Not All About the Effort? A Comparison of Playing Intensities During Winning and Losing Game Quarters in Basketball

2020 ◽  
pp. 1-4
Author(s):  
Jordan L. Fox ◽  
Jesse Green ◽  
Aaron T. Scanlan
Keyword(s):  
Heart Rate ◽  
Mixed Models ◽  
High Intensity ◽  
Movement Analysis ◽  
Effect Sizes ◽  
Basketball Players ◽  
Heart Rate Monitors ◽  
Competitive Season ◽  
Team Success ◽  
Minute Sample

Purpose: To compare peak and average intensities encountered during winning and losing game quarters in basketball players. Methods: Eight semiprofessional male basketball players (age = 23.1 [3.8] y) were monitored during all games (N = 18) over 1 competitive season. The average intensities attained in each quarter were determined using microsensors and heart-rate monitors to derive relative values (per minute) for the following variables: PlayerLoad, frequency of high-intensity and total accelerations, decelerations, changes of direction, jumps, and total inertial movement analysis events combined, as well as modified summated-heart-rate-zones workload. The peak intensities reached in each quarter were determined using microsensors and reported as PlayerLoad per minute over 15-second, 30-second, 1-minute, 2-minute, 3-minute, 4-minute, and 5-minute sample durations. Linear mixed models and effect sizes were used to compare intensity variables between winning and losing game quarters. Results: Nonsignificant (P > .05), unclear–small differences were evident between winning and losing game quarters in all variables. Conclusions: During winning and losing game quarters, peak and average intensities were similar. Consequently, factors other than the intensity of effort applied during games may underpin team success in individual game quarters and therefore warrant further investigation.

Comparing Weekly Training and Game Demands According to Playing Position in a Semiprofessional Basketball Team

2020 ◽  
pp. 1-7
Author(s):  
Markus N.C. Williams ◽  
Vincent J. Dalbo ◽  
Jordan L. Fox ◽  
Cody J. O’Grady ◽  
Aaron T. Scanlan
Keyword(s):  
Heart Rate ◽  
Mixed Models ◽  
Perceived Exertion ◽  
Movement Analysis ◽  
Rating Of Perceived Exertion ◽  
Effect Sizes ◽  
Basketball Players ◽  
Several Variables ◽  
Longitudinal Observational Study ◽  
Weekly Training

Purpose: To compare weekly training and game demands according to playing position in basketball players. Methods: A longitudinal, observational study was adopted. Semiprofessional, male basketball players categorized as backcourt (guards; n = 4) and frontcourt players (forwards/centers; n = 4) had their weekly workloads monitored across an entire season. External workload was determined using microsensors and included PlayerLoad™ (PL) and inertial movement analysis variables. Internal workload was determined using heart rate to calculate absolute and relative summated-heart-rate-zones workload and rating of perceived exertion (RPE) to calculate session-RPE workload. Comparisons between weekly training and game demands were made using linear mixed models and effect sizes in each positional group. Results: In backcourt players, higher relative PL (P = .04, very large) and relative summated-heart-rate-zones workload (P = .007, very large) were evident during training, while greater session-RPE workload (P = .001, very large) was apparent during games. In frontcourt players, greater PL (P < .001, very large), relative PL (P = .019, very large), peak PL intensities (P < .001, moderate), high-intensity inertial movement analysis events (P = .002, very large), total inertial movement analysis events (P < .001, very large), summated-heart-rate-zones workload (P < .001, very large), RPE (P < .001, very large), and session-RPE workload (P < .001, very large) were evident during games. Conclusions: Backcourt players experienced similar demands between training and games across several variables, with higher average workload intensities during training. Frontcourt players experienced greater demands across all variables during games than training. These findings emphasize the need for position-specific preparation strategies leading into games in basketball teams.

The Impact of Contextual Factors on Game Demands in Starting, Semiprofessional, Male Basketball Players

2020 ◽  
Vol 15 (4) ◽  
pp. 450-456 ◽  
Author(s):  
Jordan L. Fox ◽  
Robert Stanton ◽  
Charli Sargent ◽  
Cody J. O’Grady ◽  
Aaron T. Scanlan
Keyword(s):  
Heart Rate ◽  
High Intensity ◽  
Perceived Exertion ◽  
Contextual Factors ◽  
Relative Number ◽  
Movement Analysis ◽  
Rating Of Perceived Exertion ◽  
Basketball Players ◽  
Mixed Effect ◽  
The Impact

Purpose: To quantify and compare external and internal game workloads according to contextual factors (game outcome, game location, and score-line). Methods: Starting semiprofessional, male basketball players were monitored during 19 games. External (PlayerLoad™ and inertial movement analysis variables) and internal (summated-heart-rate-zones and rating of perceived exertion [RPE]) workload variables were collected for all games. Linear mixed-effect models and effect sizes were used to compare workload variables based on each of the contextual variables assessed. Results: The number of jumps, absolute and relative (in min−1) high-intensity accelerations and decelerations, and relative changes-of-direction were higher during losses, whereas session RPE was higher during wins. PlayerLoad™ the number of absolute and relative jumps, high-intensity accelerations, absolute and relative total decelerations, total changes-of-direction, summated-heart-rate-zones, session RPE, and RPE were higher during away games, whereas the number of relative high-intensity jumps was higher during home games. PlayerLoad™, the number of high-intensity accelerations, total accelerations, absolute and relative decelerations, absolute and relative changes-of-direction, summated-heart-rate-zones, sRPE, and RPE were higher during balanced games, whereas the relative number of total and high-intensity jumps were higher during unbalanced games. Conclusions: Due to increased intensity, starting players may need additional recovery following losses. Given the increased external and internal workload volumes encountered during away games and balanced games, practitioners should closely monitor playing times during games. Monitoring playing times may help identify when players require additional recovery or reduced training volumes to avoid maladaptive responses across the in-season.

scholarly journals Repeated Sprint Ability in Elite Basketball Players: The Effects of 10 × 30 m Vs. 20 × 15 m Exercise Protocols on Physiological Variables and Sprint Performance

2021 ◽  
Vol 77 (1) ◽  
pp. 181-189
Author(s):  
Bruno Figueira ◽  
Bruno Gonçalves ◽  
Eduardo Abade ◽  
Rūtenis Paulauskas ◽  
Nerijus Masiulis ◽  
...  
Keyword(s):  
Heart Rate ◽  
High Intensity ◽  
Exercise Heart Rate ◽  
Basketball Players ◽  
Small Magnitude ◽  
Physiological Variables ◽  
Repeated Sprint Ability ◽  
Repeated Sprint ◽  
The Impact ◽  
Sprint Ability

Abstract Team sports players are required to perform repeated bouts of short-term high-intensity actions during the games. The present study aimed to examine the effects of a novel repeated sprint ability protocol (20×15 m) and compare it with the impact of a more traditional repeated sprint ability protocol (10×30 m). Twelve male elite Lithuanian basketball players (age 21.0 ± 2.0 y, body height 1.90 ± 0,07 m, body mass 86.2 ± 5.8 kg and training experience 12.0 ± 1.9 y) competing in the Lithuanian National Basketball Championship participated in this study. Participants completed three bouts of each repeated sprint protocol interspersed with 5 minutes of recovery. Results showed that the 20×15 m protocol caused a significant decrease in total sprint time (most likely; mean changes (%) with ± 90% of confidence limits, -9.4%; ± 0.7%) and a large decrease in blood lactate (most likely, -39.2%; ±12.8%) compared to the 10×30 m protocol. Despite small differences, the fatigue index presented a similar trend (possibly decrease, -23.7%; ± 38.8%). The exercise heart rate showed a very similar trend with trivial differences between the two protocols. The 20×15 m protocol presented a lower heart rate during recovery with small magnitude. Overall, the present study showed that the 20×15 m protocol seemed to be more representative of the specific basketball demands. Coaches should be aware that RSA training during the in-season may be an adequate stimulus to improve high-intensity runs and muscle power in high-level players.

The Relationships Between External and Internal Workloads During Basketball Training and Games

2020 ◽  
Vol 15 (8) ◽  
pp. 1081-1086
Author(s):  
Jordan L. Fox ◽  
Cody J. O’Grady ◽  
Aaron T. Scanlan
Keyword(s):  
Heart Rate ◽  
High Intensity ◽  
Perceived Exertion ◽  
Movement Analysis ◽  
Rating Of Perceived Exertion ◽  
Large Games ◽  
Workload Management ◽  
Low Intensity ◽  
Medium Intensity ◽  
Selection Of

Purpose: To investigate the relationships between external and internal workloads using a comprehensive selection of variables during basketball training and games. Methods: Eight semiprofessional, male basketball players were monitored during training and games for an entire season. External workload was determined as PlayerLoad™: total and high-intensity accelerations, decelerations, changes of direction, and jumps and total low-intensity, medium-intensity, high-intensity, and overall inertial movement analysis events. Internal workload was determined using the summated-heart-rate zones and session rating of perceived exertion models. The relationships between external and internal workload variables were separately calculated for training and games using repeated-measures correlations with 95% confidence intervals. Results: PlayerLoad was more strongly related to summated-heart-rate zones (r = .88 ± .03, very large [training]; r = .69 ± .09, large [games]) and session rating of perceived exertion (r = .74 ± .06, very large [training]; r = .53 ± .12, large [games]) than other external workload variables (P < .05). Correlations between total and high-intensity accelerations, decelerations, changes of direction, and jumps and total low-intensity, medium-intensity, high-intensity, and overall inertial movement analysis events and internal workloads were stronger during training (r = .44–.88) than during games (r = .15–.69). Conclusions: PlayerLoad and summated-heart-rate zones possess the strongest dose–response relationship among a comprehensive selection of external and internal workload variables in basketball, particularly during training sessions compared with games. Basketball practitioners may therefore be able to best anticipate player responses when prescribing training drills using these variables for optimal workload management across the season.

scholarly journals Different intensities of basketball drills affect jump shot accuracy of expert and junior players

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4250 ◽  
Author(s):  
Giuseppe Marcolin ◽  
Nicola Camazzola ◽  
Fausto Antonio Panizzolo ◽  
Davide Grigoletto ◽  
Antonio Paoli
Keyword(s):  
Heart Rate ◽  
High Intensity ◽  
Perceived Exertion ◽  
Acute Effect ◽  
Rating Of Perceived Exertion ◽  
Basketball Players ◽  
Maximum Accuracy ◽  
Counter Movement Jump ◽  
Different Levels

Background In basketball a maximum accuracy at every game intensity is required while shooting. The aim of the present study was to investigate the acute effect of three different drill intensity simulation protocols on jump shot accuracy in expert and junior basketball players. Materials & Methods Eleven expert players (age 26 ± 6 yrs, weight 86 ± 11 kg, height 192 ± 8 cm) and ten junior players (age 18 ± 1 yrs, weight 75 ± 12 kg, height 184 ± 9 cm) completed three series of twenty jump shots at three different levels of exertion. Counter Movement Jump (CMJ) height was also measured after each series of jump shots. Exertion’s intensity was induced manipulating the basketball drills. Heart rate was measured for the whole duration of the tests while the rating of perceived exertion (RPE) was collected at the end of each series of shots. Results Heart rate and rating of perceived exertion (RPE) were statistically different in the three conditions for both expert and junior players. CMJ height remained almost unchanged in both groups. Jump shot accuracy decreased with increasing drills intensity both in experts and junior players. Expert players showed higher accuracy than junior players for all the three levels of exertion (83% vs 64%, p < 0.001; 75% vs 57%, p < 0.05; 76% vs 60%, p < 0.01). Moreover, for the most demanding level of exertion, experts showed a higher accuracy in the last ten shots compared to the first ten shots (82% vs 70%, p < 0.05). Discussion Experts coped better with the different exertion’s intensities, thus maintaining a higher level of performance. The introduction of technical short bouts of high-intensity sport-specific exercises into skill sessions should be proposed to improve jump shot accuracy during matches.

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.

Weekly Training Demands Increase, but Game Demands Remain Consistent Across Early, Middle, and Late Phases of the Regular Season in Semiprofessional Basketball Players

2021 ◽  
pp. 1-8
Author(s):  
Markus N.C. Williams ◽  
Jordan L. Fox ◽  
Cody J. O’Grady ◽  
Samuel Gardner ◽  
Vincent J. Dalbo ◽  
...  
Keyword(s):  
Mixed Models ◽  
Perceived Exertion ◽  
Late Phase ◽  
Movement Analysis ◽  
Rating Of Perceived Exertion ◽  
Basketball Players ◽  
External Monitoring ◽  
Weekly Training ◽  
The Stability ◽  
Training Demands

Purpose: To compare weekly training, game, and overall (training and games) demands across phases of the regular season in basketball. Methods: Seven semiprofessional, male basketball players were monitored during all on-court team-based training sessions and games during the regular season. External monitoring variables included PlayerLoad™ and inertial movement analysis events per minute. Internal monitoring variables included a modified summated heart rate zones model calculated per minute and rating of perceived exertion. Linear mixed models were used to compare training, game, and overall demands between 5-week phases (early, middle, and late) of the regular season with significance set at P ≤ .05. Effect sizes were calculated between phases and interpreted as: trivial, <0.20; small, 0.20 to 0.59; moderate, 0.60 to 1.19; large, 1.20 to 1.99; very large, ≥2.00. Results: Greater (P > .05) overall inertial movement analysis events (moderate–very large) and rating of perceived exertion (moderate) were evident in the late phase compared with earlier phases. During training, more accelerations were evident in the middle (P = .01, moderate) and late (P = .05, moderate) phases compared with the early phase, while higher rating of perceived exertion (P = .04, moderate) was evident in the late phase compared with earlier phases. During games, nonsignificant, trivial–small differences in demands were apparent between phases. Conclusions: Training and game demands should be interpreted in isolation and combined given overall player demands increased as the season progressed, predominantly due to modifications in training demands given the stability of game demands. Periodization strategies administered by coaching staff may have enabled players to train at greater intensities late in the season without compromising game intensity.

The perceptual, heart rate and technical-tactical characteristics of 3 × 3 basketball

2020 ◽  
Vol 15 (5-6) ◽  
pp. 772-782
Author(s):  
Riley B McGown ◽  
Nick B Ball ◽  
Jan S Legg ◽  
Jocelyn K Mara
Keyword(s):  
Heart Rate ◽  
Mixed Models ◽  
Perceived Exertion ◽  
Ratings Of Perceived Exertion ◽  
Peak Heart Rate ◽  
Basketball Players ◽  
Preparation Programs ◽  
Dependent Variables ◽  
Physical Preparation ◽  
Pool Game

The aim of this study was to investigate the perceptual, heart rate and technical-tactical characteristics of elite male and female 3 × 3 basketball games. Eleven male and twenty-two female elite basketball players were monitored using heart rate telemetry, Ratings of Perceived Exertion (RPE) and video analysis across three 3 × 3 basketball tournaments. Linear mixed models were performed to determine the influence of round (pool game, quarter-final, semi-final, final, classification game) and sex on all dependent variables (alpha = 0.05). There was no difference between sexes for heart rate variables (p = 0.53 - 0.85). The greatest percentage (56.9 ± 20.1%) of game time was spent in heart rate zone 5 (90-100% peak heart rate). Overall RPE was higher in semi-finals (7.2 ± 1.5, p ≤ 0.001, ES: 1.27) and finals (7.7 ± 1.6 p ≤ 0.001, ES: 1.67) compared to pool games (5.1 ± 1.5). An analysis of the technical-tactical actions revealed that there were less steals in semi-finals (p = 0.01, ES = 0.56) and finals (p = 0.01, ES = 0.71) compared to pool games, with no sex-related differences present (p = 0.06 - 0.97). Players generally spent one minute on the bench for every three minutes on the court, creating a 3:1 work to rest ratio. Physical preparation programs for elite 3 × 3 basketball athletes should include exposure to high-intensity activity in which heart rates ≥80% of peak heart rate are reached for periods of time similar to that experienced during gameplay. A 3:1 work-to-rest ratio may be beneficial during conditioning training for this population.

scholarly journals Effects of the Intensity of Lifestyle Exercise on Changes in Blood Pressure

2020 ◽  
pp. 019394592096942
Author(s):  
Carolyn Harmon Still ◽  
Shirley M. Moore ◽  
Abdus Sattar
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Mixed Models ◽  
Cardiac Event ◽  
Study Group ◽  
Target Heart Rate ◽  
Heart Rate Monitors ◽  
Underlying Mechanisms ◽  
One Year ◽  
Objectively Measured

The purpose of this study was to investigate whether the amount of time participants exercised in the target heart rate zone (THRZ) influenced change in blood pressure (BP) one year following a cardiac event. Lifestyle exercise (habitual, small exercise opportunities) and intensity were objectively measured using portable heart rate monitors. Linear mixed models were used to analyze change in BP among 331 participants. Mean BP at baseline was 118/70 mmHg, and both systolic and diastolic BP increased from baseline to one year—4.79 mmHg ( p <.001) and 2.09 mmHg ( p =.002), respectively. Overall, participants had a decrease in levels of lifestyle exercise. After controlling for time, age, gender, and study group, SBP change was inversely associated with amount of time in THRZ. Given suboptimal engagement in recommended exercise, the underlying mechanisms of lifestyle exercise effects on the time spent in THRZ to reduce BP warrants further study in this population.

scholarly journals Player Heart Rate Responses and Pony External Load Measures during 16-Goal Polo

Data ◽  
2020 ◽  
Vol 5 (2) ◽  
pp. 34 ◽  
Author(s):  
Russ Best
Keyword(s):  
Heart Rate ◽  
New Zealand ◽  
Data Collection ◽  
High Intensity ◽  
External Load ◽  
Cardiovascular Responses ◽  
Heart Rate Monitoring ◽  
Heart Rate Monitors ◽  
Monitoring Technologies ◽  
Data Collection Approach

This dataset provides information pertaining to the spatiotemporal stresses experienced by Polo ponies in play and the cardiovascular responses to these demands by Polo players, during 16-goal Polo. Data were collected by player-worn GPS units and paired heart rate monitors, across a New Zealand Polo season. The dataset comprises observations from 160 chukkas of Open Polo, and is presented as per chukka per game (curated) and in per effort per player (raw) formats. Data for distance, speed, and high intensity metrics are presented and are further categorised into five equine-based speed zones, in accordance with previous literature. The purpose of this dataset is to provide a detailed quantification of the load experienced by Polo players and their ponies at the highest domestic performance level in New Zealand, as well as advancing the scope of previous Polo literature that has employed GPS or heart rate monitoring technologies. This dataset may be of interest to equine scientists and trainers, veterinary practitioners, and sports scientists. An exemplar template is provided to facilitate the adoption of this data collection approach by other practitioners.

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