The aim of this study was to systematically review the current literature on the electromyographic (EMG) activity of six core muscles (the rectus abdominis, the internal and external oblique, the transversus abdominis, the lumbar multifidus, and the erector spinae) during core physical fitness exercises in healthy adults. A systematic review of the literature was conducted on the Cochrane, EBSCO, PubMed, Scopus, and Web of Science electronic databases for studies from January 2012 to March 2020. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines were used. The inclusion criteria were as follows: (a) the full text available in English; (b) a cross-sectional or longitudinal (experimental or cohorts) study design; (c) the reporting of electromyographic activity as a percentage of maximum voluntary contraction (% MVIC), millivolts or microvolts; (d) an analysis of the rectus abdominis (RA), transversus abdominis (TA), lumbar multifidus (MUL), erector spinae (ES), and the internal (IO) or external oblique (EO); (e) an analysis of physical fitness exercises for core training; and (f) healthy adult participants. The main findings indicate that the greatest activity of the RA, EO, and ES muscles was found in free-weight exercises. The greatest IO activity was observed in core stability exercises, while traditional exercises showed the greatest MUL activation. However, a lack of research regarding TA activation during core physical fitness exercises was revealed, in addition to a lack of consistency between the studies when applying methods to measure EMG activity.

The study aims were to describe positional differences in the acceleration and sprint profiles of professional football players in match-play, and analyse start speeds required based on the intensity of accelerations and decelerations. This longitudinal study was conducted over thirteen competitive microcycles in a professional football team from LaLiga 123. Data were collected through electronic performance tracking systems. Every player was categorised based on the playing position: central defender (CD), full-back (FB), forward (FW), midfielder (MF), and wide midfielder (WMF). In respect of acceleration profile, positional differences were found for all variables (p < 0.05), except average magnitude of accelerations (ACC_AVG, p = 0.56) and decelerations (DEC_AVG, p = 0.76). The sprint profile also showed positional differences for all variables (p < 0.05), apart from sprint duration (p = 0.07). In addition, although low-intensity accelerations required significantly greater start speeds (Vo) than high-intensity accelerations in WMF (0.4 ± 0.2 km/h; p < 0.05) and FW (0.4 ± 0.2 km/h; p < 0.05), no significant differences (p > 0.05) were found in CD, FB, and MF. However, high-intensity decelerations were performed at significantly higher Vo than low-intensity decelerations in MF (2.65 ± 0.1 km/h; p < 0.05), FW (3.3 ± 0.1 km/h; p < 0.05), FB (3.9 ± 0.4 km/h; p < 0.05), WMF (4.3 ± 0.3 km/h; p < 0.05), and CD (4.1 ± 0.7 km/h; p < 0.05). Therefore, positional differences exist for most variables of the acceleration and sprint profiles. In addition, different Vo were observed between high-intensity and low-intensity accelerations as well as high-intensity and low-intensity decelerations.

The aims of this study were to: (1) identify the representative external load profile of match‐play in Spanish professional soccer players by principal components analysis (PCA), and (2) analyse the effect of match location (home vs away), match outcome (win vs draw vs loss) and length of the microcycle (5 vs 6 vs 7 vs 8 vs 9 days) on the external load profile. Data were collected during one season consisting of 42 matches in LaLiga 123 and 11 external load variables were selected after the PCA. TD, total distance covered; DIS_0–6: distance from 0 to 6 km/h; DIS_21–24: distance from 21 to 24 km/h; HSRD: high‐speed running distance above 21 km/h; HSRA: total of high‐speed running actions above 21 km/h; V _MAX: maximum speed in km/h; Sprints: total of actions above 24 km/h; ACC: total of accelerations; ACC_G‐avg: average accelerometer G‐force; ACC_MAX: maximum acceleration (m/s2); DEC_MAX: maximum deceleration (m/s²). Match location had an impact on HSRD (p < 0.01; ES = 0.05), DIS_0–6 (p < 0.01; ES = 0.05), and ACC_MAX (p < 0.01; ES = 0.05). Match outcome had a relation to TD (p < 0.01; ES = 0.05), DIS_0–6 (p < 0.01; ES = 0.05) and HSRD (p < 0.01; ES = 0.05). Length of the microcycle had an impact on TD (p < 0.01; ES = 0.05), DIS_0–6 (p < 0.01; ES = 0.11), ACC (p < 0.01; ES = 0.04) and V_MAX (p < 0.01; ES = 0.04). This study provides coaches a selection of variables for match‐play analysis, which could represent two‐thirds of external load profile. Then, professionals should consider that these contextual variables could have an impact on the external load profile.

The aim of this study was to analyze the association between teams’ success at the end of the season and match running, and technical-tactical performance in two professional soccer leagues. Match running, and technical-tactical performance data were collected during two consecutive seasons. A...

The aims of this study were to examine the periods in which the maximum speed actions occurred during elite soccer matches and analyse these actions considering the effect of playing position and different contextual variables. Performance-related variables (V_MAX: maximum speed; Vo: starting speed; SPD: sprinting distance; ACC_MAX: maximum acceleration; DEC_MAX: maximum deceleration) and sprint-related contextual variables (trajectory, ball possession, role, field area in which the action occurred) from each maximum speed action were collected. The first 15 minutes of each match half elicited most maximum speed actions (44.6% of cases), regardless of playing position (likelihood ratio, LR=13.95; p=0.95). However, playing position had a significant effect on the role of the action (Chi-Squared, χ²=50.68; p=0.001) and the field area in which the sprint occurred (χ²=26.54; p=0.001). Regarding the effect of different contextual variables on the sprint-related performance variables, no significant effect from any contextual variable on ACC_MAX, DEC_MAX or Vo was found (p > 0.05). Nevertheless, the contextual variables had a significant effect on SPD (from ball possession: sprints without ball > sprints with ball; trajectory: non-linear sprints > linear sprints; role: offensive sprints > defensive sprints) and V_MAX (from ball possession: sprints without ball > sprints with ball; playing position: midfielders < other positions).

The aims of this study were to establish sources of variability in match physical performance of professional soccer players and provide a method for monitoring individual between‐match changes. Eleven players meeting the final inclusion criteria were monitored through an entire in‐season competition phase (n = 240 individual match observations). Ten Hertz global positioning systems were used to measure match total distance (TD), total high‐speed running distance (≥ 21 km·h⁻¹; HSRD), total accelerations (TAcc) and maximum running velocity (V _max). Between‐player, between‐position, between‐match and within‐player variability were determined through linear mixed effects models. These data were then used to establish the practical significance of individual changes using a Minimum Effects Testing framework. All sources of variability were greater for HSRD (13–36%) when compared with all other metrics (<6%). Using combined between‐match and within‐player variability along with the smallest worthwhile change (0.2 × between‐player SD), between‐match individual changes of ±∼10–15% in TD, TAcc and V _max were established as practically significant. For HSRD, these thresholds were considerably higher (≥60%). In conclusion, the ability for soccer practitioners to identify meaningful changes in match physical performance can aid decision making around player management following competition. Our study provides a method to flag changes beyond the normal match‐to‐match variability and by a substantial magnitude. This may have implications for recovery but should be combined with other sources of data (internal load and response) and used only as an adjunct to practitioner domain knowledge/experience.