Cognitive functions are essential in any form of exercise. Recently, interest has mounted in addressing the relationship between caffeine intake and cognitive performance during sports practice. This review examines this relationship through a structured search of the databases Medline/PubMed and Web of Science for relevant articles published in English from August 1999 to March 2020. The study followed PRISMA guidelines. Inclusion criteria were defined according to the PICOS model. The identified records reported on randomized cross-over studies in which caffeine intake (as drinks, capsules, energy bars, or gum) was compared to an identical placebo situation. There were no filters on participants’ training level, gender, or age. For the systematic review, 13 studies examining the impacts of caffeine on objective measures of cognitive performance or self-reported cognitive performance were selected. Five of these studies were also subjected to meta-analysis. After pooling data in the meta-analysis, the significant impacts of caffeine only emerged on attention, accuracy, and speed. The results of the 13 studies, nevertheless, suggest that the intake of a low/moderate dose of caffeine before and/or during exercise can improve self-reported energy, mood, and cognitive functions, such as attention; it may also improve simple reaction time, choice reaction time, memory, or fatigue, however, this may depend on the research protocols.

Background: The impact on athletes based on grouping methods according to the date of birth within the constituent year, known as the relative effect of age (RAE), is a factor that can influence the achievement of sports success. Many studies have examined the magnitude of this phenomenon in sport; however, the relationship between the RAE and performance in team sports competition has not been accurately evaluated so far. The purpose of this study was to conduct a systematic review on the influence of the RAE on competition performance in team sports through analysis of published peer-reviewed articles from 2000 to 2019. Methods: According to Preferred Reporting Items for Systematic Reviews and Meta-Analysis systematic search guidelines, 19 studies were identified of the 2,093 that were found in the systematic searching process carried out in four databases: Sport Discus, PubMed, Web of Knowledge, and Scopus. The sample of the study was composed by 77,329 players, of which 92.08% were male and 7.92% were female, whereas the recorded performance measurements were 87,556. The relation between relative age effects and competition performance was registered according to constraints-based theoretical model: individual constraints (sample characteristics) and task constraints (sport context). Moreover, study quality analysis, Strengthening the Reporting of Observational Studies in Epidemiology, was carried out. Results: The short-term individual (10.20%) and collective (18.09%) performance was influenced by the RAE, whereas the long-term individual performance (49.71%) was affected by the RAE reverse. However, in 16.99% of the measurements, no relationship was found between the RAE and competition performance. In the analysis by subcategory, the influence of the RAE was higher in men, in adulthood (senior category), in invasion games, and in national contexts. Discussion: The findings clearly demonstrated that the RAE has a great influence on the performance in team sport. Possible implications for policy and practice should be discussed in order to prevent unequal practice based on biased models that prioritize the athlete's current performance and therefore obviate their maturational development. The heterogeneity and variability of the identified results require a relativization of the findings of this study.

This study examines the relative age effect (RAE) and its impact on the performance of elite male (n = 3,358) and female (n = 3,273) handball players in the U-19 (n = 2,188), U-21 (n = 2,031), and senior (n = 2,412) categories of the 2013/2014, 2015/2016 and 2017/2018 World Handball Championships organised by the International Handball Federation (IHF). The distribution of the players´ birth dates (by quartile: Q, and semester: S) by categories, handball playing positions, and membership of continental federations, were analysed for each of the three two-year periods in which the World Handball Championships took place. Differences between the observed and expected birth dates were tested using a chi-square goodness of fit test, and subsequent calculations were tested using odds ratios. The Spearman’s correlation coefficient was applied to test the correlation between the relative age of the athletes and (their) performance parameters. The results revealed a prevalence of the RAE on both male and female in the U-19 and U-21 categories (p<0.001), and a stabilisation of the RAE throughout the period analysed (2013/14-2017/2018). The RAE was not found in the female senior category (2013, 2015 and 2017) or male senior category (2013) (p>0.05). All playing positions were impacted by the RAE (p<0.001), and especially strong effect sizes were noted for male pivots (Vc = 0.66/0.68/0.60) and female center backs (Vc = 0.71/0.65/0.71). In our analysis of the handball continental federations, the RAE was found in all regions, except Oceania (p>0.05). The RAE also affected athlete performance: the oldest athletes played more minutes and achieved better performances. The RAE was associated with the final placement of the teams in each championship category, except in the male youth category. The findings clearly demonstrated that the RAE has a significant impact on the selection of male and female athletes to international competitions and the performance of both men and women in international handball. The potential implications of these findings for policy and practice are discussed.

Background: The aim of this study is to describe the peak match demands and compare them with average demands in basketball players, from an external load point of view, using different time windows. Another objective is to determine whether there are differences between positions and to provide an approach for practical applications. Methods: During this observational study, each player wore a micro technology device. We collected data from 12 male basketball players (mean ± SD: age 17.56 ± 0.67 years, height 196.17 ± 6.71 cm, body mass 90.83 ± 11.16 kg) during eight games. We analyzed intervals for different time windows using rolling averages (ROLL) to determine the peak match demands for Player Load. A separate one-way analysis of variance (ANOVA) was used to identify statistically significant differences between playing positions across different intense periods. Results: Separate one-way ANOVAs revealed statistically significant differences between 1 min, 5 min, 10 min, and full game periods for Player Load, F (3,168) = 231.80, η_p² = 0.76, large, p < 0.001. It is worth noting that guards produced a statistically significantly higher Player Load in 5 min (p < 0.01, η_p² = −0.69, moderate), 10 min (p < 0.001, η_p² = −0.90, moderate), and full game (p < 0.001, η_p² = −0.96, moderate) periods than forwards. Conclusions: The main finding is that there are significant differences between the most intense moments of a game and the average demands. This means that understanding game demands using averages drastically underestimates the peak demands of the game. This approach helps coaches and fitness coaches to prepare athletes for the most demanding periods of the game and present potential practical applications that could be implemented during training and rehabilitation sessions.

The aim of the present study was to analyze the changes of game-related statistics in expert players across their whole sports careers. From an initial sample including 252 professional basketball players competing in Spanish first division basketball league (ACB) in the 2017–2018 season, 22 met the inclusion criteria. The following game-related statistics were studied: average points, assist, rebounds (all normalized by minute played), 3-point field goals percentage, 2-point field goals percentage, and free throws percentage per season. Each variable was individually investigated with a customized excel spreadsheet assessing individual variations and career trends were calculated. The results showed a positive trend in most of the investigated players in assists (91% of cases) and free throw percentages (73% of cases). Similar percentages of positive and negative trends were observed for all the other game-related statistics (range: 41–59% for negative and positive, respectively). In conclusion, an increase in assist and free throw performance was shown in the investigated players across their playing career. This information is essential for basketball coaches suggesting the use of most experienced players in the final moments of the game.

Background: The aims of the study were (1) to identify the physical fitness and basic anthropometric characteristics of Polish female basketball players aged 13–15 years, (2) to show the effect of maturity timing on the performance in motor tests and basic body composition parameters, (3) to identify the index that contributes most to the prediction of performance in the tests of speed, jumping ability, agility, and endurance.Methods: The sample included 904 female Polish players (U13–15). In part 1, maturity timing category distribution were examined within across age-groups. Maturity timing was followed by grouping with respect to years before or after the observed peak high velocity (PHV): PHV0 (− 0.50 to 0.49), PHV1 (0.50 to 1.49), PHV2 (1.50 to 2.49) and PHV3 (2.50 to 3.49). In part 2, the relationship between the anthropometric variables, physical fitness performance was assessed based on maturity timing categories (ANCOVA analysis). In part 3, backward stepwise multiple regression analyse quantified the relationship between maturity timing (group of PHV) and physical performance.Results: ANCOVA results (age, body height, and body mass as covariates) showed in the U13 female basketball players significantly higher sprinting (20 m), jumping ability and endurance tests results of the PHV1 group. Better results was observed in U14 female players in PHV1 compared to PHV2 and PHV3 in 20 m and jumping tests but opposite trend was observed for 5 m sprint and endurance test (distance covered and VO2_max). U15 basketball players from the PHV3 group were characterized by better results of jumping abilities, endurance, 10 m and 20 m sprint and agility (total, S₄) tests. Maturity timing (10 m), chronological age (5 m, 20 m, agility, SVJ, VJ, and VO_2maxtests), body height (10 m), body mass (10 m, 20 m, VJ, VO_2max), and the interaction between body mass and height (SVJ) were significant (adjustedR² = 0.02–0.10;p < 0.001) predictors of motor skills.Conclusion: Trainng content of female basketball players aged 13–15 years old should be adjusted to biological requirements especially in jumping, endurance and 20 m sprint test. The time from peak height velocity (PHV) was a significant predictor only in the 10 m sprint test.