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 (>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

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.

scholarly journals Physical Performance Differences Between Starter and Non‐Starter Players During Professional Soccer Friendly Matches

2019 ◽  
Vol 69 (1) ◽  
pp. 283-291 ◽  
Author(s):  
Jesús V. Giménez ◽  
Anthony S. Leicht ◽  
Miguel A. Gomez
Keyword(s):  
Physical Performance ◽  
Perceived Exertion ◽  
Body Height ◽  
Rating Of Perceived Exertion ◽  
Effect Sizes ◽  
Ratings Of Perceived Exertion ◽  
Professional Soccer ◽  
Performance Differences ◽  
Average Acceleration ◽  
Acceleration And Deceleration

Abstract The aim of this study was to investigate the physical performance differences between players that started (i.e. starters, ≥65 minutes played) and those that were substituted into (i.e. non‐starter) soccer friendly matches. Fourteen professional players (age: 23.2 ± 2.7 years, body height: 178 ± 6 cm, body mass: 73.2 ± 6.9 kg) took part in this study. Twenty, physical performance‐related match variables (e.g. distance covered at different intensities, accelerations and decelerations, player load, maximal running speed, exertion index, work‐to‐rest ratio and rating of perceived exertion) were collected during two matches. Results were analysed using effect sizes (ES) and magnitude based inferences. Compared to starters, non‐starters covered greater match distance within the following intensity categories: >3.3≤4.2m/s (very likely), >4.2≤5 m/s (likely) and >5≤6.9 m/s (likely). In contrast, similar match average acceleration and deceleration values were identified for starters and non‐starters (trivial). Indicators of workloads including player loads (very likely), the exertion index (very likely), and the work–to‐rest ratio (very likely) were greater, while self‐ reported ratings of perceived exertion were lower (likely) for non‐starters compared to starters. The current study demonstrates that substantial physical performance differences during friendly soccer matches exist between starters and non‐starters. Identification of these differences enables coaches and analysts to potentially prescribe optimal training loads and microcycles based upon player’s match starting status.

Individual Response to External Training Load in Elite Football Players

2020 ◽  
Vol 15 (5) ◽  
pp. 696-704
Author(s):  
Håvard Wiig ◽  
Thor Einar Andersen ◽  
Live S. Luteberget ◽  
Matt Spencer
Keyword(s):  
External Load ◽  
High Speed ◽  
Training Load ◽  
Effect Sizes ◽  
Football Players ◽  
Individual Response ◽  
Total Distance ◽  
External Training ◽  
Tracking Devices ◽  
Very High

Purpose: To investigate within-player effect, between-player effect, and individual response of external training load from player tracking devices on session rating of perceived exertion training load (sRPE-TL) in elite football players. Methods: The authors collected sRPE-TL from 18 outfield players in 21 training sessions. Total distance, high-speed running distance (>14.4 m/s), very high-speed running distance (>19.8 m/s), PlayerLoad™, PlayerLoad2D™, and high-intensity events (HIE > 1.5, HIE > 2.5, and HIE > 3.5 m/s) were extracted from the tracking devices. The authors modeled within-player and between-player effects of single external load variables on sRPE-TL, and multiple levels of variability, using a linear mixed model. The effect of 2 SDs of external load on sRPE-TL was evaluated with magnitude-based inferences. Results: Total distance, PlayerLoad™, PlayerLoad2D™, and HIE > 1.5 had most likely substantial within-player effects on sRPE-TL (100%–106%, very large effect sizes). Moreover, the authors observed likely substantial between-player effects (12%–19%, small to moderate effect sizes) from the majority of the external load variables and likely to very likely substantial individual responses of PlayerLoad™, high-speed running distance, very high-speed running distance, and HIE > 1.5 (19%–30% coefficient of variation, moderate to large effect sizes). Finally, sRPE-TL showed large to very large between-session variability with all external load variables. Conclusions: External load variables with low intensity-thresholds had the strongest relationship with sRPE-TL. Furthermore, the between-player effect of external load and the individual response to external load advocate for monitoring sRPE-TL in addition to external load. Finally, the large between-session variability in sRPE-TL demonstrates that substantial amounts of sRPE-TL in training sessions are not explained by single external load variables.

scholarly journals Activity Profiles by Position in Youth Elite Soccer Players in Official Matches

2019 ◽  
Vol 03 (01) ◽  
pp. E19-E24 ◽  
Author(s):  
Svein Arne Pettersen ◽  
Tormod Brenn
Keyword(s):  
High Intensity ◽  
External Load ◽  
Training Programs ◽  
Activity Patterns ◽  
Soccer Players ◽  
Maximum Speed ◽  
Peak Period ◽  
Significant Drop ◽  
Match Play ◽  
Youth Soccer

AbstractIn order to investigate activity profiles and external load patterns in elite youth soccer players, we studied high-intensity activity patterns, maximum running speed, and temporary and end-of-match decline in external load in 54 U17 players (96 match observations) over a full season of official match play.Wide midfielders covered most high-intensity running (HIR) distance (1044.2 m), most sprinting distance (224.4 m), and the highest number of accelerations (185.2); center defenders had the lowest values for these activities (508.3 m, 85.1 m, and 119.0), respectively. Wide midfielders had the highest and center defenders had the lowest maximum speed (30.3 km · h − 1 and 28.6 km · h − 1), respectively. During the matches, players in all playing positions displayed a significant drop in HIR distance, sprinting distance, and number of accelerations. This was especially pronounced in the 5 min following the 5-min peak period and in the last 5-min period for sprinting distance.There are substantial differences in activity profiles by positions, but all players show temporary and end-of-match drop in external load. The variation in activity profiles by playing position in this study may aid in the design of training programs. The considerable end-of-match drop in external load observed raises the question of the favorability of 90 min match times for U17 players.

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 < 0.001, effect size (ES) = 0.68] and HSMs (p < 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 < 0.001, ES = 1.10) and HSMs (p < 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 < 0.001, ES = 0.33). When considering activity patterns combined, PL (p < 0.001, ES = 0.28) and duration (p < 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 < 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 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 Multi-Location External Workload Profile in Women’s Basketball Players. A Case Study at the Semiprofessional-Level

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4277
Author(s):  
Carlos D. Gómez-Carmona ◽  
David Mancha-Triguero ◽  
José Pino-Ortega ◽  
Sergio J. Ibáñez
Keyword(s):  
Repeated Measures ◽  
Anatomical Location ◽  
Lumbar Region ◽  
Ground Contact ◽  
Basketball Players ◽  
Total Load ◽  
Women's Basketball ◽  
Acceleration And Deceleration ◽  
The Individual

The external workload measured in one anatomical location does not determine the total load supported by the human body. Therefore, the purpose of the present study was to characterize the multi-location external workload through PlayerLoadRT of 13 semi-professional women’s basketball players, as well as to analyze differences among anatomical locations (inter-scapulae line, lumbar region, 2× knee, 2× ankle) and laterality (left vs. right) during five tests that represent the most common movements in basketball—(a) linear locomotion, 30-15 IFT; (b) acceleration and deceleration, 16.25-m RSA (c) curvilinear locomotion, 6.75-m arc (d) jump, Abalakov test (e) small-sided game, 10’ 3 vs. 3 10 × 15-m. Statistical analysis was composed of a repeated-measures t-test and eta partial squared effect size. Regarding laterality, differences were found only in curvilinear locomotion, with a higher workload in the outer leg (p < 0.01; ηp2 = 0.33–0.63). In the vertical profile, differences among anatomical locations were found in all tests (p < 0.01; ηp2 = 0.56–0.98). The nearer location to ground contact showed higher values except between the scapulae and lumbar region during jumps (p = 0.83; ηp2 = 0.00). In conclusion, the multi-location assessment of external workload through a previously validated test battery will make it possible to understand the individual effect of external workload in each anatomical location that depends on the type of locomotion. These results should be considered when designing specific strategies for training and injury prevention.

scholarly journals Managing Load to Optimize Well-Being and Recovery During Short-Term Match Congestion in Elite Basketball

2021 ◽  
Vol 16 (1) ◽  
pp. 45-50
Author(s):  
Steven H. Doeven ◽  
Michel S. Brink ◽  
Barbara C.H. Huijgen ◽  
Johan de Jong ◽  
Koen A.P.M. Lemmink
Keyword(s):  
Perceived Exertion ◽  
Training Session ◽  
Well Being ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Total Quality ◽  
Short Term ◽  
Basketball Players ◽  
Total Load ◽  
And Training

In elite basketball, players are exposed to intensified competition periods when participating in both national and international competitions. How coaches manage training between matches and in reference to match scheduling for a full season is not yet known. Purpose: First, to compare load during short-term match congestion (ie, ≥2-match weeks) with regular competition (ie, 1-match weeks) in elite male professional basketball players. Second, to determine changes in well-being, recovery, neuromuscular performance, and injuries and illnesses between short-term match congestion and regular competition. Methods: Sixteen basketball players (age 24.8 [2.0] y, height 195.8 [7.5] cm, weight 94.8 [14.0] kg, body fat 11.9% [5.0%], VO2max 51.9 [5.3] mL·kg−1·min−1) were monitored during a full season. Session rating of perceived exertion (s-RPE) was obtained, and load was calculated (s-RPE × duration) for each training session or match. Perceived well-being (fatigue, sleep quality, general muscle soreness, stress levels, and mood) and total quality of recovery were assessed each training day. Countermovement jump height was measured, and a list of injuries and illnesses was collected weekly using the adapted Oslo Sports Trauma Research Center Questionnaire on Health Problems. Results: Total load (training sessions and matches; P < .001) and training load (P < .001) were significantly lower for ≥2-match weeks. Significantly higher well-being (P = .01) and less fatigue (P = .001) were found during ≥2-match weeks compared with 1-match weeks. Conclusion: Total load and training load were lower during short-term match congestion compared with regular competition. Furthermore, better well-being and less fatigue were demonstrated within short-term match congestion. This might indicate that coaches tend to overcompensate training load in intensified competition.

scholarly journals Quantification of training and match-play load across a season in professional youth football players

2021 ◽  
pp. 174795412110003
Author(s):  
Patrick C Maughan ◽  
Niall G MacFarlane ◽  
Paul A Swinton
Keyword(s):  
Perceived Exertion ◽  
Linear Models ◽  
Training Load ◽  
Effect Sizes ◽  
Future Research ◽  
Football Players ◽  
Mixed Linear Models ◽  
Match Play ◽  
Mean Values ◽  
Youth Football

The purpose of this study was to quantify load across an entire season for professional youth football players and assess the effects of stage of season, playing position and training day relative to match day (MD). Data from ratings of perceived exertion and seven global positioning system (GPS) derived measures of external training load were collected from 20 players across a 47-week season. Mixed linear models were used to assess the effects of stage of season, training proximity to match day (e.g. MD-1, MD-2) and position across each dependent variable. Training proximity to match day was found to have the most substantive effect with effect sizes ranging from small ([Formula: see text] to large ([Formula: see text]. Across training load measures, mean values collected on match day were on average 47% higher than all other sessions. Whilst significant regression coefficients were obtained for playing position (p ≤ 0.003) and stage of season (p ≤ 0.049), effect sizes were close to zero ([Formula: see text]in each instance. This study provides insight into the season-long training and match-play demands of a professional youth football team. It highlights the significant impact of match-play on load and supports the use of multiple methods of collecting training load data. Overall, there was limited variation in mean values of dependent variables across playing position, stage of the season and loading during midweek training. These findings highlight the need for future research to investigate whether greater systematic variations in training load can be used to increase physical fitness and maximise physical performance during competition.

scholarly journals Assessment of the Multi-Location External Workload Profile in the Most Common Movements in Basketball

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3441
Author(s):  
Carlos D. Gómez-Carmona ◽  
Sebastián Feu ◽  
José Pino-Ortega ◽  
Sergio J. Ibáñez
Keyword(s):  
Lower Limb ◽  
Repeated Measures ◽  
Ad Hoc ◽  
Physical Conditioning ◽  
Lumbar Region ◽  
Basketball Players ◽  
Eta Squared ◽  
Subject Variability ◽  
Acceleration And Deceleration ◽  
Linear Movement

The present study analyzed the multi-location external workload profile in basketball players using a previously validated test battery and compared the demands among anatomical locations. A basketball team comprising 13 semi-professional male players was evaluated in five tests (abilities/skills/tests): (a) aerobic, linear movement, 30-15 IFT; (b) lactic anaerobic, acceleration and deceleration, 16.25 m RSA (c) alactic anaerobic, curvilinear movement, 6.75 m arc (d) elastic, jump, Abalakov test (e) physical-conditioning, small-sided game, 10’ 3 vs.3 10 × 15 m. PlayerLoadRT was evaluated at six anatomical locations simultaneously (interscapular line, lumbar region, knees and ankles) by six WIMU PROTM inertial devices attached to the player using an ad hoc integral suit. Statistical analysis was composed of an ANOVA of repeated measures and partial eta squared effect sizes. Significant differences among anatomical locations were found in all tests with higher values in the location nearer to ground contact (p < 0.01). However, differences between lower limb locations were only found in curvilinear movements, with a higher workload in the outside leg (p < 0.01). Additionally, high between-subject variability was found in team players, especially at lower limb locations. In conclusion, multi-location evaluation in sports movements will make it possible to establish an individual external workload profile and design specific strategies for training and injury prevention programs.

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