The use of inertial measurement unit (IMU) has become popular in sports assessment. In the case of velocity-based training (VBT), there is a need to measure barbell velocity in each repetition. The use of IMUs may make the monitoring process easier; however, its validity and reliability should be established. Thus, this systematic review aimed to (1) identify and summarize studies that have examined the validity of wearable wireless IMUs for measuring barbell velocity and (2) identify and summarize studies that have examined the reliability of IMUs for measuring barbell velocity. A systematic review of Cochrane Library, EBSCO, PubMed, Scielo, Scopus, SPORTDiscus, and Web of Science databases was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. From the 161 studies initially identified, 22 were fully reviewed, and their outcome measures were extracted and analyzed. Among the eight different IMU models, seven can be considered valid and reliable for measuring barbell velocity. The great majority of IMUs used for measuring barbell velocity in linear trajectories are valid and reliable, and thus can be used by coaches for external load monitoring.

This study aimed to investigate the accuracy and reliability of Polar Team Pro GPS units (10 Hz) when used to measure distance and total distance covered in different speed zones. Eight amateur soccer players (age: 21.37 ± 1.40 years, height: 176.75 ± 5 cm, body mass: 176.75 ± 9.47 kg) completed a team sport simulation cycle. Two Polar Team Pro GPS units were positioned on each player’s chest, and one GPSports GPS unit (15 Hz) was positioned between the scapulae. The data obtained from the two Polar Team Pro GPS units were compared to determine inter-unit reliability. The data obtained from one of the Polar Team Pro GPS units and the GPSports GPS unit (reference standard) were compared to determine concurrent accuracy. There was acceptable inter-unit reliability of Polar Team Pro GPS units for total distance (TD), low speed running (LSR) (0.00–13.99 km h⁻¹), high speed running (HSR) (14.00–19.99 km h⁻¹) and very high speed running (VHSR) (>20.0 km h⁻¹) with high ICCs (0.63, 0.99, 0.99 and 0.99, respectively), and low typical error of measurement (%) (TEM%) (4.64, 5.05, 1.06 and 2.89, respectively). Regarding accuracy, the ICCs were extremely high for LSR and HSR (0.99 and 0.92, respectively), but high for TD and VHSR (0.63 and 0.65, respectively). Moreover, TEM (%) values were very low for TD and LSR (0.6 and 1.6, respectively), but they were high for HSR and VHSR (13.8 and 13.1, respectively). Consequently, acceptable inter-unit reliability was observed, indicating that the Polar Team Pro GPS unit is suitable for tracking pertinent team-sport variables. Moreover, the Polar Team Pro GPS units (10 Hz) are accurate under the same conditions. However, the research showed that the two systems cannot be used interchangeably for quantifying distances covered at higher speeds.

This study aimed to analyse the impact of an 8-week core strength training (CST) programme in youth karate practitioners on core endurance, agility, flexibility, sprinting, jumping, and kick performance. This study followed a randomized parallel design. Twenty-nine participants (age: 12.86 ± 0.81 years old; height: 152.55 ± 10.37 cm; weight: 42.93 ± 8.85 kg) were allocated to a CST programme (n = 16) performed thrice weekly or to a control group (n = 13) only performing the sport-specific (karate) training. Participants were assessed three times (baseline, mid and post-intervention) for the following tests: (i) flexor endurance test (FET); (ii) back extensor test (BET); (iii) lateral musculature test (LMT); (iv) flexibility; (v) chance of direction (COD); (vi) countermovement jump (CMJ); (vii) back muscle strength (BMS); (viii) horizontal jump (LJ); (ix) sprint test; and (x) karate kick test (KKT). Between-group analysis revealed significant advantages for the CST group on the FET (p < 0.001), BET (p < 0.001), LMT (p < 0.001), 20 m sprint (p = 0.021) and KKT for right (p < 0.006) and left (p < 0.020) legs. No significant differences were found between groups in the remaining physical fitness variables (p > 0.05). The within-group changes revealed significant improvements in the CST group at flexibility (p = 0.002), COD (p < 0.001), CMJ (p < 0.001), BMS (p < 0.002), 20 m sprint (p = 0.033), and KKT (p < 0.001). In addition, within-group changes in the control group were also significant in flexibility (p = 0.024) and right kick (p < 0.042). We conclude that the CST programme improves core endurance and karate kick performance; however, it is not effective enough for other physical performance parameters in KR practitioners.

This systematic review aimed to (1) identify and summarize studies that have examined the validity of apps for measuring human strength, power, velocity, and change-of-direction, and (2) identify and summarize studies that have examined the reliability of apps for measuring human strength, power, velocity, and change-of-direction. A systematic review of Cochrane Library, EBSCO, PubMed, Scielo, Scopus, SPORTDiscus, and Web of Science databases was performed, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. From the 435 studies initially identified, 23 were fully reviewed, and their outcome measures were extracted and analyzed. In total, 11 mobile applications were analyzed and summarized for their validity and reliability to test movement velocity, movement time, movement displacement, power output, and workload. The present systematic review revealed that the tested apps are valid and reliable for measuring bar movement velocity during lower and upper body resistance exercises; however, systematic bias was detected with heavier loads.

Background: Stretching has garnered significant attention in sports sciences, resulting in numerous studies. However, there is no comprehensive overview on investigation of stretching in healthy athletes.Objectives: To perform a systematic scoping review with an evidence gap map of stretching studies in healthy athletes, identify current gaps in the literature, and provide stakeholders with priorities for future research.Methods: Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 and PRISMA-ScR guidelines were followed. We included studies comprising healthy athletes exposed to acute and/or chronic stretching interventions. Six databases were searched (CINAHL, EMBASE, PubMed, Scopus, SPORTDiscus, and Web of Science) until 1 January 2023. The relevant data were narratively synthesized; quantitative data summaries were provided for key data items. An evidence gap map was developed to offer an overview of the existing research and relevant gaps.Results: Of ~ 220,000 screened records, we included 300 trials involving 7080 athletes [mostly males (~ 65% versus ~ 20% female, and ~ 15% unreported) under 36 years of age; tiers 2 and 3 of the Participant Classification Framework] across 43 sports. Sports requiring extreme range of motion (e.g., gymnastics) were underrepresented. Most trials assessed the acute effects of stretching, with chronic effects being scrutinized in less than 20% of trials. Chronic interventions averaged 7.4 ± 5.1 weeks and never exceeded 6 months. Most trials (~ 85%) implemented stretching within the warm-up, with other application timings (e.g., post-exercise) being under-researched. Most trials examined static active stretching (62.3%), followed by dynamic stretching (38.3%) and proprioceptive neuromuscular facilitation (PNF) stretching (12.0%), with scarce research on alternative methods (e.g., ballistic stretching). Comparators were mostly limited to passive controls, with ~ 25% of trials including active controls (e.g., strength training). The lower limbs were primarily targeted by interventions (~ 75%). Reporting of dose was heterogeneous in style (e.g., 10 repetitions versus 10 s for dynamic stretching) and completeness of information (i.e., with disparities in the comprehensiveness of the provided information). Most trials (~ 90%) reported performance-related outcomes (mainly strength/power and range of motion); sport-specific outcomes were collected in less than 15% of trials. Biomechanical, physiological, and neural/psychological outcomes were assessed sparsely and heterogeneously; only five trials investigated injury-related outcomes.Conclusions: There is room for improvement, with many areas of research on stretching being underexplored and others currently too heterogeneous for reliable comparisons between studies. There is limited representation of elite-level athletes (~ 5% tier 4 and no tier 5) and underpowered sample sizes (≤ 20 participants). Research was biased toward adult male athletes of sports not requiring extreme ranges of motion, and mostly assessed the acute effects of static active stretching and dynamic stretching during the warm-up. Dose–response relationships remain largely underexplored. Outcomes were mostly limited to general performance testing. Injury prevention and other effects of stretching remain poorly investigated. These relevant research gaps should be prioritized by funding policies.Registration: OSF project (https://osf.io/6auyj/) and registration (https://osf.io/gu8ya).

The aim of this study is to examine how physical performance has changed after 15 weeks (109 days) long-term absence of organized training in youth soccer players imposed by the stay at home orders. A total of sixty-eight young male soccer players from different age categories (U15, U16, U17 and U19) voluntarily participated in the prospective cohort study. Body fat percentage (BF%), counter-movement jump (CMJ), 30 m sprint, change-of-direction (COD) and yo-yo intermittent recovery test level-1 (YYIRTL-1) were evaluated twice (before and after the detraining period). Subsequently, 2 × 2 repeated measures ANOVA was used to investigate group and time differences in repeated measurements. A significance level of p < 0.05 was implemented. CV and SWC values were calculated to test the reliability of the tests performed at different times. Statistical analysis was performed using the IBM SPSS statistics software (v.25, IBM, New York, NY, USA). Significant increments in BF%, 30 m sprint, and COD (left and right), and also significant decrements in CMJ and YYIRTL-1, were found after the detraining period. A long-term detraining period due to the stay at home orders has a detrimental effect on body composition, neuromuscular performances, and aerobic capacity in youth soccer players.