The sport of basketball exposes athletes to frequent high intensity movements including sprinting, jumping, accelerations, decelerations and changes of direction during training and competition which can lead to acute and accumulated chronic fatigue. Fatigue may affect the ability of the athlete to perform over the course of a lengthy season. The ability of practitioners to quantify the workload and subsequent fatigue in basketball athletes in order to monitor and manage fatigue levels may be beneficial in maintaining high levels of performance and preventing unfavorable physical and physiological training adaptations. There is currently limited research quantifying training or competition workload outside of time motion analysis in basketball. In addition, systematic research investigating methods to monitor and manage athlete fatigue in basketball throughout a season is scarce. To effectively optimize and maintain peak training and playing performance throughout a basketball season, potential workload and fatigue monitoring strategies need to be discussed.

The sport of American football (AmF) exposes athletes to high-velocity movements and frequent collisions during competition and training, placing them at risk of contact and non-contact injury. Due to the combative nature of the game, the majority of injuries are caused by player contact; however, a significant number are also non-contact soft-tissue injuries. The literature suggests that this mechanism of injury can be prevented through workload monitoring and management. The recent introduction of microtechnology into AmF allows practitioners and coaches to quantify the external workload of training and competition to further understand the demands of the sport. Significant workload differences exist between positions during training and competition; coupling this with large differences in anthropometric and physical characteristics between and within positions suggests that the training response and physiological adaptations will be highly individual. Effective athlete monitoring and management allows practitioners and coaches to identify how athletes are coping with the prescribed training load and, subsequently, if they are prepared for competition. Several evidence-based principles exist that can be adapted and applied to AmF and could decrease the risk of injury and optimise athletic performance.

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Edwards, T, Banyard, HG, Piggott, B, Haff, GG, and Joyce, C. The reliability and minimal detectable change of sprint times and forcevelocity-power characteristics. J Strength Cond Res 36(1): 268-272, 2022-Research has not yet provided critical information for practitioners to determine the minimal detectable change (MDC) in sprint times or force-velocity-power characteristics. Therefore, the aim of this study was to establish the interday reliability and MDC of sprint times and sprint force-velocity-power characteristics in junior Australian football (AF) players. Seventeen players were assessed using a radar device that recorded instantaneous velocity during 3 maximal 30-m sprint accelerations performed on 2 nonconsecutive days. Sprint force, velocity, and power characteristics were derived through inverse dynamics applied to the raw velocity-time data. Relative and absolute reliability was determined by calculating the intraclass correlation coefficient (ICC), coefficient of variation (CV), and MDC. Data analysis was assessed for (a) the first trial, (b) the best trial (the fastest 30-m split time), (c) the average of the first 2 trials, and (d) the average of all 3 trials from each testing session. The main findings were (a) absolute theoretical maximum force (F0), theoretical maximal velocity (V0), absolute and relative maximum power (Pmax), maximum ratio of force (RFmax), maximum velocity (Vmax), and all sprint distance times (5-30 m) displayed acceptable reliability (CV , 10% and ICC .0.75) and 2) the average of 2 and 3 trials was the best method of establishing reliable sprint times and force-velocity-power characteristics between sessions. This study provides important information for practitioners to determine the MDC in sprint times and force-velocity-power characteristics that allow coaches to identify true changes in performance.