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Key Points• To quantify resistance exercise, it is important to understand the numerous factors contributing to the overall intensity of training, rather than simply the relative load being lifted.• Methods to monitor the external volume load, perceptual training intensity, subjective wellness, and physical performance during resistance exercise all appear useful methods for monitoring resistance training.• Strength coaches should identify which monitoring tools are applicable and viable for their athletes, and should take an integrative approach to resistance training monitoring to help inform their practice.3 AbstractResistance exercise is difficult to quantify due to its inherent complexity with numerous training variables contributing to the training dose (type of exercise, load lifted, training volume, inter-set rest periods and repetition velocity). In addition, the intensity of resistance training is often inadequately determined as the relative load lifted (% 1-repetition maximum), which does not account for the effects of inter-set recovery periods, repetition velocity, or the number of repetitions performed in each set at a given load. Methods to calculate the volume load associated with resistance training, as well as the perceived intensity of individual sets and entire training sessions have been shown to provide useful information regarding the actual training stimulus. In addition, questionnaires to subjectively assess how athletes are coping with the stressors of training and portable technologies to quantify performance variables such as concentric velocity may also be valuable. However, while several methods have been proposed to quantify resistance training, there is not yet consensus regarding how these methods can be best implemented and integrated to complement each other. Therefore, the purpose of this review is to provide practical information for strength coaches to highlight effective methods to assess resistance training, and how they can be integrated into a comprehensive monitoring program.4

Delaney, JA, Cummins, CJ, Thornton, HR, and Duthie, GM. Importance, reliability and usefulness of acceleration measures in team sports. J Strength Cond Res 32(12): 3494-3502, 2018-The ability to accelerate, decelerate, and change direction efficiently is imperative to successful team sports performance. Traditional intensity-based thresholds for acceleration and deceleration may be inappropriate for time-series data and have been shown to exhibit poor reliability, suggesting other techniques may be preferable. This study assessed movement data from one professional rugby league team throughout 2 full seasons and 1 preseason period. Using both 5 and 10 Hz global positioning systems (GPS) units, a range of acceleration-based variables were evaluated for their interunit reliability, ability to discriminate between positions, and associations with perceived muscle soreness. The reliability of 5 Hz global positioning systems for measuring acceleration and deceleration ranged from good to poor (CV = 3.7-27.1%), with the exception of high-intensity deceleration efforts (CV = 11.1-11.8%), the 10 Hz units exhibited moderate-to-good interunit reliability (CV = 1.2-6.9%). Reliability of average metrics (average acceleration/deceleration, average acceleration, and average deceleration) ranged from good to moderate (CV = 1.2-6.5%). Substantial differences were detected between positions using time spent accelerating and decelerating for all magnitudes, but these differences were less clear when considering the count or distance above acceleration/deceleration thresholds. All average metrics detected substantial differences between positions. All measures were similarly related to perceived muscle soreness, with the exception of high-intensity acceleration and deceleration counts. This study has proposed that averaging the acceleration/deceleration demands over an activity may be a more appropriate method compared with threshold-based methods, because a greater reliability between units, while not sacrificing sensitivity to within-subject and between-subject changes.

Rugby league involves frequent periods of high-intensity running including acceleration and deceleration efforts, often occurring at low speeds. Purpose: To quantify the energetic cost of running and acceleration efforts during rugby league competition to aid in prescription and monitoring of training. Methods: Global Positioning System (GPS) data were collected from 37 professional rugby league players across two seasons. Peak values for relative distance, average acceleration/deceleration and metabolic power (Pmet) were calculated for ten different moving average durations (1-10 min), for each position. A mixed-effects model was used to assess the effect of position for each duration, and individual comparisons were made using a magnitude-based inference network. Results: There were almost certainly large differences in relative distance and Pmet between the 10-min window and all moving averages <5 min in duration (ES = 1.21-1.88). Fullbacks, halves and hookers covered greater relative distances than outside backs, edge forwards and middle forwards for moving averages lasting between 2-10 min. Acceleration/deceleration demands were greatest in hookers and halves compared to fullbacks, middle forwards and outside backs. Pmet was greatest in hookers, halves and fullbacks compared to middle forwards and outside backs. Conclusions: Competition running intensities varied by both position and moving average duration. Hookers exhibited the greatest Pmet of all positions, due to high involvement in both attack and defence. Fullbacks also reached high Pmet, possibly due to a greater absolute volume of running. This study provides coaches with match data that can be used for the prescription and monitoring of specific training drills.