While BFR conferred slightly greater haemodynamic stress than CON, this was lower for walking than leg-press exercise. Given similar response magnitudes between YA and OA, these data support aerobic exercise being a more appropriate BFRE for prescription in older adults that may contribute to limiting the effects of age-related muscle atrophy.

This study assessed accelerometry-derived relative exercise intensity during elite women's basketball match play. The influence of player position/role and match period on relative exercise intensities was evaluated. Ten basketballers wore accelerometers during a Yo-Yo intermittent recovery test (Yo-Yo-IR1) and 18 competitive matches. Relative exercise intensity was quantified using predicted oxygen consumption reserve determined using correlations from Yo-Yo-IR1. Total time, bout frequency and bout duration were calculated in seven intensity zones and compared between quarters, positions (back-court front-court) and roles (starters bench). Back-court players spent 6.0±1.9% more match time performing supramaximal activity when compared to front-court players (p<0.045). Back-court players experienced more supramaximal bouts (125±37 52±36; p=0.031) of greater average duration (2.1±0.4 1.4±0.2 s; p=0.021) and maximum duration (7±2 3±1 s; p=0.020). More sedentary to very light activity was observed in the 2 and 4 quarters compared to the 1 and 3 quarters (p<0.05). Despite reduced playing time, bench players performed similar amounts of maximal and supramaximal exercise when compared to starters (p≥0.279). Player position, role and match periods influence the demands of women's basketball; these factors should be considered when designing match-specific conditioning programs.

This study assessed the construct validity of accelerometry-derived net force to quantify the external demands of basketball movements. Twenty-eight basketballers completed the Yo-Yo intermittent recovery test (Yo-Yo-IR1) and basketball exercise simulation test (BEST). Intensity was quantified using accelerometry-derived average net force (AvF) and PlayerLoad per minute (PL/min). Within-player correlations were determined between intensity and running speed during Yo-Yo-IR1. Measured AvF was determined for movements during the BEST and predicted AvF was calculated using movement speed and correlations from Yo-Yo-IR1. Relationships between AvF and running speed during Yo-Yo-IR1 were nearly perfect (r=0.95, 95% CI: 0.94-0.96; p<0.001) and stronger than correlations between running speed and PL/min (r=0.80, 95% CI: 0.73-0.87; p<0.001). Differences between measured and predicted AvF were small during jogging and running (<1%), but large for basketball movements including jumping, change-of-direction and shuffling (15%-41%). As hypothesised, AvF differed by playing position (11%-16%; <0.001) and reflected the additional demand upon players with larger body mass and lower movement efficiency. Both sprint speed and AvF reduced during the course of the BEST (≤0.013). These findings confirm the construct validity of AvF to quantify the external demand of basketball movements. Accelerometry-derived net force has the potential to quantify the external demands of basketballers during training and competition.

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Despite the International System of Units (SI), as well as several publications guiding researchers on correct use of terminology, there continues to be widespread misuse of mechanical terms such as 'work' in sport and exercise science. A growing concern is the misuse of the term 'load'. Terms such as 'training load' and 'PlayerLoad' are popular in sport and exercise science vernacular. However, a 'load' is a mechanical variable which, when used appropriately, describes a force and therefore should be accompanied with the SI-derived unit of the newton (N). It is tempting to accept popular terms and nomenclature as scientific. However, scientists are obliged to abide by the SI and must pay close attention to scientific constructs. This communication presents a critical reflection on the use of the term 'load' in sport and exercise science. We present ways in which the use of this term breaches principles of science and provide practical solutions for ongoing use in research and practice.

Accelerometry-derived exercise dose (intensity × duration) was assessed throughout a competitive basketball season. Nine elite basketballers wore accelerometers during a Yo-Yo intermittent recovery test (Yo-Yo-IR1) and during three two-week blocks of training that represented phases of the season defined as easy, medium, and hard based on difficulty of match schedule. Exercise dose was determined using accumulated impulse (accelerometry-derived average net force × duration). Relative exercise intensity was quantified using linear relationships between average net force and oxygen consumption during the Yo-Yo-IR1. Time spent in different intensity zones was computed. Influences of match schedule difficulty and playing position were evaluated. Exercise dose reduced for recovery and pre-match tapering sessions during the medium match schedule. Exercise dose did not vary during the hard match schedule. Exercise dose was not different between playing positions. The majority of activity during training was spent performing sedentary behaviour or very light intensity activity (64.3 ± 6.1%). Front-court players performed a greater proportion of very light intensity activity (mean difference: 6.8 ± 2.8%), whereas back-court players performed more supramaximal intensity activity (mean difference: 4.5 ± 1.0%). No positional differences existed in the proportion of time in all other intensity zones. Objective evaluation of exercise dose might allow coaches to better prescribe and monitor the demands of basketball training.

This study assessed the influence of exercise prescription on the objectively measured exercise dose in basketball. Intensity (RPE) and volume (sRPE) were prescribed by a professional coach on a drill-by-drill basis during pre-season training for nine elite basketball players. Training drills were classified by prescribed intensity (easy-moderate, moderate-hard, hard–very hard, and very hard-maximal) and type (warm-up, skill-development, offensive- and defensive-technical/tactical, or match-simulation). Exercise intensity was objectively quantified using accelerometry-derived average net force (AvFNet) and time spent in accelerometry-derived relative intensity zones. The volume of exercise (exercise dose) was objectively quantified using accumulated impulse (AvFNet × duration). Relationships between prescribed volume and exercise dose were explored by correlations between sRPE and drill-by-drill accumulation of sRPE (dRPE) with impulse. Very hard-maximal drill intensity was greater than hard-very hard (p = 0.011), but not moderate-hard (p = 0.945). Very hard-maximal drills included the most time performing Supra-maximal intensity (>100% V ˙ O2R) efforts (p < 0.001), suggesting that intensity prescription was based upon the amount of high-intensity exercise. Correlations between impulse with sRPE and dRPE were moderate (r = 0.401, p = 0.197) and very-large (r = 0.807, p = 0.002), respectively, demonstrating that the coach misinterpreted the accumulative effect of drill volume over an entire training session. Overall, a mismatch existed between exercise prescription and exercise dose. Objective monitoring might assist coaches to improve precision of exercise prescription.

Staunton, CA, Stanger, JJ, Wundersitz, DW, Gordon, BA, Custovic, E, and Kingsley, MI. Criterion validity of a MARG sensor to assess countermovement jump performance in elite basketballers. J Strength Cond Res XX(X): 000-000, 2018-This study assessed the criterion validity of a magnetic, angular rate, and gravity (MARG) sensor to measure countermovement jump (CMJ) performance metrics, including CMJ kinetics before take-off, in elite basketballers. Fifty-four basketballers performed 2 CMJs on a force platform with data simultaneously recorded by a MARG sensor located centrally on the player's back. Vertical accelerations recorded from the MARG sensor were expressed relative to the direction of gravity. Jumps were analyzed by a blinded assessor and the best jump according to the force platform was used for comparison. Pearson correlation coefficients (r) and mean bias with 95% ratio limits of agreement (95% RLOA) were calculated between the MARG sensor and the force platform for jumps performed with correct technique (n = 44). The mean bias for all CMJ metrics was less than 3%. Ninety-five percent RLOA between MARG- and force platform-derived flight time and jump height were 1 ± 7% and 1 ± 15%, respectively. For CMJ performance metrics before takeoff, impulse displayed less random error (95% RLOA: 1 ± 13%) when compared with mean concentric power and time to maximum force displayed (95% RLOA: 0 ± 29% and 1 ± 34%, respectively). Correlations between MARG and force platform were significant for all CMJ metrics and ranged from large for jump height (r = 0.65) to nearly perfect for mean concentric power (r = 0.95). Strong relationships, low mean bias, and low random error between MARG and force platform suggest that MARG sensors can provide a practical and inexpensive tool to measure impulse and flight time-derived CMJ performance metrics.