These findings reflect a higher prevalence of concussion in high school football players than previously reported in the literature. The ultimate concern associated with unreported concussion is an athlete's increased risk of cumulative or catastrophic effects from recurrent injury. Future prevention initiatives should focus on education to improve athlete awareness of the signs of concussion and potential risks of unreported injury.

Purpose: The aim of this study was to compare the power profile, internal and external workloads, and racing performance between U23 and professional cyclists and between varying rider types across 2 editions of a professional multistage race. Methods: Nine U23 cyclists from a Union Cycliste Internationale “Continental Team” (age 20.8 [0.9] y; body mass 71.2 [6.3] kg) and 8 professional cyclists (28.1 [3.2] y; 63.0 [4.6] kg) participated in this study. Rider types were defined as all-rounders, general classification (GC) riders, and domestiques. Data were collected during 2 editions of a 5-day professional multistage race and split into the following 4 categories: power profile, external and internal workloads, and race performance. Results: The professional group, including domestiques and GC riders, recorded higher relative power profile values after certain amounts of total work (1000–3000 kJ) than the U23 group or all-rounders (P ≤ .001–.049). No significant differences were found for external workload measures between U23 and professional cyclists, nor among rider types. Internal workloads were higher in U23 cyclists and all-rounders (P ≤ .001–.043) compared with professionals, domestiques, and GC riders, respectively. The power profile significantly predicted percentage general classification and Union Cycliste Internationale points (R2 = .90–.99), whereas external and internal workloads did not. Conclusion: These findings reveal that the power profile represents a practical tool to discriminate between professionals and U23 cyclists as well as rider types. The power profile after 1000 to 3000 kJ of total work could be used by practitioners to evaluate the readiness of U23 cyclists to move into the professional ranks, as well as differentiate between rider types.

Emerging trends in technological innovations, data analysis and practical applications have facilitated the measurement of cycling power output in the field, leading to improvements in training prescription, performance testing and race analysis. This review aimed to critically reflect on power profiling strategies in association with the power-duration relationship in cycling, to provide an updated view for applied researchers and practitioners. The authors elaborate on measuring power output followed by an outline of the methodological approaches to power profiling. Moreover, the deriving a power-duration relationship section presents existing concepts of power-duration models alongside exercise intensity domains. Combining laboratory and field testing discusses how traditional laboratory and field testing can be combined to inform and individualize the power profiling approach. Deriving the parameters of power-duration modelling suggests how these measures can be obtained from laboratory and field testing, including criteria for ensuring a high ecological validity (e.g. rider specialization, race demands). It is recommended that field testing should always be conducted in accordance with pre-established guidelines from the existing literature (e.g. set number of prediction trials, inter-trial recovery, road gradient and data analysis). It is also recommended to avoid single effort prediction trials, such as functional threshold power. Power-duration parameter estimates can be derived from the 2 parameter linear or non-linear critical power model: P(t) = W′/t + CP (W′—work capacity above CP; t—time). Structured field testing should be included to obtain an accurate fingerprint of a cyclist’s power profile.

To study the natural recovery from sports concussion, 12 concussed high school football athletes and 12 matched uninjured teammates were evaluated with symptom rating scales, tests of postural balance and cognition, and an event-related fMRI study during performance of a load-dependent working memory task at 13 h and 7 weeks following injury. Injured athletes showed the expected postconcussive symptoms and cognitive decline with decreased reaction time (RT) and increased RT variability on a working memory task during the acute period and an apparent full recovery 7 weeks later. Brain activation patterns showed decreased activation of right hemisphere attentional networks in injured athletes relative to controls during the acute period with a reversed pattern of activation (injured > controls) in the same networks at 7 weeks following injury. These changes coincided with a decrease in self-reported postconcussive symptoms and improved cognitive test performance in the injured athletes. Results from this exploratory study suggest that decreased activation of right hemisphere attentional networks mediate the cognitive changes and postconcussion symptoms observed during the acute period following concussion. Conversely, improvement in cognitive functioning and postconcussive symptoms during the subacute period may be mediated by compensatory increases in activation of this same attentional network.

Background: The purpose of this study was to investigate differences in the power profile derived from training and racing, the training characteristics across a competitive season and the relationships between training and power profile in U23 professional cyclists. Methods: Thirty male U23 professional cyclists (age, 20.0 ± 1.0 years; weight, 68.9 ± 6.9 kg; V˙O2max, 73.7 ± 2.5 mL·kg−1·min−1) participated in this study. The cycling season was split into pre-, early-, mid- and late-season periods. Power data 2, 5, 12 min mean maximum power (MMP), critical power (CP) and training characteristics (Hours, Total Work, eTRIMP, Work·h−1, eTRIMP·h−1, Time<VT1, TimeVT1-2 and Time>VT2) were recorded for each period. Power profiles derived exclusively from either training or racing data and training characteristics were compared between periods. The relationships between the changes in training characteristics and changes in the power profile were also investigated. Results: The absolute and relative power profiles were higher during racing than training at all periods (p ≤ 0.001–0.020). Training characteristics were significantly different between periods, with the lowest values in pre-season followed by late-season (p ≤ 0.001–0.040). Changes in the power profile between early- and mid-season significantly correlated with the changes in training characteristics (p < 0.05, r = −0.59 to 0.45). Conclusion: These findings reveal that a higher power profile was recorded during racing than training. In addition, training characteristics were lowest in pre-season followed by late-season. Changes in training characteristics correlated with changes in the power profile in early- and mid-season, but not in late-season. Practitioners should consider the influence of racing on the derived power profile and adequately balance training programs throughout a competitive season.