RESUMO
OBJECTIVES: To identify and summarise the contextual factors associated with running demands in elite male Australian football (AF) gameplay that have been reported in the literature. DESIGN: Scoping review. METHODS: A contextual factor in sporting gameplay is a variable associated with the interpretation of results, yet is not the primary objective of gameplay. Systematic literature searches were performed in four databases to identify what contextual factors associated with running demands in elite male AF have been reported: Scopus, SPORTDiscus, Ovid Medline and CINAHL, for terms constructed around Australian football AND running demands AND contextual factors. The present scoping review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), and narrative synthesis was conducted. RESULTS AND CONCLUSION: A total of 36 unique articles were identified by the systematic literature search, which included 20 unique contextual factors. The most studied contextual factors were position (n = 13), time in game (n = 9), phases of play (n = 8), rotations (n = 7) and player rank (n = 6). Multiple contextual factors, such as playing position, aerobic fitness, rotations, time within a game, stoppages, and season phase appear to correlate with running demands in elite male AF. Many identified contextual factors have very limited published evidence and thus additional studies would help draw stronger conclusions.
RESUMO
BACKGROUND: Intensified training is important for inducing adaptations to improve athletic performance, but detrimental performance effects can occur if prescribed inappropriately. Monitoring biomarker responses to training may inform changes in training load to optimize performance. OBJECTIVE: This systematic review and meta-analysis aimed to identify biomarkers associated with altered exercise performance following intensified training. METHODS: Embase, MEDLINE, CINAHL, Scopus and SPORTDiscus were searched up until September 2017. Included articles were peer reviewed and reported on biomarkers collected at rest in well-trained male athletes before and after periods of intensified training. RESULTS: The full text of 161 articles was reviewed, with 59 included (708 participants) and 42 (550 participants) meta-analysed. In total, 118 biomarkers were evaluated, with most being cellular communication and immunity markers (n = 54). Studies most frequently measured cortisol (n = 34), creatine kinase (n = 25) and testosterone (n = 20). Many studies reported decreased immune cell counts following intensified training, irrespective of performance. Moreover, reduced performance was associated with a decrease in neutrophils (d = - 0.57; 95% confidence interval (CI) - 1.07 to - 0.07) and glutamine (d = - 0.37; 95% CI - 0.43 to - 0.31) and an increase in urea concentration (d = 0.80; 95% CI 0.30 to 1.30). In contrast, increased performance was associated with an increased testosterone:cortisol ratio (d = 0.89; 95% CI 0.54 to 1.24). All remaining biomarkers showed no consistent patterns of change with performance. CONCLUSIONS: Many biomarkers were altered with intensified training but not in a manner related to changes in exercise performance. Neutrophils, glutamine, urea and the testosterone:cortisol ratio exhibited some evidence of directional changes that corresponded with performance changes therefore indicating potential to track performance. Additional investigations of the potential for these markers to track altered performance are warranted.