated down by one category for each weakness (e.g., from high to moderate). Quality was rated up by one category in case of a large-magnitude effects or dose-response gradients. This resulted in final certainty rating being high, moderate, low, or very low.\u003c/p\u003e\n\u003ch3\u003eData extraction\u003c/h3\u003e\n\u003cp\u003eThe following data were extracted by two examiners (CW and MS): sample size, participant characteristics, intervention details, measured outcomes and results (pre and post means and SD as well as pre-post changes and SD per intervention arm). The outcomes of the meta-analyses encompassed measures of strength (e.g., maximum voluntary force), jump height (counter-movement jump/CMJ, squat jump/SJ, and both pooled), and sprint time (e.g., 5m, 10m, 20m, 30m). Biomechanical information was gathered from each study. If a study assessed more than one parameter of the same outcome (e.g., 10 and 20 m sprint, or CMJ and SJ height), all effect sizes (ES) were extracted.\u003c/p\u003e\n\u003ch3\u003eData processing and statistics\u003c/h3\u003e\n\u003cp\u003ePer trial arm, changes from pre to post were computed as Mean\u003csub\u003epost\u003c/sub\u003e \u0026ndash; Mean\u003csub\u003epre\u003c/sub\u003e and standard deviations (SD) were pooled as\u003c/p\u003e \u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/127393_c7e80a1c9bb65875/127393_custom_files/img1731078804.png\"\u003e\u003cbr\u003e\u003c/p\u003e \u003cp\u003eIn addition to pre-post differences, differences between groups and related SD were calculated. The authors of the primary studies were contacted if data (e.g., SD of changes) were missing and could not be read from figures. To account for within-study outcome dependency resulting from multiple outcomes (e.g., 1RM of squat and leg press), we used robust variance estimation to pool the effect sizes [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Standardized mean differences (SMD) and 95% confidence intervals (CI) were calculated for measures of strength, jump height, and sprint time. We used R (R Foundation for Statistical Computing, Vienna, Austria) with the robumeta (version 2.0, Fisher \u0026amp; Tipton, 2015) and meta packages. Effect sizes (ES) were interpreted as 0\u0026thinsp;\u0026le;\u0026thinsp;d\u0026thinsp;\u0026lt;\u0026thinsp;0.2 trivial, 0.2\u0026thinsp;\u0026le;\u0026thinsp;d\u0026thinsp;\u0026lt;\u0026thinsp;0.5 small, 0.5\u0026thinsp;\u0026le;\u0026thinsp;d\u0026thinsp;\u0026lt;\u0026thinsp;0.8 moderate, or d\u0026thinsp;\u0026ge;\u0026thinsp;0.8 large [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Heterogeneity was quantified as τ\u0026sup2;. P values\u0026thinsp;\u0026le;\u0026thinsp;0.05 were considered as statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSearch results and study characteristics\u003c/h2\u003e \u003cp\u003eThe search returned a total of 684 articles (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). After removal duplicates and application of the exclusion criteria, n\u0026thinsp;=\u0026thinsp;10 studies were found eligible for inclusion.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe 10 papers [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan additionalcitationids=\"CR31 CR32 CR33 CR34 CR35 CR36\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] collectively evaluated 417 participants (120 men, 198 women; no sex reported by one study [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]) with a mean age of 29\u0026thinsp;\u0026plusmn;\u0026thinsp;17 years. While 6 of the included studies examined the effect of force-velocity training (FVT) on jump capacities, 5 focused on sprint time, and 6 assessed strength. The training duration ranged from 8 to 12 weeks and training frequency varied between two and three sessions per week (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of the studies included into quantitative synthesis.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePerformance Level\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIndividualization parameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntervention Duration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOutcome\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLindberg et al. (2021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40 male handball, ice hockey, and football players; 20\u0026thinsp;\u0026plusmn;\u0026thinsp;4 years;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProfessional (national team)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTheoretical SJ FV profile was calculated using SJ with five different weights (0, 20, 40, 60, and 80 kg).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10 and 30 m sprints, SJ and CMJ, 1 repetition maximum (1RM) squat and a leg press performance test\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEscobar \u0026Aacute;lvarez et al. (2019)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46 female ballet dancers; 18,9 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNot reported\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMultiple series of loaded vertical jumps, CMJ.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9 weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMJ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBarrera-Dom\u0026iacute;nguez et al. (2023)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 male basketball players; 22,8\u0026thinsp;\u0026plusmn;\u0026thinsp;5,68 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNot reported\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCMJ, unilateral drop jumps, triple hop test, sprint, and change of direction.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8 weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eJumping ability CMJ, Drop Jump, sprint 10m, change of direction (COD)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRodriguez-Lopez et al. (2021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45 men and women; \u0026ge; 65 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNot reported\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFV used to determine 1-RM, F0, V0, and Pmax. Power-oriented resistance training with either light (LL-PT, 40% 1-RM) or heavy (HL-PT, 80% 1-RM) weight on leg press.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12 weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1-RM, F0 (force at zero velocity), V0 (maximum unloaded velocity), Pmax (maximum muscle force), RFD), muscle activation, muscle cross-sectional area (CSA), pennation angle (muscle architecture)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJim\u0026eacute;nez-Reyes et al. (2017)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84 male football and rugby players; 23,1\u0026thinsp;\u0026plusmn;\u0026thinsp;4,4 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSemi-professional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFV imbalance: focused on the FV curve range, where both high loads for strength exercises (\u0026gt;\u0026thinsp;80% of a repetition maximum in squats) and speed exercises (with bodyweight at high speed) were used.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9 weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eJumping performance (unloaded SJ height)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZabaloy et al. (2020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34 male rugby players; 22,17\u0026thinsp;\u0026plusmn;\u0026thinsp;3,32 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProfessional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNot reported\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7 weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSprint performance, 1RM-SQ strength (maximum squat), jump height, (CMJ SJ), Pmax\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRakovic et al. (2018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 female handball players; IG\u0026thinsp;=\u0026thinsp;23\u0026thinsp;\u0026plusmn;\u0026thinsp;3 years, CG 23\u0026thinsp;\u0026plusmn;\u0026thinsp;3 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSemi-professional /professional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNot reported\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8 weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eChanges in maximum velocity (V0) and improvements in 0\u0026ndash;30 m sprint time\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLindberg et al. (2022)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56 healthy males; 68\u0026thinsp;\u0026plusmn;\u0026thinsp;5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRecreational\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFV profile determined by leg press.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStair climb, loaded stair climb, sit to stand, grip strength\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCross et al. (2018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 male soccer players (27\u0026thinsp;\u0026plusmn;\u0026thinsp;5 years) and 21 (12 females, 9 males) rugby players (27\u0026thinsp;\u0026plusmn;\u0026thinsp;2 years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSemi-professional/ professional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFV profile determined by sprint.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSprint performance 30-m unresisted, 30-m at 25%; 20-m at 50%; 20-m at 75%; 15-m at 100% BM or its ́ 1080 Sprint equivalents\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSimpson et al. (2021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 male rugby players; 24\u0026thinsp;\u0026plusmn;\u0026thinsp;3 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProfessional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNot reported\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8 weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10-m and 20-m sprint, squats with 3 repetitions, SJ under five load conditions\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eSJ\u0026thinsp;=\u0026thinsp;squat jump, CMJ\u0026thinsp;=\u0026thinsp;counter-movement jump, FV\u0026thinsp;=\u0026thinsp;force-velocity, 1RM\u0026thinsp;=\u0026thinsp;one repetition maximum, CG\u0026thinsp;=\u0026thinsp;control group, IG\u0026thinsp;=\u0026thinsp;intervention group,\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eRisk of bias\u003c/h3\u003e\n\u003cp\u003eRatings of study qualities revealed a low risk of bias for all papers as the mean PEDro score was 5.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8, with values ranging from 4 to 6 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Visual inspection of funnel plots suggested absence of a reporting bias for strength level and speed while some asymmetry (i.e., lack of small studies with negative effect) was identified for jump height (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eQuantitative synthesis\u003c/h3\u003e\n\u003cp\u003eFVT was not superior to non-individualized training with regard to all tested parameters as no differences to control were found for strength (SMD: -0.04, 95% CI: -0.34 to 0.26, p\u0026thinsp;=\u0026thinsp;0.72 I\u003csup\u003e2\u003c/sup\u003e: 0%, 6 studies, 14 effect sizes), sprint time (SMD: 0.28, 95% CI: -0.75 to 1.32, p\u0026thinsp;=\u0026thinsp;0.49, I\u003csup\u003e2\u003c/sup\u003e: 70%, 5 studies, 22 effect sizes), general jump height (SMD: 1.8, 95% CI: -0.57 to 4.16, p\u0026thinsp;=\u0026thinsp;0.11, I\u003csup\u003e2\u003c/sup\u003e: 90%, 6 studies, 14 effect sizes), CMJ height (SMD: 0.96, 95% CI: -0.49 to 2.41, p\u0026thinsp;=\u0026thinsp;0.13, Tau\u003csup\u003e2\u003c/sup\u003e: 0.48, 4 studies, 6 effect sizes), and SJ height (SMD: 0.12, 95% CI: -0.67 to 0.92, p\u0026thinsp;=\u0026thinsp;0.58, Tau\u003csup\u003e2\u003c/sup\u003e: 0, 3 studies, 5 effect sizes). The certainty about the evidence was high for strength, low for sprint time, and very low for jump height.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePEDro ratings of the included studies.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"12\" nameend=\"c13\" namest=\"c2\"\u003e \u003cp\u003eItem score\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLindberg et al. (2021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLindberg et al. (2022)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJim\u0026eacute;nez-Reyes et al. (2017)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCross et al. (2018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRakovic et al. (2018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRodriguez-Lopez et al. (2021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSimpson et al. (2021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZabaloy et al. (2020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEscobar \u0026Agrave;lvarez et al. (2020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBarrera-Dom\u0026iacute;nguez et al. (2023)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"13\"\u003e1\u0026thinsp;=\u0026thinsp;eligibility criteria specified; 2\u0026thinsp;=\u0026thinsp;subjects randomly allocated; 3\u0026thinsp;=\u0026thinsp;concealed allocation; 4\u0026thinsp;=\u0026thinsp;groups similar at baseline regarding important prognostic indicators; 5\u0026thinsp;=\u0026thinsp;subject blinding; 6\u0026thinsp;=\u0026thinsp;therapist blinding; 7\u0026thinsp;=\u0026thinsp;assessor blinding; 8\u0026thinsp;=\u0026thinsp;measures of 1 key outcome from 85% of subjects initially allocated to groups; 9\u0026thinsp;=\u0026thinsp;subjects for whom outcome measures were available received treatment/control as allocated or data analyzed \u0026ldquo;intention to treat\u0026rdquo;; 10\u0026thinsp;=\u0026thinsp;between-group statistical comparisons reported; 11\u0026thinsp;=\u0026thinsp;point measures and measures of variability\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIndividualization plays an instrumental role in the design of training programs, which is mainly due to the variability in the exercise response. Non-modifiable factors such as genomic predictors [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] or the influence of sex hormones [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] have been proposed to explain different adaptations to the same intervention [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In addition, Pickering et al. [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] suggested that considering training variables including volume, duration, and intensity may help to reduce heterogeneity. This systematic review investigated the effects of training based on the FV profile, a highly popular approach for exercise-based individualization of interventions aiming to improve speed and power [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Of note, our meta-analysis of the available literature did not show superiority of FV based training over non-individualized training regimes.\u003c/p\u003e \u003cp\u003eThe lack of FV based training effects partly contrasts with previous research on methods for exercise-based individualization. Evaluating a total of 58 original studies, Fleckstein et al. [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] found personalized training to slightly better combat chronic-nonspecific low back pain than standard training. Other recent reviews examining individualization [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]) focused on exercise prescription based on heart rate variability (HRV). The authors reported improvements in submaximal physiological parameters, a lower number of non-responders, as well as a higher number of high responders with HRV-based training when compared to predefined training regimes. Regarding performance, however, effects seemed small or of questionable relevance.\u003c/p\u003e \u003cp\u003eNon-superiority of FV based individualization may be attributed to several aspects. First, an athlete\u0026rsquo;s FV profile is significantly influenced by numerous factors such as body mass, joint range of motion, and gravity or friction [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. These variables interact in a non-linear way, impacting performance differently and potentially limiting the effectiveness of purely FV based individualization approaches. Additionally, methodological differences in the individual studies (e.g., variation in measurement tools such as smartphone apps or linear transducers) and inadequate adjustments to the specific conditions (e.g., ground) may have impacted the results [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. In sum, individualization may need to go beyond FV profiling and include a more comprehensive consideration of both personal and environmental constraints.\u003c/p\u003e \u003cp\u003eA second issue does not relate to the individualization method, but the available evidence itself. It needs to be acknowledged that the number of RCTs on FV based training is still small and that the certainty about the evidence of the present meta-analysis was low and very low for sprint time and jump height, respectively. The populations of the primary studies included healthy older persons and athletes, as well as individuals from a number of different sports such as handball, basketball, football, rugby, ice hockey, and ballet dancing. The latter is noteworthy because the nature and magnitude of FV imbalance could be sports specific. For instance, Escobar \u0026Aacute;lvarez et al. [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] found a large force deficit of more than 40% in both, their experimental and control groups. Against this background, using more homogenous populations in upcoming trials may help to better delineate the potential of FV based training. Finally, it may be that the potential of FV based training is direction dependent. While effect sizes for sprint time and strength were small or trivial, we found a non-significant, but large effect size for jump height. In view of the comparatively small number of available studies, additional research may help clarify if FV based training is only effective in jumping and/or other vertically directed movements.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eAlthough FV profiling represents a plausible approach to individualize speed and power training, our meta-analysis does not support its application for performance optimization (particularly regarding strength and sprint time) at present. Future research should investigate more specific conditions and homogenous populations such as elite athletes.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eForce\u0026ndash;Velocity\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e1RM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e1\u0026ndash;Repetition Maximum\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCMJ\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCounter\u0026ndash;Movement Jump\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSJ\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSquat Jump\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePEDro\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePhysiotherapy Evidence Database\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRCT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRandomized Controlled Trial\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence Interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSMD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStandardized Mean Difference\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eI\u0026sup2;\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eI\u0026ndash;squared (a statistic measuring heterogeneity)\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePmax\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMaximum Power Output\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eF0\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eForce at Zero Velocity\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eV0\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMaximum Unloaded Velocity\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRFD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRate of Force Development\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCSA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCross\u0026ndash;Sectional Area\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGRADE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGrading of Recommendations Assessment, Development, and Evaluation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePRISMA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePreferred Reporting Items for Systematic Reviews and Meta\u0026ndash;Analyses\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePROSPERO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInternational Prospective Register of Systematic Reviews\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIntervention Group\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eControl Group\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCOD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChange of Direction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBody Mass\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHRV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHeart Rate Variability\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePT\u0026ndash;Light Load Power\u0026ndash;Oriented Training\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePT\u0026ndash;Heavy Load Power\u0026ndash;Oriented Training\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request. Data are located in controlled access data storage at University of Klagenfurt.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funds, grants, or other support was received.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by\u0026nbsp;MS, TG\u003csup\u003e\u0026nbsp;\u003c/sup\u003eand CW. The first draft of the manuscript was written by CW and JW. JW had the idea for the article. CW and\u0026nbsp;MS\u0026nbsp;performed literature search. JW and CW made the analyses and drafted manuscript, all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e-\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGordon BR, McDowell CP, Lyons M, Herring MP. The Effects of Resistance Exercise Training on Anxiety: A Meta-Analysis and Meta-Regression Analysis of Randomized Controlled Trials. Sports Med. 2017;47:2521\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLum D, Barbosa TM. Brief Review: Effects of Isometric Strength Training on Strength and Dynamic Performance. Int J Sports Med. 2019;40:363\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmiri S, Hasani J, Satkin M. Effect of exercise training on improving sleep disturbances: a systematic review and meta-analysis of randomized control trials. Sleep Med. 2021;84:205\u0026ndash;18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHortob\u0026aacute;gyi T, Lesinski M, G\u0026auml;bler M, VanSwearingen JM, Malatesta D, Granacher U. Effects of Three Types of Exercise Interventions on Healthy Old Adults\u0026rsquo; Gait Speed: A Systematic Review and Meta-Analysis. Sports Med. 2015;45:1627\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGranacher U, Hortob\u0026aacute;gyi T. Exercise to Improve Mobility in Healthy Aging. Sports Med. 2015;45:1625\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBurton I, McCormack A. The implementation of resistance training principles in exercise interventions for lower limb tendinopathy: A systematic review. Phys Ther Sport. 2021;50:97\u0026ndash;113.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLevin O, Netz Y, Ziv G. The beneficial effects of different types of exercise interventions on motor and cognitive functions in older age: a systematic review. Eur Rev Aging Phys Act. 2017;14:20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHubal MJ, Gordish-Dressman H, Thompson PD, Price TB, Hoffman EP, Angelopoulos TJ, et al. Variability in Muscle Size and Strength Gain after Unilateral Resistance Training. Med Sci Sports Exerc. 2005;37:964.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHecksteden A, Kraushaar J, Scharhag-Rosenberger F, Theisen D, Senn S, Meyer T. Individual response to exercise training - a statistical perspective. J Appl Physiol Bethesda Md. 1985. 2015;118:1450\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMeyler S, Bottoms L, Wellsted D, Muniz-Pumares D. Variability in exercise tolerance and physiological responses to exercise prescribed relative to physiological thresholds and to maximum oxygen uptake. Exp Physiol. 2023;108:581\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBouchard C, An P, Rice T, Skinner JS, Wilmore JH, Gagnon J, et al. Familial aggregation ofV˙o 2 max response to exercise training: results from the HERITAGE Family Study. J Appl Physiol. 1999;87:1003\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMann TN, Lamberts RP, Lambert MI. High Responders and Low Responders: Factors Associated with Individual Variation in Response to Standardized Training. Sports Med. 2014;44:1113\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBouchard C, Rankinen T. Individual differences in response to regular physical activity. Med Sci Sports Exerc. 2001;33:S446.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGronwald T, T\u0026ouml;rpel A, Herold F, Budde H. Perspective of Dose and Response for Individualized Physical Exercise and Training Prescription. J Funct Morphol Kinesiol. 2020;5:48.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHaugen T, Seiler S, Sandbakk \u0026Oslash;, T\u0026oslash;nnessen E. The Training and Development of Elite Sprint Performance: an Integration of Scientific and Best Practice Literature. Sports Med - Open [Internet]. 2019 [cited 2024 Apr 17];5. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6872694/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6872694/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSimpson A, Waldron M, Cushion E, Tallent J. Optimised force-velocity training during pre-season enhances physical performance in professional rugby league players. J Sports Sci. 2021;39:91\u0026ndash;100.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLindberg K, Lohne-Seiler H, Fosstveit SH, Sibayan EE, Fjeller JS, L\u0026oslash;vold S, et al. Effectiveness of individualized training based on force\u0026ndash;velocity profiling on physical function in older men. Scand J Med Sci Sports. 2022;32:1013\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSamozino P, Rejc E, Di Prampero PE, Belli A, Morin J-B. Optimal force-velocity profile in ballistic movements\u0026ndash;altius: citius or fortius? Med Sci Sports Exerc. 2012;44:313\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePage MJ, Moher D, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. BMJ. 2021;372:n160.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWager E, Wiffen PJ. Ethical issues in preparing and publishing systematic reviews. J Evid-Based Med. 2011;4:130\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWilke J, Krause F, Vogt L, Banzer W. What Is Evidence-Based About Myofascial Chains: A Systematic Review. Arch Phys Med Rehabil. 2016;97:454\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGiesche F, Stief F, Groneberg DA, Wilke J. Effect of unplanned athletic movement on knee mechanics: a systematic review with multilevel meta-analysis. Br J Sports Med. 2021;55:1366\u0026ndash;78.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWilke J, Giesche F, Klier K, Vogt L, Herrmann E, Banzer W. Acute Effects of Resistance Exercise on Cognitive Function in Healthy Adults: A Systematic Review with Multilevel Meta-Analysis. Sports Med Auckl NZ. 2019;49:905\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHorsley T, Dingwall O, Sampson M. Checking reference lists to find additional studies for systematic reviews. Cochrane Database Syst Rev. 2011;2011:MR000026.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Morton NA. The PEDro scale is a valid measure of the methodological quality of clinical trials: a demographic study. Aust J Physiother. 2009;55:129\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaher CG, Sherrington C, Herbert RD, Moseley AM, Elkins M. Reliability of the PEDro Scale for Rating Quality of Randomized Controlled Trials. Phys Ther. 2003;83:713\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuyatt G, Oxman AD, Akl EA, Kunz R, Vist G, Brozek J, et al. GRADE guidelines: 1. Introduction\u0026mdash;GRADE evidence profiles and summary of findings tables. J Clin Epidemiol. 2011;64:383\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFisher Z, Tipton E. robumeta: An R-package for robust variance estimation in meta-analysis [Internet]. arXiv; 2015 [cited 2024 May 13]. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://arxiv.org/abs/1503.02220\u003c/span\u003e\u003cspan address=\"http://arxiv.org/abs/1503.02220\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFaraone SV. Interpreting Estimates of Treatment Effects. Pharm Ther. 2008;33:700\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarrera-Dom\u0026iacute;nguez FJ, Almagro BJ, S\u0026aacute;ez De Villarreal E, Molina‐L\u0026oacute;pez J. Effect of individualised strength and plyometric training on the physical performance of basketball players. Eur J Sport Sci. 2023;23:2379\u0026ndash;88.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCross MR, Lahti J, Brown SR, Chedati M, Jimenez-Reyes P, Samozino P et al. Training at maximal power in resisted sprinting: Optimal load determination methodology and pilot results in team sport athletes. Sandbakk \u0026Oslash;, editor. PLOS ONE. 2018;13:e0195477.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEscobar \u0026Aacute;lvarez JA, Fuentes Garc\u0026iacute;a JP, Da Concei\u0026ccedil;\u0026atilde;o FA, Jim\u0026eacute;nez-Reyes P. Individualized Training Based on Force\u0026ndash;Velocity Profiling During Jumping in Ballet Dancers. Int J Sports Physiol Perform. 2020;15:788\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJim\u0026eacute;nez-Reyes P, Samozino P, Brughelli M, Morin J-B. Effectiveness of an Individualized Training Based on Force-Velocity Profiling during Jumping. Front Physiol [Internet]. 2017 [cited 2024 Apr 17];7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://journal.frontiersin.org/article/\u003c/span\u003e\u003cspan address=\"http://journal.frontiersin.org/article/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fphys.2016.00677/full\u003c/span\u003e\u003cspan address=\"10.3389/fphys.2016.00677/full\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLindberg K, Solberg P, R\u0026oslash;nnestad BR, Frank MT, Larsen T, Abusdal G, et al. Should we individualize training based on force-velocity profiling to improve physical performance in athletes? Scand J Med Sci Sports. 2021;31:2198\u0026ndash;210.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRakovic E, Paulsen G, Helland C, Eriksrud O, Haugen T. The effect of individualised sprint training in elite female team sport athletes: A pilot study. J Sports Sci. 2018;36:2802\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRodriguez-Lopez C, Alcazar J, Sanchez‐Martin C, Baltasar‐Fernandez I, Ara I, Csapo R, et al. Neuromuscular adaptations after 12 weeks of light‐ vs. heavy‐load power‐oriented resistance training in older adults. Scand J Med Sci Sports. 2021;32:324\u0026ndash;37.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZabaloy S, Pareja-Blanco F, Gir\u0026aacute;ldez JC, Rasmussen JI, Gonz\u0026aacute;lez JG. Effects of individualised training programmes based on the force-velocity imbalance on physical performance in rugby players. Isokinet Exerc Sci. 2020;28:181\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBouchard C. Genomic predictors of trainability. Exp Physiol. 2012;97:347\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Jonge XJ, Thompson B, Drover K, Almarjawi A. Effect of female sex hormones on muscle function and resistance training regimens. J Sci Med Sport. 2017;20:S15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePickering C, Kiely J. Do Non-Responders to Exercise Exist-and If So, What Should We Do About Them? Sports Med Auckl NZ. 2019;49:1\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFleckenstein J, Floessel P, Engel T, Krempel L, Stoll J, Behrens M, et al. Individualized Exercise in Chronic Non-Specific Low Back Pain: A Systematic Review with Meta-Analysis on the Effects of Exercise Alone or in Combination with Psychological Interventions on Pain and Disability. J Pain. 2022;23:1856\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eD\u0026uuml;king P, Zinner C, Trabelsi K, Reed JL, Holmberg H-C, Kunz P, et al. Monitoring and adapting endurance training on the basis of heart rate variability monitored by wearable technologies: A systematic review with meta-analysis. J Sci Med Sport. 2021;24:1180\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eD\u0026uuml;king P, Zinner C, Reed JL, Holmberg H-C, Sperlich B. Predefined vs data-guided training prescription based on autonomic nervous system variation: A systematic review. Scand J Med Sci Sports. 2020;30:2291\u0026ndash;304.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHaug WB, Pain MTG. Using a simple model to systematically examine the influence of force-velocity profile and power on vertical jump performance with different constraints. Sports Biomech. 2024;0:1\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Strength, sprint, jump height, individualization, exercise","lastPublishedDoi":"10.21203/rs.3.rs-5135420/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5135420/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eExercise has numerous benefits for health, well-being and performance. However, due to factors such as genetics or training status, the individual response can be highly different. Force-velocity (FV) based training is a popular method to individualize exercise programs aiming to improve speed and power. This systematic review investigated the effects of FV based training on motor performance.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA systematic literature search was conducted by two independent examiners using PubMed, Web of Science, and Google Scholar. We included randomized controlled trials involving healthy adults and comparing individualized (FV) to non-individualized training programs with a minimal duration of four weeks. Study quality was evaluated using the PEDro scale, publication bias was checked by inspection of funnel plots. We used robust variance estimation to pool the effects of individualized vs. non-individualized training for sprint time, strength, and jump height.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eSearches returned 684 articles, and n\u0026thinsp;=\u0026thinsp;10 papers were included. Study quality was good (5.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 / 7 points on the PEDro scale) and no indication of publication bias was found. Meta-analysis did not reveal differences between FV based and non-individualized training for strength (SMD: -0.04, 95%CI: -0.34 to 0.26, p\u0026thinsp;=\u0026thinsp;0.72, I2: 0%), sprint time (SMD: 0.28, 95%CI: -0.75 to 1.32, p\u0026thinsp;=\u0026thinsp;0.49, I2: 69,7%), and jump height (SMD: 1.8, 95%CI: -0.57 to 4.2, p\u0026thinsp;=\u0026thinsp;0.11, I2: 90.8%).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eAlthough FV profiling represents a plausible approach to individualize speed and power training, our meta-analysis does not support its application for performance reasons at present. Future research should investigate more specific conditions and homogenous populations such as elite athletes.\u003c/p\u003e","manuscriptTitle":"Individualized Training Based on the Force-Velocity Profile: A Systematic Review with Meta-Analysis examining the Effects on Motor Performance","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-08 15:16:39","doi":"10.21203/rs.3.rs-5135420/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2dc1021a-53e9-46de-b65b-7d90feb739f9","owner":[],"postedDate":"November 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-02-14T15:47:47+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-08 15:16:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5135420","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5135420","identity":"rs-5135420","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}