(1) Background: Training load monitoring has become a relevant research-practice gap to control training and match demands in team sports. However, there are no systematic reviews about accumulated training and match load in football. (2) Methods: Following the preferred reporting item for systematic reviews and meta-analyses (PRISMA), a systematic search of relevant English-language articles was performed from earliest record to March 2020. The search included descriptors relevant to football, training load, and periodization. (3) Results: The literature search returned 7972 articles (WoS = 1204; Pub-Med = 869, SCOPUS = 5083, and SportDiscus = 816). After screening, 36 full-text articles met the inclusion criteria and were reviewed. Eleven of the included articles analyzed weekly training load distribution; fourteen, the weekly training load and match load distribution; and eleven were about internal and external load relationships during training. The reviewed articles were based on short-telemetry systems (n = 12), global positioning tracking systems (n = 25), local position measurement systems (n = 3), and multiple-camera systems (n = 3). External load measures were quantified with distance and covered distance in different speed zones (n = 27), acceleration and deceleration (n = 13) thresholds, accelerometer metrics (n = 11), metabolic power output (n = 4), and ratios/scores (n = 6). Additionally, the internal load measures were reported with perceived exertion (n = 16); heart-rate-based measures were reported in twelve studies (n = 12). (4) Conclusions: The weekly microcycle presented a high loading variation and a limited variation across a competitive season. The magnitude of loading variation seems to be influenced by the type of week, player’s starting status, playing positions, age group, training mode and contextual variables. The literature has focused mainly on professional men; future research should be on the youth and female accumulated training/match load monitoring.

Monitoring the training load in football is an important strategy to improve athletic performance and an effective training periodization. The aim of this study was two-fold: (1) to quantify the weekly training load and recovery status variations performed by under-15, under-17 and under-19 sub-elite young football players; and (2) to analyze the influence of age, training day, weekly microcycle, training and playing position on the training load and recovery status. Twenty under-15, twenty under-17 and twenty under-19 players were monitored over a 2-week period during the first month of the 2019–2020 competitive season. Global positioning system technology (GPS) was used to collect external training loads: total distance covered, average speed, maximal running speed, relative high-speed running distance, high metabolic load distance, sprinting distance, dynamic stress load, accelerations and decelerations. Internal training load was monitored using ratings of perceived exertion (RPE) and session rating of perceived exertion (sRPE). Recovery status was obtained using the total quality recovery (TQR) scale. The results show an age-related influence for external training load (p ≤ 0.001; d = 0.29–0.86; moderate to strong effect), internal training load (p ≤ 0.001, d = 0.12–0.69; minimum to strong effect) and recovery status (p ≤ 0.001, d = 0.59; strong effect). The external training load presented differences between training days (p < 0.05, d = 0.26–0.95; moderate to strong effect). The playing position had a minimum effect on the weekly training load (p < 0.05; d = 0.06–0.18). The weekly microcycle had a moderate effect in the TD (p < 0.05, d = 0.39), RPE (p < 0.05; d = 0.35) and sRPE (p < 0.05, d = 0.35). Interaction effects were found between the four factors analyzed for deceleration (F = 2.819, p = 0.017) and between inter-day, inter-week and age for total covered distance (F = 8.342, p = 0.008). This study provided specific insights about sub-elite youth football training load and recovery status to monitor training environments and load variations. Future research should include a longer monitoring period to assess training load and recovery variations across different season phases.

The aim of this study was to develop a confirmatory model, using structural equation modeling, to describe and explain the fear of falling in elderly women. Forty-one participants (67.69 ± 5.30 years) were selected to test a theoretical model. The final model revealed that the fear of falling is related to impaired balance (dynamic and static). Strength has a positive effect on both dynamic and static balance. Strength depends on bone mineral density. In conclusion, more strength and bone mineral density and better body balance tend to decrease the fear of falling.

BackgroundWe studied the influence of the ACE I/D and ACTN3 R577X polymorphisms (single or combined) on lower-extremity function in older women in response to high-speed power training.MethodsOne hundred and thirty-nine healthy older Caucasian women participated in this study (age: 65.5 ± 8.2 years, body mass: 67.0 ± 10.0 kg and height: 1.57 ± 0.06 m). Walking speed (S10) performance and functional capacity assessed by the “get-up and go” (GUG) mobility test were measured at baseline (T1) and after a consecutive 12-week period of high-speed power training (40-75% of one repetition maximum in arm and leg extensor exercises; 3 sets 4–12 reps, and two power exercises for upper and lower extremity). Genomic DNA was extracted from blood samples, and genotyping analyses were performed by PCR methods. Genotype distributions between groups were compared by Chi-Square test and the gains in physical performance were analyzed by two-way, repeated-measures ANOVA.ResultsThere were no significant differences between genotype groups in men or women for adjusted baseline phenotypes (P > 0.05). ACE I/D and ACTN3 polymorphisms showed a significant interaction genotype-training only in S10 (P = 0.012 and P = 0.044, respectively) and not in the GUG test (P = 0.311 and P = 0.477, respectively). Analyses of the combined effects between genotypes showed no other significant differences in all phenotypes (P < 0.05) at baseline. However, in response to high-speed power training, a significant interaction on walking speed (P = 0.048) was observed between the “power” (ACTN3 RR + RX & ACE DD) versus “non-power” muscularity-oriented genotypes (ACTN3 XX & ACE II + ID)].ConclusionsThus, ACE I/D and ACTN3 R577X polymorphisms are likely candidates in the modulation of exercise-related gait speed phenotype in older women but not a significant influence in mobility traits.

The aims of this study were 1) to analyze the influence of chronological age, relative age, and biological maturation on accumulated training load and perceived exertion in young sub-elite football players and 2) to understand the interaction effects amongst age grouping, maturation status, and birth quartiles on accumulated training load and perceived exertion in this target population. A 6-week period (18 training sessions and 324 observation cases) concerning 60 young male sub-elite football players grouped into relative age (Q1 to Q4), age group (U15, U17, and U19), and maturation status (Pre-peak height velocity (PHV), Mid-PHV, and Post-PHV) was established. External training load data were collected using 18 Hz global positioning system technology (GPS), heart-rate measures by a 1 Hz short-range telemetry system, and perceived exertion with total quality recovery (TQR) and rating of perceived exertion (RPE). U17 players and U15 players were 2.35 (95% CI: 1.25–4.51) and 1.60 (95% CI: 0.19–4.33) times more likely to pertain to Q1 and Q3, respectively. A negative magnitude for odds ratio was found in all four quartile comparisons within maturation status (95% CI: 6.72–0.64), except for Mid-PHV on Q2 (95% CI: 0.19–4.33). Between- and within-subject analysis reported significant differences in all variables on age group comparison measures (F = 0.439 to 26.636, p = 0.000 to 0.019, η2 = 0.003–0.037), except for dynamic stress load (DSL). Between-subject analysis on maturity status comparison demonstrated significant differences for all training load measures (F = 6.593 to 14.424, p = 0.000 to 0.037, η2 = 0.020–0.092). Interaction effects were found for age group x maturity band x relative age (Λ Pillai’s = 0.391, Λ Wilk’s = 0.609, F = 11.385, p = 0.000, η2 = 0.391) and maturity band x relative age (Λ Pillai’s = 0.252, Λ Wilk’s = 0.769, F = 0.955, p = 0.004, η2 = 0.112). Current research has confirmed the effects of chronological age, relative age, and biological maturation on accumulated training load. Perceived exertion does not seem to show any differences concerning age group or maturity status. Evidence should be helpful for professionals to optimize the training process and young football players’ performance.

The aim of this study was to analyze the effects of match location, quality of opposition and match outcome on match running performance according to playing position in a Portuguese professional football team. Twenty-three male professional football players were monitored from eighteen Portuguese Football League matches during the 2019–2020 season. Global positioning system technology (GPS) was used to collect time-motion data. The match running performance was obtained from five playing positions: central defenders (CD), fullbacks (FB), central midfielders (CM), wide midfielders (WM) and forwards (FW). Match running performance was analyzed within specific position and contextual factors using one-way analysis of variance (ANOVA) for repeated measures, standardized (Cohen) differences and smallest worthwhile change. CM and WM players covered significantly greater total distance (F = 15.45, p = 0.000, η2 = 0.334) and average speed (F = 12.79, p < 0.001, η2 = 0.294). WM and FB players covered higher distances at high-speed running (F = 16.93, p = 0.000, η2 = 0.355) and sprinting (F = 13.49; p < 0.001, η2 = 0.305). WM players covered the highest number of accelerations (F = 4.69, p < 0.001, η2 = 0.132) and decelerations (F = 12.21, p < 0.001, η2 = 0.284). The match running performance was influenced by match location (d = 0.06–2.04; CI: −0.42–2.31; SWC = 0.01–1.10), quality of opposition (d = 0.13–2.14; CI: –0.02–2.60; SWC = 0.01–1.55) and match outcome (d = 0.01–2.49; CI: −0.01–2.31; SWC = 0.01–0.35). Contextual factors influenced the match running performance with differential effects between playing positions. This study provides the first report about the contextual influence on match running performance in a Portuguese professional football team. Future research should also integrate tactical and technical key indicators when analyzing the match-related contextual influence on match running performance.

Complex and dynamic systems are characterised by emergent behaviour, self-similarity, self-organisation and a chaotic component. In team sports as football, complexity and non-linear dynamics includes understanding the mechanisms underlying human movement and collective behaviour. Linear systems approaches in this kind of sports may limit performance understanding due to the fact that small changes in the inputs may not represent proportional and quantifiable changes in the output. Thus, non-linear approaches have been applied to assess training and match outcomes in football. The increasing access to wearable and tracking technology provides large datasets, enabling the analyses of time-series related to different performance indicators such as physiological and positional parameters. However, it is important to frame the theoretical concepts, mathematical models and procedures to determine metrics with physiological and behavioural significance. Additionally, physiological and behavioural data should be considered to determine the complexity and non-linearity of the system in football. Thus, the current chapter summarises the main methodological procedures to extract positional data using non-linear analyses such as entropy scales, relative phase transforms, non-linear indexes, cross correlation, fractals and clustering methods.

Physical inactivity has been classified as a public health problem. The excess fat with muscle loss along with the general decline of physical and functional capacity. The aim of this study was to evaluate the relative contribution of objectively estimated daily physical activity (PA) in functional fitness, isokinetic strength and body composition in community-dwelling elderly women. Sixty elderly female volunteered for this research, with 67.69 ± 5.30 years old. Daily PA was assessed using accelerometers for 7 days. The evaluation and quantification of body composition, total lean body mass, fat mass, total body fat mass and bone mineral density, were made with the DXA equipment. Body Mass Index (BMI) was also calculated. The functional fitness (FF) assessment was performed using Functional Fitness Test. The knee extensor and flexor isokinetic strength was evaluated in both lower limbs, using a dynamometer at two different angular velocities: 60°/sec. and 180°/sec. Body Composition, Bone Mineral Density (p = 0.014) and Fat Mass (p = 0.029) were statistically lowers in the 3rd tertile compared to the 2nd one. The knee flexion peak torque at 180°/sec on the dominant leg (p = 0.051) and non-dominant leg (p = 0.020) was statistically different between the less active group and the most active group. For the FF, no significant differences between groups were found. Our results suggest that daily PA seems to induce benefits on BMI and % Fat Mass as well as on isokinetic