Comparison of the most demanding scenarios during different in-season training sessions and official matches in professional basketball players.

The purpose of this study was to compare physical demands during the most demanding scenarios (MDS) of different training sessions and official matches in professional basketball players across playing positions. Thirteen professional basketball players were monitored over a 9-week competitive season using a local positioning system. Peak physical demands included total distance, distance covered at > 18 km·h-1, distance and number of accelerations (≥ 2 m∙s-2) and decelerations (≤ -2 m∙s-2) over a 60-second epoch. Analysis of variance for repeated measures, Bonferroni post-hoc tests and standardised Cohen's effect size (ES) were calculated. Overall, almost all physical demands during the MDS of training were lower (-6.2% to -35.4%) compared to official matches. The only variable that surpassed competition demands was distance covered at > 18 km·h-1, which presented moderate (ES = 0.61, p = 0.01) and small (ES = 0.48, p > 0.05) increases during training sessions four and three days before a competition, respectively. Conversely, the two previous practices before match day presented trivial to very large decreases (ES = 0.09-2.66) in all physical demands. Furthermore, centres achieved the lowest peak value in total distance covered during matches, forwards completed the greatest peak distance at > 18 km·h-1, and guards performed the greatest distance and number of high-intensity accelerations and decelerations. In conclusion, physical demands during the MDS of different training sessions across the microcycle failed to match or surpass peak values during official matches, which should be considered when prescribing a training process intended to optimise the MDS of match play.

The Recovery Umbrella in the World of Elite Sport: Do Not Forget the Coaching and Performance Staff.

In the field of sports science, the recovery umbrella is a trending topic, and even more so in the world of elite sports. This is evidenced by the significant increase in scientific publications during the last 10 years as teams look to find a competitive edge. Recovery is recognized to be an integral component to assist athlete preparation in the restoration of physical and psychological function, and subsequently, performance in elite team sports athletes. However, the importance of recovery in team staff members (sports coaches and performance staff) in elite sports appears to be a forgotten element. Given the unrelenting intense nature of daily tasks and responsibilities of team staff members, the elite sports environment can predispose coaches to increased susceptibility to psycho-socio physiological fatigue burden, and negatively affect health, wellbeing, and performance. Therefore, the aim of this opinion was to (1) develop an educational recovery resource for team staff members, (2) identify organizational task-specific fatigue indicators and barriers to recovery and self-care in team staff members, and (3) present recovery implementation strategies to assist team staff members in meeting their organizational functions. It is essential that we do not forget the coaching and performance staff in the recovery process.

Differences in Physical Demands between Game Quarters and Playing Positions on Professional Basketball Players during Official Competition.

The purpose of this study was to compare physical demands between game quarters and specific playing positions during official basketball competition. Thirteen professional male basketball players from the Spanish 2nd Division were monitored across all 17 regular-season home games. Physical demands were analyzed using a local positioning system (WIMU PRO™, Realtrack Systems S.L., Almería, Spain) and included peak velocity, total distance covered, high-speed running (>18 km·h-1), player load, jumps (>3G), impacts (>8G) and high-intensity accelerations (≥2 m·s-2) and decelerations (≤-2 m·s-2). A linear mixed model was used to test statistical significance (p < 0.05) between independent variables. Furthermore, standardized Cohen's effect size (ES) and respective 90% confidence intervals were also calculated. There was an overall decrease in all variables between the first and fourth quarter during competition. Specifically, total distance covered (p < 0.001; ES = -1.31) and player load (p < 0.001; ES = -1.27) showed large effects between the first and last period. Regarding differences between positions, guards presented significant increased values compared to centers (p = 0.04; ES = 0.51), whereas centers achieved significant larger results and moderate effects in comparison to guards in peak velocity (p = 0.01; ES = 0.88) and jumps (p = 0.04; ES = 0.86). In conclusion, physical demands vary between game quarters and playing positions during official competition and these differences should be considered when designing training drills to optimize game performance.

Match Activities in Basketball Games: Comparison Between Different Competitive Levels.

Ferioli, D, Schelling, X, Bosio, A, La Torre, A, Rucco, D, and Rampinini, E. Match activities in basketball games: comparison between different competitive levels. J Strength Cond Res 34(1): 172-182, 2020-This study examined the (a) differences in the activity demands of official basketball games between different competitive levels (from elite to amateur levels) among a large cohort of adult male players and (b) match-to-match variations of basketball physical demands. Video-based time-motion analysis (TMA) was performed to assess the players' physical activity among 136 players. Match-to-match variations were determined analyzing 2 consecutive matches of the same level on 35 players. The frequency of occurrence (n per minutes) and the duration in percentage of playing time were calculated for high-intensity activity (HIA), moderate-intensity activity (MIA), low-intensity activity (LIA), and recovery (REC). Division I performed an almost certain greater number of HIA, MIA, and total actions per minutes of playing time compared with Division II that performed similarly to Division III. Division VI performed a likely-to-very likely lower number of LIA, MIA, and total actions per minute compared with Division III. Division I spent almost certain greater playing time competing in HIA and MIA compared with lower divisions. Time spent at REC was very likely greater in Division VI compared with all other Divisions. The frequency of occurrence was less reliable than percentage duration of game activities. Matches of different competitive levels are characterized by different physical activities. The ability to sustain greater intermittent workloads and HIA, and the ability to quickly recover from high-intensity phases during competitions should be considered as key components of basketball. The match-to-match variations values observed in this study might be useful to correctly interpret individual TMA data.

Brief ideas about evidence-based recovery in team sports.

Performance in team sports is the expression of complex, dynamic, interactive, and multidimensional processes. It is now well-established that optimum recovery after practice or match is a key factor of team sport performance. During season and tournaments, improving recovery could offer an advantage for following performance. As a consequence of the professionalization of different roles in staffs, new particular roles have been developed within the team sports physician core in order to improve recovery protocols. Presently, scientific literature presents a big amount of methods used to enhance recovery based on the type of practice, time between session or competitions and equipment and/or staff accessible. These practices, usually used by teams are related to: ergonutritional, water therapy, massages techniques, stretching compression garments, sleep strategies and psychological implements. Besides, travel fatigue has been recognized by athletes and coaches as a challenging problem that could benefit from practical solutions. Nowadays, players have to play a lot of matches without enough time to recover among them, therefore the use of well-managed recovery can lead to a competitive advantage. Although the main purpose of applied sport sciences investigation is to categorize the protocols as well as providing approaches for individual recovery, the stages to recognize the most appropriate recovery plans in the field of team sports come from the analysis of the individual parameters.

Validity and reliability of an accelerometer-based player tracking device.

This study aimed to determine the intra- and inter-device accuracy and reliability of wearable athletic tracking devices, under controlled laboratory conditions. A total of nineteen portable accelerometers (Catapult OptimEye S5) were mounted to an aluminum bracket, bolted directly to an Unholtz Dickie 20K electrodynamic shaker table, and subjected to a series of oscillations in each of three orthogonal directions (front-back, side to side, and up-down), at four levels of peak acceleration (0.1g, 0.5g, 1.0g, and 3.0g), each repeated five times resulting in a total of 60 tests per unit, for a total of 1140 records. Data from each accelerometer was recorded at a sampling frequency of 100Hz. Peak accelerations recorded by the devices, Catapult PlayerLoad™, and calculated player load (using Catapult's Cartesian formula) were used for the analysis. The devices demonstrated excellent intradevice reliability and mixed interdevice reliability. Differences were found between devices for mean peak accelerations and PlayerLoad™ for each direction and level of acceleration. Interdevice effect sizes ranged from a mean of 0.54 (95% CI: 0.34-0.74) (small) to 1.20 (95% CI: 1.08-1.30) (large) and ICCs ranged from 0.77 (95% CI: 0.62-0.89) (very large) to 1.0 (95% CI: 0.99-1.0) (nearly perfect) depending upon the magnitude and direction of the applied motion. When compared to the player load determined using the Cartesian formula, the Catapult reported PlayerLoad™ was consistently lower by approximately 15%. These results emphasize the need for industry wide standards in reporting validity, reliability and the magnitude of measurement errors. It is recommended that device reliability and accuracy are periodically quantified.

Accelerometer Load Profiles for Basketball-Specific Drills in Elite Players.

The purpose of this study was to quantify the workload during basketball-specific drills measured through microtechnology. Twelve professional male basketball players from the Spanish 1st Division were monitored over a 4-week period. Data were collected from 16 sessions, for a total of 95 ± 33 drills per player. Workload data (Acceleration load; AL) were obtained from a tri-axial accelerometer at 100Hz sampling frequency, and were expressed over time (AL.min-1). Comparisons among training drills (i.e., 2v2, 3v3, 4v4, and 5v5) were assessed via standardized mean differences. Full-court 3v3 and 5v5 showed the highest physical demand (AL.min-1: 18.7 ± 4.1 and 17.9 ± 4.6, respectively) compared with other traditional balanced basketball drills such as 2v2 and 4v4 (14.6 ± 2.8 and 13.8±2.5, respectively). The AL.min-1 on half-court showed trivial-to-moderate differences with a likely increase of ~10-20% in 2v2 drill compared with any other formats. This study provides insight into the specific requirements of a range of exercises typically performed in basketball sessions. The use of accelerometer data is presented as a useful tool in assessing the workload.

Using testosterone and cortisol as biomarker for training individualization in elite basketball: a 4-year follow-up study.

The purpose of this study was to determine the responses of testosterone and cortisol, with special reference to playing positions, playing time (PT), and phase of the season. We performed a follow-up study during 4 consecutive seasons to investigate the effects of PT, positional role, and phase of the season on anabolic-catabolic biomarkers (plasma total testosterone -TT- and cortisol -C-) on 20 professional male basketball players (27.0 ± 4.2 years; 24.4 ± 1.2 kg·m). First blood samples were collected right after the off-season period and considered as baseline. Samples were taken periodically every 4-6 weeks, always after a 24- to 36-hour break after the last game played. Statistical procedures were nonparametric mainly. Hormonal status was playing position-dependent, power forward (PF) showed the lowest TT values (median ± interquartile range [IQR]; PF: 18.1 ± 4.9; nmol·L), and small forwards showed the highest ones of cortisol (0.55 ± 0.118 µmol·L). Players who played between 13 and 25 minutes per game showed the highest values of TT (22.8 ± 6.9 nmol·L) and TT/C (47.1 ± 21.2). March and April showed the most catabolic or stressed hormonal state (low TT/C values and high ones of cortisol) and that is necessary to take into account according to PT (>25-minute per game) and specific playing position. Monitoring plasma TT and cortisol is recommended to prevent excessive stress caused by professional basketball season requirements.

Hormonal analysis in elite basketball during a season

In elite basketball, the high demands of competition and training require a detailed follow-up of the effects on theplayer’s performance and health. Controlling these effects could improve the knowledge about the players’ recovery process andallow a better design of their individual workloads.Aim: To describe the behavior of the total testosterone serum levels (T), cortisol (C) and T/C ratio.Methodology: 8 blood samples were collected during the whole season of an elite basketball team (n=8) of the First SpanishDivision (ACB). The samples were taken every 4-6 weeks, at 8:00 AM, after 24-36 hours of post-game recovery.Results: T increases after 4 after 3.5 days of rest (6th vs. 1st, p=0.039; 6th vs. 5th, p=0.041) and decreases significantly at theend of the season (8th vs. 7th, p=0.003). C does not show significant variation along the season. T/C ratio shows a significantdecrease at the end of the season (8th vs. 1st , p=0.021; 8th vs. 7th, p=0.017) and in VarT/C (8th vs. 1st, p=0.005; 8th vs. 7th,p=0.036).Conclusions: Concentration values as well as percentages of variation are useful indicators to describe the studied parameters.T/C ratio and/or T could be used as recovery state indicators and could even induce, in conjunction with other indicators,necessary actions to optimize individual workloads. Future investigations should compare these variations to objective workloadparameters and/or other hormonal modulators(AU)