scholarly journals Quantifying Training and Game Demands of a National Basketball Association Season

2021 ◽  
Vol 12 ◽  
Author(s):  
Jennifer L. Russell ◽  
Blake D. McLean ◽  
Sean Stolp ◽  
Donnie Strack ◽  
Aaron J. Coutts
Keyword(s):  
Body Mass ◽  
External Load ◽  
Primary Objective ◽  
Training Load ◽  
National Basketball Association ◽  
Training Data ◽  
Basketball Players ◽  
Load Monitoring ◽  
Individualized Training ◽  
And Training

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.

scholarly journals Load monitoring system in top-level basketball team

Kinesiology ◽  
2018 ◽  
Vol 50 (1) ◽  
pp. 25-33 ◽  
Author(s):  
Luka Svilar ◽  
Igor Jukić
Keyword(s):  
External Load ◽  
Perceived Exertion ◽  
Body Height ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Basketball Players ◽  
Load Monitoring ◽  
Acceleration And Deceleration ◽  
And Control ◽  
High Band

The study aimed to describe and compare the external training load, monitored using microtechnology, with the internal training load, expressed as the session rating of perceived exertion (sRPE), in elite male basketball training sessions. Thirteen professional basketball players participated in this study (age=25.7±3.3 years; body height=199.2±10.7 cm; body mass=96.6±9.4 kg). All players belonged to the same team, competing in two leagues, ACB and the Euroleague, in the 2016/2017 season. The variables assessed within the external motion analysis included: Player Load (PL), acceleration and deceleration (ACC/DEC), jumps (JUMP), and changes of direction (CoD). The internal demands were registered using the sRPE method. Pearson product-moment correlations were used to determine relationships between the variables. A significant correlation was observed between the external load variables and sRPE (range r=0.71–0.93). Additionally, the sRPE variable showed a high correlation with the total PL, ACC, DEC, and CoD. The contrary was observed with respect to the relationship between sRPE and JUMP variables: the correlation was higher for the high band and lower for the total number of jumps. With respect to the external load variables, a stronger correlation was found between PL and the total number of ACC, DEC and COD than the same variables within the high band. The only contrary finding was the correlation between PL and JUMP variables, which showed a stronger correlation for hJUMP. Tri-axial accelerometry technology and the sRPE method serve as valuable tools for monitoring the training load in basketball. Even though the two methods exhibit a strong correlation, some variation exists, likely due to frequent static movements (i.e., isometric muscle contractions) that accelerometers are not able to detect. Finally, it is suggested that both methods are to be used complementary, when possible, in order to design and control the training process as effectively as possible.

Defensive Strategy and Player Sex Impact Heart-Rate Responses During Games-Based Drills in Professional Basketball

2020 ◽  
pp. 1-7
Author(s):  
David Suárez-Iglesias ◽  
Rubén Dehesa ◽  
Aaron T. Scanlan ◽  
José A. Rodríguez-Marroyo ◽  
Alejandro Vaquera
Keyword(s):  
Heart Rate ◽  
Training Stimulus ◽  
Training Load ◽  
Defensive Strategy ◽  
Basketball Players ◽  
Professional Basketball ◽  
Defensive Strategies ◽  
Cardiovascular Stress ◽  
The Impact ◽  
And Training

Purpose: Games-based drills (GBD) are the predominant form of training stimulus prescribed to male and female basketball players. Despite being readily manipulated during GBD, the impact of defensive strategy on the sex-specific demands of GBD remains unknown. Therefore, the aim of this study was to quantify and compare the heart-rate (HR) responses experienced during 5v5 GBD using different defensive strategies (man-to-man defense vs zone defense [ZD] formations) according to player sex. Method: HR was recorded in 11 professional male and 10 professional female basketball players while performing 5v5 GBD with different defensive strategies (man-to-man defense or ZD). HR-based training load was also calculated using the summated heart-rate zones model. Results: During man-to-man defense, mean HR (), relative time (in percentage) spent working at 90% to 100% maximal HR (), and summated heart-rate zones () were greater (P < .05) in female players compared with males. During ZD, higher (P < .01) peak HR (), mean HR (), relative and absolute (in minutes) time spent working at 80% to 89% maximal HR ( and .03, respectively) and 90% to 100% maximal HR ( and .09, respectively), and summated heart-rate zones () were observed in female players compared with males. Conclusions: The defensive strategy employed during 5v5 full-court GBD influences HR responses and training load differently according to sex, where female players experience higher HR responses than males, especially when ZD are adopted. Basketball coaching staff can use these findings for the precise manipulation of team defenses during GBD to elicit desired cardiovascular stress on players.

scholarly journals Variations of Workload Indices Prior to Injuries: A Study in Trail Runners

2020 ◽  
Vol 17 (11) ◽  
pp. 4037 ◽  
Author(s):  
Sérgio Matos ◽  
Filipe Manuel Clemente ◽  
Rui Silva ◽  
José María Cancela Carral
Keyword(s):  
Body Mass ◽  
External Load ◽  
Injury Risk ◽  
Perceived Exertion ◽  
Training Time ◽  
Positioning Systems ◽  
Total Distance ◽  
Injury Occurrence ◽  
Global Positioning ◽  
And Training

The purpose of this study was to compare the variations of weekly workload indices of internal and external load measures across the three weeks prior to injury occurrences in trail runners. Twenty-five trail runners (age: 36.23 ± 8.30 years old; body mass: 67.24 ± 5.97 kg; height: 172.12 ± 5.12 cm) were monitored daily for 52 weeks using global positioning systems (GPSs) to determine the total distance covered. Additionally, a rate of perceived exertion (RPE) scale was applied to determine session-RPE (sRPE: RPE multiplied by training time). The accumulated load (AL), acute: chronic workload ratio (ACWR), training monotony (TM), and training strain (TS) indices were calculated weekly for each runner. During the period of analysis, the injury occurrences were recorded. The differences were observed in AL and ACWR for sRPE and training time were significantly greater during the injury week when compared to the previous weeks. Similar evidence was found in TM and TS indices for sRPE, training time, and total distance. Furthermore, no meaningful differences were observed in AL and ACWR for total distance in the weeks prior to injury occurrence. Nevertheless, significant between-subjects variability was found, and this should be carefully considered. For that reason, an individualized analysis of the workload dynamics is recommended, avoiding greater spikes in load by aiming to keep a progressive increment of load without consequences for injury risk.

Player Session Rating of Perceived Exertion: A More Valid Tool Than Coaches’ Ratings to Monitor Internal Training Load in Elite Youth Female Basketball

2020 ◽  
Vol 15 (4) ◽  
pp. 548-553 ◽  
Author(s):  
Corrado Lupo ◽  
Alexandru Nicolae Ungureanu ◽  
Riccardo Frati ◽  
Matteo Panichi ◽  
Simone Grillo ◽  
...  
Keyword(s):  
Body Mass ◽  
Perceived Exertion ◽  
Team Sports ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Basketball Players ◽  
Mixed Effect ◽  
Maximal Intensity ◽  
Session Duration ◽  
Post Hoc

Purpose: To monitor elite youth female basketball training to verify whether players’ and coaches’ (3 technical coaches and 1 physical trainer) session rating of perceived exertion (s-RPE) has a relationship with Edwards’ method. Methods: Heart rate of 15 elite youth female basketball players (age 16.7 [0.5] y, height 178 [9] cm, body mass 72 [9] kg, body mass index 22.9 [2.2] kg·m−2) was monitored during 19 team (268 individual) training sessions (102 [15] min). Mixed effect models were applied to evaluate whether s-RPE values were significantly (P ≤ .05) related to Edwards’ data, total session duration, maximal intensity (session duration at 90–100% HRmax), type of training (ie, strength, conditioning, and technique), and whether differences emerged between players’ and coaches’ s-RPE values. Results: The results showed that there is a relationship between s-RPE and Edwards’ methods for the players’ RPE scores (P = .019) but not for those of the trainers. In addition, as expected, both players’ (P = .014) and coaches’ (P = .002) s-RPE scores were influenced by total session duration but not by maximal intensity and type of training. In addition, players’ and coaches’ s-RPE values differed (P < .001)—post hoc differences emerged for conditioning (P = .01) and technique (P < .001) sessions. Conclusions: Elite youth female basketball players are better able to quantify the internal training load of their sessions than their coaches, strengthening the validity of s-RPE as a tool to monitor training in team sports.

scholarly journals No evidence of association between HRV and training load in a pool of professional athletes before, during, and after the first COVID-19 lockdown.

2021 ◽  
Author(s):  
Alejandro Javaloyes ◽  
Daniele Marinazzo ◽  
Daniel Sanabria ◽  
Manuel Moya-Ramón ◽  
José Ramón Lillo-Bevia ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Body Mass ◽  
Mixed Model ◽  
Elite Athletes ◽  
Training Load ◽  
Training Volume ◽  
Specific Effects ◽  
And Training

PURPOSE: The COVID-19 crisis also affected elite sport severely, as elite athletes either stopped or drastically reduced their training regimen due to the lack of competitions and the mandatory lockdown. The aim of this study was to test whether heart rate variability was a reliable index of training load, which was dramatically altered due to the mandatory lockdown that occurred as a consequence of the COVID-19. METHODS: Training (volume and intensity) and heart rate variability of sixteen professional male (n = 8; body mass index = 22.2 ± 2.0) and female cyclists (n = 8; body mass index = 20.3 ± 1.1) before (4 weeks), during (7 weeks), and after (4 weeks) the mandatory lockdown in Spain were monitored. RESULTS: Individual analyses showed that the mandatory lockdown caused reliable reductions in training volume in 13 subjects (-96 to -7 % reductions in minutes), that were followed by an increase after the lockdown in all subjects (5 to 270%). In contrast, changes in training load were not homogenous across individuals. Moreover, such changes were not matched by comparable variations in heart rate variability. A mixed model of the heart rate variability as a function of training volume and intensity revealed no significant modulation by these two variables, and subject specific effects on the slope. CONCLUSIONS: In this study, we did not find evidence of association between heart rate variability and training load and/or intensity as many previous reports have suggested, even if training conditions changed dramatically overnight.

scholarly journals Assessing the External Load Associated With High-Intensity Activities Recorded During Official Basketball Games

2021 ◽  
Vol 12 ◽  
Author(s):  
Marco Pernigoni ◽  
Davide Ferioli ◽  
Ramūnas Butautas ◽  
Antonio La Torre ◽  
Daniele Conte
Keyword(s):  
Mixed Models ◽  
High Intensity ◽  
External Load ◽  
Injury Risk ◽  
Training Programs ◽  
Specific Activity ◽  
Activity Patterns ◽  
Basketball Players ◽  
Time Motion ◽  
Load Monitoring

Load monitoring in basketball is fundamental to develop training programs, maximizing performance while reducing injury risk. However, information regarding the load associated with specific activity patterns during competition is limited. This study aimed at assessing the external load associated with high-intensity activities recorded during official basketball games, with respect to different (1) activity patterns, (2) playing positions, and (3) activities performed with or without ball. Eleven male basketball players (six backcourt, five frontcourt, age: 20.5 ± 1.1 years, stature: 191.5 ± 8.7 cm, body mass: 86.5 ± 11.3 kg; experience: 8.5 ± 2.4 years) competing in the Lithuanian third division were recruited for this study. Three in-season games were assessed via time-motion analysis and microsensors. Specifically, the high-intensity activities including sprints, high-intensity specific movements (HSM) and jumps were identified and subsequently the external load [PlayerLoad™ (PL) and PlayerLoad™/min (PL/min)] of each activity was determined. Linear mixed models were used to examine differences in PL, PL/min and mean duration between activity pattern, playing positions and activities performed with or without ball. Results revealed PL was lower in jumps compared to sprints [p &lt; 0.001, effect size (ES) = 0.68] and HSMs (p &lt; 0.001, ES = 0.58), while PL/min was greater in sprints compared to jumps (p = 0.023, ES = 0.22). Jumps displayed shorter duration compared to sprints (p &lt; 0.001, ES = 1.10) and HSMs (p &lt; 0.001, ES = 0.81), with HSMs lasting longer than sprints (p = 0.002, ES = 0.17). Jumps duration was longer in backcourt than frontcourt players (p &lt; 0.001, ES = 0.33). When considering activity patterns combined, PL (p &lt; 0.001, ES = 0.28) and duration (p &lt; 0.001, ES = 0.43) were greater without ball. Regarding HSMs, PL/min was higher with ball (p = 0.036, ES = 0.14), while duration was longer without ball (p &lt; 0.001, ES = 0.34). The current findings suggest that external load differences in high-intensity activities exist among activity patterns and between activities performed with and without ball, while no differences were found between playing positions. Practitioners should consider these differences when designing training sessions.

scholarly journals Comparing external total load, acceleration and deceleration outputs in elite basketball players across positions during match play

Kinesiology ◽  
2018 ◽  
Vol 50 (2) ◽  
pp. 228-234 ◽  
Author(s):  
Jairo Vázquez-Guerrero ◽  
Luis Suarez-Arrones ◽  
David Casamichana Gómez ◽  
Gil Rodas
Keyword(s):  
External Load ◽  
Training Programs ◽  
Body Height ◽  
Training Load ◽  
Effect Sizes ◽  
Basketball Players ◽  
Match Play ◽  
Total Load ◽  
Load Model ◽  
Acceleration And Deceleration

The aim of this study was to compare external load, calculated by an accelerometer training load model, the number and intensity of accelerations and decelerations, and the acceleration:deceleration ratio between playing positions during basketball matches. Twelve elite male basketball players (mean±SD, age: 25.5±5.2 years; (range: 19-36 years); body height 201.4±8.6 cm; body mass: 98.4±12.6 kg) were monitored during two official matches. An accelerometer training load model and the number of accelerations and decelerations were used to assess physical demands imposed on basketball players. Magnitude-based inferences and effect sizes (ES) were used to assess possible differences between positions: point guards (PG), shooting guards (SG), small forwards (SF), power forwards (PF) and centers (C). Elite basketball players in all positions presented higher maximal decelerations than accelerations (ES=2.70 to 6.87) whereas the number of moderate accelerations were higher than the number of moderate decelerations (ES=0.54 to 3.12). Furthermore, the acceleration:deceleration ratio (&gt;3 m∙s-2) was significantly lower in players on the perimeter (PG and SG) than in PF and C (ES=1.03 to 2.21). Finally, PF had the lowest total external load (ES=0.67 to 1.18). These data allow us to enlarge knowledge of the external demands in basketball matches and this information could be used in the planning of training programs

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