External Load Fluctuations Across an Amateur Athletic Union Basketball Season.

ABSTRACT: Kutson, CW, Russell, JL, Strack, D, Coutts, AJ, and McLean, BD. External load fluctuations across an Amateur Athletic Union basketball season. J Strength Cond Res 38(3): 592-598, 2024-Amateur Athletic Union (AAU) competitions are an important component of the developmental pathway for youth basketball athletes. Despite its relative importance, there is currently a paucity of research investigating the physical demands in AAU basketball. Therefore, the purpose of this study was to examine the physical demands encountered over the course of an AAU basketball season. External training load was quantified using inertial sensors (Catapult T6) from one male AAU basketball team (age: 17.5 ± 0.5 years, height: 197.3 ± 10.0 cm, and mass: 89.4 ± 11.6 kg) over the course of the 2021 AAU season and categorized post hoc into high-, medium-, and low-minute groups based on mean playing minutes. After player categorization, 2 linear mixed models were constructed, one for PlayerLoad (PL) and one for duration, to examine the differences across player category, month of the season, and activity types (practices or games). The results show that the highest training loads were encountered by high-minute players, who had total PLs of 9,766 ± 1,516 AU, 13,207 ± 2,561 AU, and 7,071 ± 2,122 AU during April, May, and June, respectively. Highly variable training loads were also evident over the course of a season, with peak PL values as high as 4,921 AU per week. Practitioners should be aware that AAU basketball players experience variable loads throughout the season, which peak around congested competition/tournament periods. In addition, players with high game minutes accumulate the most load over the course of a season. This information may be used to better inform planning and periodizing strategies during developmental phases.

The Relationship Between Mental Fatigue and Shooting Performance Over the Course of a National Collegiate Athletic Association Division I Basketball Season.

ABSTRACT: Daub, BD, McLean, BD, Heishman, AD, Peak, KM, and Coutts, AJ. The relationship between mental fatigue and shooting performance over the course of a National Collegiate Athletic Association Division I basketball season. J Strength Cond Res 38(2): 334-341, 2024-The aim of this investigation was to examine the presence of mental fatigue and concurrent changes in shooting performance across various experimental weeks throughout a National Collegiate Athletic Association (NCAA) basketball season. Fifteen elite male NCAA Division I collegiate basketball players (age 20.2 ± 1.2 years, height 199.3 ± 7.1 cm, and body mass 93.1 ± 8.6 kg) volunteered for this study. Mental fatigue and basketball shooting performance was evaluated at 4 timepoints with varying seasonal demands: high game volume (GAME), high academic load (ACADEMIC), no games and no academic load (PRACTICE), and standard number of games and academic requirements (TYPICAL). Subjective mental fatigue increased significantly ( p ≤ 0.05) from Pre to Post brief psychomotor vigilance test (PVT-B) measurements at the end of the ACADEMIC week ( p = 0.002, d = 1.51) and from beginning to end of the ACADEMIC week ( p < 0.001, d = 2.21). Ratings of mental effort were significantly increased during the ACADEMIC week ( p < 0.001, d = 1.67). Recovery stress questionnaire (REST-Q) showed significant differences between week GAME and ACADEMIC with an increase in Social Stress ( p = 0.001, d = 0.84), Fatigue ( p = 0.021, d = 1.12), Disturbed Breaks ( p = 0.024, d = 0.57), and Emotional Exhaustion ( p = 0.035, d = 0.75). Lower shooting performance was observed during the ACADEMIC week from Pre to Post ( p = 0.009, d = 0.35) and higher scores Pre to Post in the TYPICAL week ( p = 0.008, d = 0.25). Basketball shooting performance was significantly reduced after increased levels of mental fatigue stemming from added academic stress. In addition, an increase in sport-specific training or games had no effect on subsequent basketball shooting performance. Special consideration should be given by coaches around examination periods because the existence of academic stressors can influence basketball shooting performance.

Sensitivity of Countermovement Jump Variables in Professional Rugby Union Players Within a Playing Season.

ABSTRACT: Howarth, DJ, McLean, BD, Cohen, DD, and Coutts, AJ. Sensitivity of countermovement jump variables in professional rugby union players within a playing season. J Strength Cond Res 37(7): 1463-1469, 2023-The aim of this study was to explore the measurement sensitivity of a wide range of countermovement jump (CMJ) variables to a full European professional rugby union season. A secondary purpose was to compare 3 different data treatment methods for the calculation of CMJ variables. Twenty-nine professional rugby union players (mean ± SD; age 24 ± 4 years, height 183.7 ± 8.0 cm, body mass 101.6 ± 10.7 kg) completed a minimum of 12 CMJ testing sessions on Thursdays-a day preceded by a rest day and a minimum of 96 hours after a match-throughout a season. Measurement sensitivity, quantified by signal-to-noise ratio (SNR), was determined for 74 CMJ variables and was calculated by dividing the signal, (week-to-week variation expressed as a coefficient of variation [CV%]) by the noise (interday test/retest reliability expressed as CV%). We also identified variables which had no overlap between the 95% confidence intervals (CIs) for the signal and the noise. The 3 data treatment methods for comparison were (a) mean output across 3 jump trials (Mean3), (b) single output from the trial with the highest jump (BestJH), and (c) the trial with the highest flight time to contraction time ratio (BestFTCT). Most variables had an SNR >1.0 (Mean3 = 60/74; BestFTCT = 59/74; BestJH = 48/74). Fewer variables displayed a nonoverlap of 95% CIs (Mean3 = 23/60; BestFTCT = 22/59; BestJH = 16/48). Most CMJ variables during a professional rugby season demonstrated a signal that exceeded measured noise (SNR > 1.0) and that using the Mean3 or BestFTCT data treatment methods yields a greater number of variables considered sensitive within a season (i.e., SNR > 1.0) than when using BestJH. We also recommend the calculation of the 95% CIs for both signal and noise, with nonoverlap indicative of a greater probability that the responsiveness of the variable at team level (i.e., SNR) also applies at the individual level. As sensitivity analysis is cohort and environment specific, practitioners should conduct a sensitivity analysis using internal signal and noise data to inform their own monitoring protocols.

Finding the Signal in the Noise-Interday Reliability and Seasonal Sensitivity of 84 Countermovement Jump Variables in Professional Basketball Players.

ABSTRACT: Mercer, RAJ, Russell, JL, McGuigan, LC, Coutts, AJ, Strack, DS, and McLean, BD. Finding the signal in the noise-interday reliability and seasonal sensitivity of 84 countermovement jump variables in professional basketball players. J Strength Cond Res 37(2): 394-402, 2023-This study examined the measurement characteristics of countermovement jump (CMJ) variables in basketball athletes using different variable selection criteria. Test-retest reliability (noise) and seasonal variability (signal) CMJ data were collected from 13 professional basketball athletes playing for the same club throughout 1 competitive season. Interday reliability (coefficient of variation [CV] and intraclass correlation coefficients) were calculated over 3 preseason tests conducted on 3 consecutive days. To evaluate sensitivity, signal-to-noise ratio (SNR) was calculated by dividing seasonal variability (CV) from 8 in-season CMJ tests (collected from November to February) by preseason reliability (CV). Players performed 3 CMJs each testing day, and 3 data analysis techniques were applied: a single variable from the trial with either the best jump height (BestJH; calculated by flight time) or the best flight time to contraction time (BestFT:CT) and mean output across 3 jumps (Mean3). Mean3 was the most reliable data analysis technique, with 79 and 82 of 84 variables displaying lower interday CVs compared with BestJH and BestFT:CT, respectively. Overall, many CMJ measures display seasonal changes that are greater than the inherent noise, with 77 variables producing SNR of >1.00 for Mean3 compared with 65 and 58 variables for BestJH and BestFT:CT, respectively. To improve reliability and sensitivity, it is recommended that practitioners use the average of multiple CMJ trials and regularly reassess measurement characteristics specific to their cohort and environment.

Establishing the Noise: Interday Ecological Reliability of Countermovement Jump Variables in Professional Rugby Union Players.

ABSTRACT: Howarth, DJ, Cohen, DD, McLean, BD, and Coutts, AJ. Establishing the noise: interday ecological reliability of countermovement jump variables in professional rugby union players. J Strength Cond Res 36(11): 3159-3166, 2022-The purpose of this study was to examine the interday "ecological" reliability of a wide range of ground reaction force-derived countermovement jump (CMJ) variables. Thirty-six male, professional rugby union players performed 3 CMJs on 4 separate days over an 8-day period during the first week of preseason. We calculated reliability for 86 CMJ variables across 5 interday combinations using 2 criteria: mean output across 3 jump trials (Mean 3 ) and single output from the highest jump (Best JH ). Interday coefficient of variation (CV) of the 86 variables in each CMJ phase, for Mean 3 and Best JH , respectively, ranged between concentric = 2-11% and 2-13%; eccentric = 1-45% and 1-107%; and landing = 4-32% and 6-45%. Mean 3 interday CV was lower in all 86 variables across every interday combination, compared with Best JH . CVs were lower in our cohort than previous studies, particularly for eccentric phase variables. There was no meaningful difference between interday conditions, suggesting any 2-day combination conducted within the first 8 days of preseason, represents a measure of "noise." We did not apply arbitrary reliability "cut-offs" used in previous work (e.g., CV <10%); therefore, our analysis provides reference reliability for a wide range of CMJ variables. However, we recommend that practitioners assess reliability in their athletes, as it is likely to be environment, protocol, and cohort specific.

Changes in Running Performance After Four Weeks of Interval Hypoxic Training in Australian Footballers: A Single-Blind Placebo-Controlled Study.

There is a paucity of data examining the impact of high-intensity interval hypoxic training (IHT) on intermittent running performance. This study assessed the effects of IHT on 17 amateur Australian Footballers, who completed 8 interval treadmill running sessions (IHT [FIO2 = 15.1%] or PLACEBO) over 4 weeks, in addition to normoxic football (2 per week) and resistance (2 per week) training sessions. To match relative training intensity, absolute IHT intensity reduced by 6% of normoxic vV[Combining Dot Above]O2peak compared with PLACEBO. Before and after the intervention, performance was assessed by Yo-Yo intermittent recovery test level 2 (Yo-Yo IR2) and a self-paced team sport running protocol. Standardized effect size statistics were calculated using Cohen's d to compare between the interventions. Compared with PLACEBO, IHT subjects experienced (a) smaller improvements in Yo-Yo IR2 performance (Cohen's d = -0.42 [-0.82 to -0.02; 90% confidence interval]); (b) similar increases in high-intensity running distance during the team sport protocol (d = 0.17 [-0.50 to 0.84]); and (c) greater improvements in total distance (d = 0.72 [0.33-1.10]) and distance covered during low-intensity activity (d = 0.59 [-0.07 to 1.11]) during the team sport protocol. The lower absolute training intensity of IHT may explain the smaller improvements in Yo-Yo IR2 performance in the hypoxic group. Conversely, the data from the self-paced protocol suggest that IHT may positively influence pacing strategies in team sport athletes. In conclusion, IHT alters pacing strategies in team sport athletes (i.e., increased distance covered during low-intensity activity). However, IHT leads to smaller improvements in externally paced high-intensity intermittent running performance (i.e., Yo-Yo IR2), which may be related to a reduced absolute training intensity during IHT sessions.

A self-paced intermittent protocol on a non-motorised treadmill: a reliable alternative to assessing team-sport running performance.

This study assessed the reliability of a 'self-paced' 30-min, team-sport running protocol on a Woodway Curve 3.0 non-motorised treadmill (NMT). Ten male team-sport athletes (20.3 ± 1.2 y, 74.4 ± 9.7 kg, VO2peak 57.1 ± 4.5 ml·kg(-1)·min(-1)) attended five sessions (VO2peak testing + familiarisation; four reliability trials). The 30-min protocol consisted of three identical 10-min activity blocks, with visual and audible commands directing locomotor activity; however, actual speeds were self-selected by participants. Reliability of variables was estimated using typical error ± 90% confidence limits expressed as a percentage [coefficient of variation (CV)] and intraclass correlation coefficient. The smallest worthwhile change (SWC) was calculated as 0.2 × between participant standard deviation. Peak/mean speed and distance variables assessed across the 30-min protocol exhibited a CV < 5%, and < 6% for each 10-min activity block. All power variables exhibited a CV < 7.5%, except walking (CV 8.3-10.1%). The most reliable variables were maximum and mean sprint speed (CV < 2%). All variables produced a CV% greater than the SWC. A self-paced, team-sport running protocol performed on a NMT produces reliable speed/distance and power data. Importantly, a single familiarisation session allowed for adequate test-retest reliability. The self-paced design provides an ecologically-valid alternative to externally-paced team-sport running simulations. Key pointsSelf-paced team-sport running protocols on a curved NMT that closely match the locomotor demands of competition deliver reliable test-retest measures of speed, distance and power.Such protocols may be sensitive to changes in running profile following an intervention that may not be detectable during externally-paced protocols.One familiarisation session is adequate to ensure test-retest reliability.

Year-to-year variability in haemoglobin mass response to two altitude training camps.

AIM: To quantify the year-to-year variability of altitude-induced changes in haemoglobin mass (Hb(mass)) in elite team-sport athletes. METHODS: 12 Australian-Footballers completed a 19-day (ALT1) and 18-day (ALT2) moderate altitude (∼2100 m), training camp separated by 12 months. An additional 20 participants completed only one of the two training camps (ALT1 additional n=9, ALT2 additional n=11). Total Hb(mass) was assessed using carbon monoxide rebreathing before (PRE), after (POST1) and 4 weeks after each camp. The typical error of Hb(mass) for the pooled data of all 32 participants was 2.6%. A contemporary statistics analysis was used with the smallest worthwhile change set to 2% for Hb(mass). RESULTS: POST1 Hb(mass) was very likely increased in ALT1 (3.6 ± 1.6%, n=19; mean ± ∼90 CL) as well as ALT2 (4.4 ± 1.3%, n=23) with an individual responsiveness of 1.3% and 2.2%, respectively. There was a small correlation between ALT1 and ALT2 (R=0.21, p=0.59) for a change in Hb(mass), but a moderately inverse relationship between the change in Hb(mass) and initial relative Hb(mass) (g/kg (R=-0.51, p=0.04)). CONCLUSIONS: Two preseason moderate altitude camps 1 year apart yielded a similar (4%) mean increase in Hb(mass) of elite footballers, with an individual responsiveness of approximately half the group mean effect, indicating that most players gained benefit. Nevertheless, the same individuals generally did not change their Hb(mass) consistently from year to year. Thus, a 'responder' or 'non-responder' to altitude for Hb(mass) does not appear to be a fixed trait.

Altitude training and haemoglobin mass from the optimised carbon monoxide rebreathing method determined by a meta-analysis.

OBJECTIVE: To characterise the time course of changes in haemoglobin mass (Hbmass) in response to altitude exposure. METHODS: This meta-analysis uses raw data from 17 studies that used carbon monoxide rebreathing to determine Hbmass prealtitude, during altitude and postaltitude. Seven studies were classic altitude training, eight were live high train low (LHTL) and two mixed classic and LHTL. Separate linear-mixed models were fitted to the data from the 17 studies and the resultant estimates of the effects of altitude used in a random effects meta-analysis to obtain an overall estimate of the effect of altitude, with separate analyses during altitude and postaltitude. In addition, within-subject differences from the prealtitude phase for altitude participant and all the data on control participants were used to estimate the analytical SD. The 'true' between-subject response to altitude was estimated from the within-subject differences on altitude participants, between the prealtitude and during-altitude phases, together with the estimated analytical SD. RESULTS: During-altitude Hbmass was estimated to increase by ∼1.1%/100 h for LHTL and classic altitude. Postaltitude Hbmass was estimated to be 3.3% higher than prealtitude values for up to 20 days. The within-subject SD was constant at ∼2% for up to 7 days between observations, indicative of analytical error. A 95% prediction interval for the 'true' response of an athlete exposed to 300 h of altitude was estimated to be 1.1-6%. CONCLUSIONS: Camps as short as 2 weeks of classic and LHTL altitude will quite likely increase Hbmass and most athletes can expect benefit.

Impacts of mental fatigue and sport specific film sessions on basketball shooting tasks.

PURPOSE: The aim of this investigation was to examine the impact of mental fatigue on basketball specific shooting performance, utilising the newly developed basketball Standardized Shooting Task (SST). METHODS: Fifteen male elite NCAA Division 1 collegiate basketball players (Age 20.2 ± 1.2 y, height 199.3 ± 7.1 cm, body mass 93.1 ± 8.6 kg) volunteered to participate in a randomised, counterbalanced crossover design undergoing three conditions (Control, Stroop, and Film). The task, performed on three consecutive days, was comprised of 60 free throw attempts followed by a 4-minute spot-to-spot shooting. RESULTS: Visual Analog Scales revealed significantly higher levels of mental fatigue following the Stroop (54.2 ± 24.5) condition compared to the Control (24.5 ± 16.2) and higher levels of mental effort in the Stroop (61.0 ± 31.3) and Film (49.9 ± 27.7) compared to the Control (14.0 ± 18.5). No significant differences were observed for Motivation among groups (p > 0.05). There was a significant decrease (p = 0.006) in number of shots made in 4-minutes (MAKE4MIN; control = 49.5 ± 10.2, Stroop = 44.0 ± 10.6, and Film = 45.1 ± 11.7) and shots missed in 4-minutes (MISS4MIN; control = 27.3 ± 7.0, Stroop = 30.9 ± 7.1, and Film = 30.9 ± 7.6). No significant differences were detected for any other performance variables. CONCLUSION: These data demonstrate that mental fatigue negatively impacts basketball shooting performance in elite collegiate basketball players. We suggest that practitioners and coaches encourage athletes to abstain from cognitively demanding tasks prior to basketball competition.

Basketball shooting performance was significantly reduced following acutely increased levels of mental fatigue.This study provides novel preliminary evidence that a sport-specific Film session of 30-minutes in duration (or longer) requires a large amount of mental effort and may also have a detrimental effect on subsequent basketball shooting performanceThe outcomes of this study suggest that practitioners and coaches should encourage elite collegiate basketball players to abstain from potential cognitively demanding tasks prior to practice and games when shooting performance is required.

A Conceptual Exploration of Hamstring Muscle-Tendon Functioning during the Late-Swing Phase of Sprinting: The Importance of Evidence-Based Hamstring Training Frameworks.

An eccentrically lengthening, energy-absorbing, brake-driven model of hamstring function during the late-swing phase of sprinting has been widely touted within the existing literature. In contrast, an isometrically contracting, spring-driven model of hamstring function has recently been proposed. This theory has gained substantial traction within the applied sporting world, influencing understandings of hamstring function while sprinting, as well as the development and adoption of certain types of hamstring-specific exercises. Across the animal kingdom, both spring- and motor-driven muscle-tendon unit (MTU) functioning are frequently observed, with both models of locomotive functioning commonly utilising some degree of active muscle lengthening to draw upon force enhancement mechanisms. However, a method to accurately assess hamstring muscle-tendon functioning when sprinting does not exist. Accordingly, the aims of this review article are three-fold: (1) to comprehensively explore current terminology, theories and models surrounding muscle-tendon functioning during locomotion, (2) to relate these models to potential hamstring function when sprinting by examining a variety of hamstring-specific research and (3) to highlight the importance of developing and utilising evidence-based frameworks to guide hamstring training in athletes required to sprint. Due to the intensity of movement, large musculotendinous stretches and high mechanical loads experienced in the hamstrings when sprinting, it is anticipated that the hamstring MTUs adopt a model of functioning that has some reliance upon active muscle lengthening and muscle actuators during this particular task. However, each individual hamstring MTU is expected to adopt various combinations of spring-, brake- and motor-driven functioning when sprinting, in accordance with their architectural arrangement and activation patterns. Muscle function is intricate and dependent upon complex interactions between musculoskeletal kinematics and kinetics, muscle activation patterns and the neuromechanical regulation of tensions and stiffness, and loads applied by the environment, among other important variables. Accordingly, hamstring function when sprinting is anticipated to be unique to this particular activity. It is therefore proposed that the adoption of hamstring-specific exercises should not be founded on unvalidated claims of replicating hamstring function when sprinting, as has been suggested in the literature. Adaptive benefits may potentially be derived from a range of hamstring-specific exercises that vary in the stimuli they provide. Therefore, a more rigorous approach is to select hamstring-specific exercises based on thoroughly constructed evidence-based frameworks surrounding the specific stimulus provided by the exercise, the accompanying adaptations elicited by the exercise, and the effects of these adaptations on hamstring functioning and injury risk mitigation when sprinting.

Maximal power output and perceptual fatigue responses during a Division I female collegiate soccer season.

The purpose of this study was to investigate how maximal power output (PMAX), as measured via the inertial load cycling technique, changes throughout a collegiate soccer season in relation to training load completed. The current investigation took place throughout the 2010 Big XII soccer season. Nineteen Division I female collegiate soccer players (age: 19.9 ± 1.2 years, stature: 165.1 ± 6.6 cm, mass: 61.0 ± 6.8 kg) from the same team completed regular inertial load cycling tests and perceptual fatigue questionnaires throughout the season. Players were divided into STARTERS and NON-STARTERS based on percentage of matches started throughout the season. The results demonstrated that STARTERS experience much greater load throughout the season than NON-STARTERS (2247 ± 176 arbitrary units [AU] and 1585 ± 174 AU, p < 0.05), accounted for by increased load during matches. This increased load throughout the season was accompanied by decline in PMAX in STARTERS (to 92.3 ± 6.6%, p < 0.05), whereas PMAX was maintained in NON-STARTERS for the duration of the season (99.0 ± 4.9%). Furthermore, STARTERS experienced greater muscle soreness throughout the in-season period compared with NON-STARTERS. The main finding of this study is that PMAX declined throughout the middle and latter parts of the season in STARTERS, after experiencing significantly greater match loads than NON-STARTERS throughout the season. The current findings, combined with previous investigations, suggest that load needs to be carefully monitored throughout the in-season period to maintain optimal neuromuscular performance throughout a team's entire sporting season.

'Avoidance Preening', Displacement Behavior and Co-Dependency in Professional Team Sport: When Wants Become More Important Than Needs.

An athlete's body plays an important role in their performance and well-being. However, game-relevant skills are better determinants of success, compared with physical fitness, in technically-driven team sports. In the professional era, over utilization of resources, in pursuit of physical optimization, can detract from time spent on priorities. Athletes' non-strategic, time-demanding focus on physical preparation/treatments resembles avian 'avoidance preening', whereby stressful situations trigger birds to excessively preen in place of more productive activities. The purpose of this commentary is to explore the behaviors of resource-rich professional teams and the roles of staff dedicated to optimizing physical performance, including circumstances that foster avoidance behavior and create the potential for practitioners to encourage co-dependent relationships with athletes. To cultivate healthy/productive environments, the following is recommended: I) recognition of non-productive avoidance behaviors; II) eschewing unjustified, fear promoting, pathoanatomical language; III) fostering collaborative approaches; IV) encouraging utilization of psychology services; V) recognizing that optimal physical function and feeling good is rarely the primary goal in professional team sports. Level of Evidence: 5.

Understanding 'monitoring' data-the association between measured stressors and athlete responses within a holistic basketball performance framework.

This study examined associations between cumulative training load, travel demands and recovery days with athlete-reported outcome measures (AROMs) and countermovement jump (CMJ) performance in professional basketball. Retrospective analysis was performed on data collected from 23 players (mean±SD: age = 24.7±2.5 years, height = 198.3±7.6 cm, body mass = 98.1±9.0 kg, wingspan = 206.8±8.4 cm) from 2018-2020 in the National Basketball Association G-League. Linear mixed models were used to describe variation in AROMs and CMJ data in relation to cumulative training load (previous 3- and 10-days), hours travelled (previous 3- and 10-day), days away from the team's home city, recovery days (i.e., no travel/minimal on-court activity) and individual factors (e.g., age, fatigue, soreness). Cumulative 3-day training load had negative associations with fatigue, soreness, and sleep, while increased recovery days were associated with improved soreness scores. Increases in hours travelled and days spent away from home over 10 days were associated with increased sleep quality and duration. Cumulative training load over 3 and 10 days, hours travelled and days away from home city were all associated with changes in CMJ performance during the eccentric phase. The interaction of on-court and travel related stressors combined with individual factors is complex, meaning that multiple athletes response measures are needed to understand fatigue and recovery cycles. Our findings support the utility of the response measures presented (i.e., CMJ and AROMs), but this is not an exhaustive battery and practitioners should consider what measures may best inform training periodization within the context of their environment/sport.

Quantifying Training and Game Demands of a National Basketball Association Season.

Purpose: There are currently no data describing combined practice and game load demands throughout a National Basketball Association (NBA) season. The primary objective of this study was to integrate external load data garnered from all on-court activity throughout an NBA season, according to different activity and player characteristics. Methods: Data from 14 professional male basketball players (mean ± SD; age, 27.3 ± 4.8 years; height, 201.0 ± 7.2 cm; body mass, 104.9 ± 10.6 kg) playing for the same club during the 2017-2018 NBA season were retrospectively analyzed. Game and training data were integrated to create a consolidated external load measure, which was termed integrated load. Players were categorized by years of NBA experience (1-2y, 3-5y, 6-9y, and 10 + y), position (frontcourt and backcourt), and playing rotation status (starter, rotation, and bench). Results: Total weekly duration was significantly different (p < 0.001) between years of NBA playing experience, with duration highest in 3-5 year players, compared with 6-9 (d = 0.46) and 10+ (d = 0.78) year players. Starters experienced the highest integrated load, compared with bench (d = 0.77) players. There were no significant differences in integrated load or duration between positions. Conclusion: This is the first study to describe the seasonal training loads of NBA players for an entire season and shows that a most training load is accumulated in non-game activities. This study highlights the need for integrated and unobtrusive training load monitoring, with engagement of all stakeholders to develop well-informed individualized training prescription to optimize preparation of NBA players.

Measuring Physical Demands in Basketball: An Explorative Systematic Review of Practices.

BACKGROUND: Measuring the physical work and resultant acute psychobiological responses of basketball can help to better understand and inform physical preparation models and improve overall athlete health and performance. Recent advancements in training load monitoring solutions have coincided with increases in the literature describing the physical demands of basketball, but there are currently no reviews that summarize all the available basketball research. Additionally, a thorough appraisal of the load monitoring methodologies and measures used in basketball is lacking in the current literature. This type of critical analysis would allow for consistent comparison between studies to better understand physical demands across the sport. OBJECTIVES: The objective of this systematic review was to assess and critically evaluate the methods and technologies used for monitoring physical demands in competitive basketball athletes. We used the term 'training load' to encompass the physical demands of both training and game activities, with the latter assumed to provide a training stimulus as well. This review aimed to critique methodological inconsistencies, establish operational definitions specific to the sport, and make recommendations for basketball training load monitoring practice and reporting within the literature. METHODS: A systematic review of the literature was performed using EBSCO, PubMed, SCOPUS, and Web of Science to identify studies through March 2020. Electronic databases were searched using terms related to basketball and training load. Records were included if they used a competitive basketball population and incorporated a measure of training load. This systematic review was registered with the International Prospective Register of Systematic Reviews (PROSPERO Registration # CRD42019123603), and approved under the National Basketball Association (NBA) Health Related Research Policy. RESULTS: Electronic and manual searches identified 122 papers that met the inclusion criteria. These studies reported the physical demands of basketball during training (n = 56), competition (n = 36), and both training and competition (n = 30). Physical demands were quantified with a measure of internal training load (n = 52), external training load (n = 29), or both internal and external measures (n = 41). These studies examined males (n = 76), females (n = 34), both male and female (n = 9), and a combination of youth (i.e. under 18 years, n = 37), adults (i.e. 18 years or older, n = 77), and both adults and youth (n = 4). Inconsistencies related to the reporting of competition level, methodology for recording duration, participant inclusion criteria, and validity of measurement systems were identified as key factors relating to the reporting of physical demands in basketball and summarized for each study. CONCLUSIONS: This review comprehensively evaluated the current body of literature related to training load monitoring in basketball. Within this literature, there is a clear lack of alignment in applied practices and methodological framework, and with only small data sets and short study periods available at this time, it is not possible to draw definitive conclusions about the true physical demands of basketball. A detailed understanding of modern technologies in basketball is also lacking, and we provide specific guidelines for defining and applying duration measurement methodologies, vetting the validity and reliability of measurement tools, and classifying competition level in basketball to address some of the identified knowledge gaps. Creating alignment in best-practice basketball research methodology, terminology and reporting may lead to a more robust understanding of the physical demands associated with the sport, thereby allowing for exploration of other research areas (e.g. injury, performance), and improved understanding and decision making in applying these methods directly with basketball athletes.

Blood Volumes Following Preseason Heat Versus Altitude: A Case Study of Australian Footballers.

PURPOSE: There is debate as to which environmental intervention produces the most benefit for team sport athletes, particularly comparing heat and altitude. This quasi-experimental study aimed to compare blood volume (BV) responses with heat and altitude training camps in Australian footballers. METHODS: The BV of 7 professional Australian footballers (91.8 [10.5] kg, 191.8 [10.1] cm) was measured throughout 3 consecutive spring/summer preseasons. During each preseason, players participated in altitude (year 1 and year 2) and heat (year 3) environmental training camps. Year 1 and year 2 altitude camps were in November/December in the United States, whereas the year 3 heat camp was in February/March in Australia after a full exposure to summer heat. BV, red cell volume, and plasma volume (PV) were measured at least 3 times during each preseason. RESULTS: Red cell volume increased substantially following altitude in both year 1 (d = 0.67) and year 2 (d = 1.03), before returning to baseline 4 weeks postaltitude. Immediately following altitude, concurrent decreases in PV were observed during year 1 (d = -0.40) and year 2 (d = -0.98). With spring/summer training in year 3, BV and PV were substantially higher in January than temporally matched postaltitude measurements during year 1 (BV: d = -0.93, PV: d = -1.07) and year 2 (BV: d = -1.99, PV: d = -2.25), with year 3 total BV, red cell volume, and PV not changing further despite the 6-day heat intervention. CONCLUSIONS: We found greater BV after training throughout spring/summer conditions, compared with interrupting spring/summer exposure to train at altitude in the cold, with no additional benefits observed from a heat camp following spring/summer training.

Quantifying Physical Demands in the National Basketball Association-Challenges Around Developing Best-Practice Models for Athlete Care and Performance.

The National Basketball Association (NBA) has an extremely demanding competition schedule, requiring its athletes to compete in 82 regular-season games over a 6-mo period (∼3.4 games/wk). Despite the demanding schedule and high value of athletes, there is little public information on the specific game and training demands required to compete in the NBA. Although provisions in the NBA collective-bargaining agreement allow for research designed to improve player health and broaden medical knowledge, such information is sparse in the available literature. In relation to the physical demands of the NBA, the current lack of information likely results from multiple factors including limited understanding of (basketball-related) emerging technologies, impact of specific league rules, and steps taken to protect players in the age of Big Data. This article explores current limitations in describing specific game/training demands in the NBA and provides perspectives on how some of these challenges may be overcome. The authors propose that future collaborations between league entities, NBA clubs, commercial partners, and outside research institutions will enhance understanding of the physical demands in the NBA (and other health- and performance-related areas). More detailed understanding of physical demands (games, practices, and travel) and other health-related areas can augment player-centered decision making, leading to enhanced player care, increased availability, and improved physical performance.

The Fit Matters: Influence of Accelerometer Fitting and Training Drill Demands on Load Measures in Rugby League Players.

PURPOSE: To determine the relationship between drill type and accelerometer-derived loads during various team-sport activities and examine the influence of unit fitting on these loads. METHODS: Sixteen rugby league players were fitted with microtechnology devices in either manufacturer vests or playing jerseys before completing standardized running, agility, and tackling drills. Two-dimensional (2D) and 3-dimensional (3D) accelerometer loads (BodyLoad™) per kilometer were compared across drills and fittings (ie, vest and jersey). RESULTS: When fitted in a vest, 2D BodyLoad was higher during tackling (21.5 [14.8] AU/km) than during running (9.5 [2.5] AU/km) and agility (10.3 [2.7] AU/km). Jersey fitting resulted in more than 2-fold higher BodyLoad during running (2D = 9.5 [2.7] vs 29.3 [14.8] AU/km, 3D = 48.5 [14.8] vs 111.5 [45.4] AU/km) and agility (2D = 10.3 [2.7] vs 21.0 [8.1] AU/km, 3D = 40.4 [13.6] vs 77.7 [26.8] AU/km) compared with a vest fitting. Jersey fitting also produced higher BodyLoad during tackling drills (2D = 21.5 [14.8] vs 27.8 [18.6] AU/km, 3D = 42.0 [21.4] vs 63.2 [33.1] AU/km). CONCLUSIONS: This study provides evidence supporting the construct validity of 2D BodyLoad for assessing collision/tackling load in rugby league training drills. Conversely, the large values obtained from 3D BodyLoad (which includes the vertical load vector) appear to mask small increases in load during tackling drills, rendering 3D BodyLoad insensitive to changes in contact load. Unit fitting has a large influence on accumulated accelerometer loads during all drills, which is likely related to greater incidental unit movement when units are fitted in jerseys. Therefore, it is recommended that athletes wear microtechnology units in manufacturer-provided vests to provide valid and reliable information.

The effect of intense exercise periods on physical and technical performance during elite Australian Football match-play: A comparison of experienced and less experienced players.

OBJECTIVES: The physical and technical responses of experienced (≥5 years) and less experienced (1-4 years) elite Australian Football (AF) players were compared following the most intense passages of match-play. DESIGN: Descriptive cohort study. METHODS: Time-motion analyses were performed using global positioning systems (MinimaxX S4, Catapult Innovations, Melbourne, Australia) on one elite AF team during 13 matches. The global positioning data were categorised into total distance, low-speed activity (0-2.78ms(-1)), moderate-speed running (2.79-4.14ms(-1)) and high-speed running (≥4.15ms(-1)) distances. A standardised 5-point technical coding criteria was used to rate the number and quality of skill involvements during match-play. RESULTS: Following the most intense 3-min running period the experienced players covered greater distances at high-speeds in match quarters two (effect size, ES=0.42±0.30) and three (ES=0.38±0.33) than their less experienced counterparts. Compared with less experienced players, experienced players performed more skill involvements during the second quarter (ES=0.42±0.33) and fourth quarter peak 3-min bouts of exercise intensity (ES=0.40±0.30) and quarter one (ES=0.49±0.29) and three subsequent periods (ES=0.33±0.20). CONCLUSIONS: Less experienced players exhibited greater reductions in physical and technical performance following peak periods of match-play. These findings suggest that training may require a greater emphasis on developing the ability of less experienced players to maintain physical performance and gain possession of the football following intense periods of match-play.