Is it enough to use the traditional approach based on average values for basketball physical performance analysis?

Intensity Zones and Intensity Thresholds Used to Quantify External Load in Competitive Basketball: A Systematic Review

BACKGROUND

Despite widespread use of intensity zones to quantify external load variables in basketball research, the consistency in identifying zones and accompanying intensity thresholds using predominant monitoring approaches in training and games remains unclear.

OBJECTIVES

The purpose of this work was to examine the external load intensity zones and thresholds adopted across basketball studies using video-based time-motion analysis (TMA), microsensors, and local positioning systems (LPS).

METHODS

PubMed, MEDLINE, and SPORTDiscus databases were searched from inception until 31 January 2023 for studies using intensity zones to quantify external load during basketball training sessions or games. Studies were excluded if they examined players participating in recreational or wheelchair basketball, were reviews or meta-analyses, or utilized monitoring approaches other than video-based TMA, microsensors, or LPS.

RESULTS

Following screening, 86 studies were included. Video-based TMA studies consistently classified jogging, running, sprinting, and jumping as intensity zones, but demonstrated considerable variation in classifying low-intensity (standing and walking) and basketball-specific activities. Microsensor studies mostly utilized a single, and rather consistent, threshold to identify only high-intensity activities (> 3.5 m·s-2 for accelerations, decelerations, and changes-in-direction or > 40 cm for jumps), not separately quantifying lower intensity zones. Similarly, LPS studies predominantly quantified only high-intensity activities in a relatively consistent manner for speed (> 18.0 m·s-1) and acceleration/deceleration zones (> 2.0 m·s-2); however, the thresholds adopted for various intensity zones differed greatly to those used in TMA and microsensor research.

CONCLUSIONS

Notable inconsistencies were mostly evident for low-intensity activities, basketball-specific activities, and between the different monitoring approaches. Accordingly, we recommend further research to inform the development of consensus guidelines outlining suitable approaches when setting external load intensity zones and accompanying thresholds in research and practice.

Do Elite Basketball Players Maintain Peak External Demands throughout the Entire Game?

Consideration of workload intensity and peak demands across different periods of basketball games contributes to understanding the external physical requirements of elite basketball players. Therefore, the aim of this study was to investigate the average intensity and peak demands encountered by players throughout game quarters. PlayerLoad per minute and PlayerLoad at three different time samples (30 s, 1 min, and 3 min) were used as workload metrics. A total of 14 professional elite male basketball players were monitored during 30 official games to investigate this. A linear mixed model and Cohen's d were employed to identify significant differences and quantify the effect sizes among game quarters. The results showed a significant, moderate effect in PlayerLoad per minute between Q1 vs. Q4, and a small effect between Q2 and Q3 vs. Q4. Furthermore, a small to moderate decline was observed in external peak values for PlayerLoad across game quarters. Specifically,, a significant decrease was found for the 3 min time window between Q1 and other quarters. The findings from the present study suggest that professional basketball players tend to experience fatigue or reduced physical output as the game progresses.

A Narrative Review of the Most Demanding Scenarios in Basketball: Current Trends and Future Directions

Since the analysis of most demanding scenarios (MDS) in basketball has improved the practical knowledge about match demands and possible impacts for the training process, it seems important to summarize the scientific evidence providing useful information and future directions related to MDS. This review assesses the results reflected in the available literature about the MDS in basketball, synthesizing and discussing data from scientific papers, and then providing relevant insights about terminology, sex and sample size, competition category, workload variables recorded, technology used, method of calculation, time windows analyzed, and activities evaluated related to MDS. Therefore, the present narrative review would be of practical use for coaches, scientists, athletes as well as strength and conditioning trainers exploring the current trends and future directions related to MDS in basketball.

The discriminative, criterion, and longitudinal validity of small-sided games to assess physical fitness in female basketball players

The validity of small-sided games (SSG) for assessing physical fitness was evaluated in 21 female basketball players from senior (n = 8), under-18 years (n = 6), and under-16 years (n = 7) age categories. Players underwent fitness testing (countermovement jump [CMJ], agility T-test, repeated-sprint ability (RSA) test, and Yo-Yo Intermittent Recovery Test [YYIRT1]) and 3vs3-SSG before and after a 6-week preseason. Player demands were monitored during SSG using local positioning system and heart rate technology. Regarding discriminative validity, senior players produced better CMJ, agility T-test, and YYIRT1 performance (p  < 0.05, effect size [ES] = 1.72-2.25), and more distance and PlayerLoad (p  < 0.05, ES = 1.53-2.47) during SSG than under-18 players following the preseason. For criterion validity, total distance and distance completing high-intensity decelerations during SSG were significantly (p  < 0.05) correlated with CMJ (r = 0.44-0.66), YYIRT1 (r = 0.43-0.63), agility T-test (total distance only, r=-0.51), and RSA test performance (r=-0.49 to -0.52) among all players combined following the preseason. Regarding longitudinal validity, significantly better agility T-test and YYIRT1 performance (p ≤ 0.001, ES = 0.88-0.93) alongside lower heart rate during SSG (p = 0.001, ES = 0.88) were evident for all players combined following the preseason. These results partially support the validity of 3vs3-SSG to assess physical fitness in female basketball players.

Physical Demands of Elite Male and Female 3 × 3 International Basketball Matches

ABSTRACT

Ferioli, D, Conte, D, Rucco, D, Alcaraz, PE, Vaquera, A, Romagnoli, M, and Rampinini, E. Physical demands of elite male and female 3×3 international basketball matches. J Strength Cond Res 37(4): e289-e296, 2023-This study aimed to (1) characterize the physical demands of 3 × 3 basketball games during live playing time and ball possession and (2) assess the differences in physical demands between male and female players. Following an observational design, video footage from 27 games of the International Basketball Federation 3 × 3 World Cup 2019 were analyzed from 104 international 3 × 3 basketball players ( n = 52 male and n = 52 female players) resulting in a total of 216 (104 male and 112 female) individual game samples. Manual frame-by-frame time-motion analyses determined the relative frequency (n·min -1 ) and duration (%) for several physical demands at different intensities, according to sex, during the live playing time and in ball possession phases. Linear mixed models for repeated measures and effect size (ES) analyses revealed small non-significant differences in the intermittent profile of 3 × 3 basketball games according to sex (total movements per minute, male = 39.3 (38.6-40.1); female = 40.2 (39.5-41.0), estimated marginal means with 95% confidence intervals). Female competitions had significantly greater number of low-intensity activities (LIA, small ES) and high-intensity activities (HIA, small ES) performed per minute over longer games ( small ES), whereas male players had more recovery activities ( small ES). During ball possession, male players spent a larger amount of time performing LIA ( small ES) than female players, who displayed both the greatest number of HIA and the highest percentage of playing time performed at high intensity ( small ES). Overall, these findings suggest that basketball coaches should design sex-specific training sessions based on the specific match demands.

STRENGTH AND QUALITY TRAINING OF BASKETBALL PLAYERS

ABSTRACT Introduction: Quality exercise training of young people is a fundamental basic requirement for developing physical fitness in college basketball teaching. Objective: Enhance exercise training in young basketball players. Methods: A random selection of 50 student volunteers was made for this research. The strength and quality of basketball players of different ages were analyzed. The experimental group was subjected to specific strength training, while the control group was subjected to routine physical exercises. The experiment period was 12 weeks, and the specific technical indicators of the athletes were collected before and after the end of the experiment. The collected data were statistically treated and discussed in light of the scientific literature. Results: No significant difference was found between the two groups in the initial test score (P>0.05). The experimental group’s performance in exercise was better than the control group after 12 weeks (P<0.01). The experimental group demonstrated better performance than the control group in the standing jump, 15-meter reentry, and forward jump, corroborating the significantly different data between the two groups (P<0.01). Conclusion: This study aimed to study the unique role of strength training in the physical training of young basketball players. Special strength training positively affects upper limb muscle training in young basketball players. The lower extremities of basketball players showed expressive functional gains with special strength training. Level of evidence II; Therapeutic studies - investigation of treatment outcomes.

The distribution of different intensity demanding scenarios in elite rink hockey players using an electronic performance tracking system

Despite the traditional use of average values for determining physical demands, the intermittent and fluctuating nature of team sports may lead to underestimation of the most demanding scenarios. All the most demanding scenario-related investigations to date only report one maximal scenario per game, the greatest. However, the latest research on this subject has shown additional scenarios of equal or similar magnitude that most researchers have not considered. This repetition concept started a new way of describing competition and training loads; then the study aims were: first, to quantify and assess differences between playing positions in terms of the most demanding scenarios in official matches; and second, to quantify and assess the differences between playing positions in the repetition of different intensity scenarios relative to the most demanding individual scenario. We monitored nine professional rink hockey players (7 exterior and 2 interior players) in 18 competitive matches using an electronic performance tracking system. The interior players are closest to the opponent's goal, while the exterior players are farthest from it. Peak physical demands variables included total distance (m), distance covered at >18 km·h-1 (m), the number of accelerations (≥2 m∙s-2, count) and decelerations (≤-2 m∙s-2, count) in 30 s. An average from the top three individual most demanding scenarios was used to define a reference value to quantify the distribution scenario repetition during matches. The results showed that peak demands in rink hockey are position-dependent, with more distance covered by exterior players and more accelerations performed by interior players. In addition, rink hockey matches include multiple scenario exposures that are close to the peak physical demands of a match. Using the results of this study, coaches can prepare tailored training plans for each position, focusing on distances covered or accelerations for exterior players.

The Maximal Intensity Period: Rationalising its Use in Team Sports Practice

Quantifying the highest intensity of competition (the maximal intensity period [MIP]) for varying durations in team sports has been used to identify training targets to inform the preparation of players. However, its usefulness has recently been questioned since it may still underestimate the training intensity required to produce specific physiological adaptations. Within this conceptual review, we aimed to: (i) describe the methods used to determine the MIP; (ii) compare the data obtained using MIP or whole-match analysis, considering the influence of different contextual factors; (iii) rationalise the use of the MIP in team sports practice and (iv) provide limitations and future directions in the area. Different methods are used to determine the MIP, with MIP values far greater than those derived from averaging across the whole match, although they could be affected by contextual factors that should be considered in practice. Additionally, while the MIP might be utilised during sport-specific drills, it is inappropriate to inform the intensity of interval-based, repeated sprint and linear speed training modes. Lastly, MIP does not consider any variable of internal load, a major limitation when informing training practice. In conclusion, practitioners should be aware of the potential use or misuse of the MIP.

The Distribution of Match Physical Activities Relative to the Most Demanding Scenarios in Professional Basketball Players

The purpose of this study was to examine the distribution of physical activities relative to the most demanding scenarios across playing positions during official basketball match-play. Twelve professional basketball players were monitored during twelve matches using a local positioning system. Peak physical demands were measured via total distance covered, distance covered >18 km·h^-1, and the number of accelerations and decelerations >3 m·s^-2 captured over 30- and 60-s rolling averages. The results showed that players were exposed to more than one high-demanding scenario in all variables and time epochs examined. Additionally, total distance covered presented the greatest number of moderate-demanding scenarios (40-80% of most demanding scenarios), whereas distance covered >18 km·h^-1, and accelerations and decelerations >3 m·s^-2 presented the greatest proportion of low-demanding scenarios (<40% of most demanding scenarios). Regarding positional differences, backcourt players generally experienced a higher number of scenarios than frontcourt players in most variables, especially in total distance covered. For this variable, scenarios between 20 and 70% of most demanding scenarios during the 30-s epoch (p < 0.001; ES = 0.420.78), and scenarios between 50 and 90% of most demanding scenarios during the 60-s epoch (p < 0.001; ES = 0.400.64) showed significant differences between backcourt and frontcourt players. Our data suggest that match physical activities are position-dependent and variable-dependent. In addition, peak physical demands appear to be repeated during basketball competition. These results may be considered by practitioners to complement average values and most demanding scenarios when prescribing individualized training programs to optimize team performance.

Relationship Between Game Load and Player's Performance in Professional Basketball

PURPOSE

The purpose of the study was to examine the relationships between external and internal loads, and their ratio (efficiency index), with game performance between backcourt and frontcourt professional basketball players.

METHODS

Game loads of 14 basketball players were monitored during 6 games. External load variables measured were total distance (TD); distance >18 km·h-1, commonly known as high-speed running (HSR); and number of accelerations (ACC) and decelerations (DEC) >3 m·s-2, whereas the internal load variable measured was average heart rate (HRmean). The ratio between external and internal load variables was calculated and defined through 4 efficiency indexes (TD:HRmean, HSR:HRmean, ACC:HRmean, and DEC:HRmean). Furthermore, basketball performance was quantified using game-related statistics.

RESULTS

TD presented a small association with basketball performance, whereas the other external load variables and the 4 efficiency indexes calculated showed trivial relationships with game-related statistics. Furthermore, HRmean showed the greatest (small) associations with individual performance (P = .01-.02; r = .19 to .22). Regarding specific positions, the only 2 variables that presented significant differences were DEC (P = .01; d = 0.86) and DEC:HRmean (P = .01; d = 0.81), which showed higher values in backcourt players compared with frontcourt players.

CONCLUSIONS

The results suggest that the best performances of basketball players during official competition are not associated with higher game loads. This illustrates the necessity to assess basketball performance from a holistic approach and consider more than just external and internal variables to better understand the players' performance during basketball competition.

Fluctuations in External Peak Demands Across Quarters During Basketball Games

The purpose of this study was to compare external peak demands (PDs) across quarters (Q) in basketball. Thirteen elite, junior, male basketball players were monitored using electronic performance tracking systems. There were studied intervals for different time windows to determine the external PD for distance (m); player load; distance covered in four different zones; accelerations; and decelerations. A mixed linear model was run to identify differences among quarters, and the auto-correlation function was carried out to determine fluctuations across the whole game. The results showed significant differences between Q1 vs. Q2 for distance, player load, and standing–walking distance; between Q1 vs. Q3 for distance, player load, and HSR; between Q1 vs. Q4 for distance, player load, standing–walking, and HSR; and between Q3 vs. Q4 for distance and player load. These findings suggest that external PD for running-based demands (distance, player load, and high-speed running) decrease across basketball games with the most notable declines occurring between the first and fourth quarters. Nevertheless, it is important to note that non-significant differences were found between quarters for several external PD variables (jogging, running, acceleration, and deceleration) across different time windows. Findings from the present study reinforce the importance of considering specific PD variables for different functions due to the specific insight each provides.

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.

Local Positioning System-Derived External Load of Female and Male Varsity Ice Hockey Players During Regular Season Games

Purpose

The purposes of this study were to quantify the external load for female and male varsity ice hockey players during regular season games using a local positioning system (LPS), compare LPS-derived external load between sexes and positions, and compare skating distances in absolute and relative speed zones.

Methods

Data were collected for 21 female (7 defense, 14 forwards; 20.0 ± 1.4 yrs., 69.1 ± 6.7 kg, 167.1 ± 5.4 cm) and 25 male (8 defense, 17 forwards; 21.9 ± 1.1 yrs., 85.9 ± 5.4 kg, 181.1 ± 5.2 cm) varsity ice hockey players. Measures included skating distance (total, and in absolute and relative speed zones), peak skating speed, peak acceleration and deceleration, accumulative acceleration load, and number of accelerations, decelerations, turns, skating transitions, direction changes, and impacts.

Results

Female and male players had a high external load during games, with average peak skating speeds >28 km/h and average skating distances >4.4 km. Most LPS-derived measures showed greater external load in males than females (p < 0.05). Forwards skated further at higher speeds compared to defense in both sexes (p < 0.001). Skating distances were significantly different when comparing absolute and relative speed zones (p < 0.001), with absolute speed zones potentially overestimating skating at very slow, very fast, and sprint speeds and underestimating skating at slow and moderate speeds.

Conclusion

This was the first study to measure external load in female ice hockey players with a LPS. Both female and male varsity players had high external loads during games, with forwards having greater external load at higher intensities and defense having greater external load at lower intensities. Sex and positional differences outline the importance of individualized athlete monitoring.

Higher Playing Times Accumulated Across Entire Games and Prior to Intense Passages Reduce the Peak Demands Reached by Elite, Junior, Male Basketball Players

The aim of this study was to analyze the effects of different factors on the external peak demands (PD) encountered by elite, junior, male basketball players in games, including the (1) total playing time during games and (2) playing time accumulated directly prior to each PD episode. Workload variables included the PD for total distance, distance covered in different intensity zones, accelerations >2 m·s-2 (ACC), decelerations <-2 m·s-2 (DEC), and PlayerLoad. PD were calculated across different sample durations for each variable. Linear mixed models were used to identify differences in PD between groups based on playing times. PD for total distance (5-min window), high-speed running (>18 km·h-1) distance (2-min window), and ACC (30-s, 45-s, 1-min, 2-min, and 5-min windows) were significantly (p < .05) higher for players who completed lower total playing times (16.6 ± 2.4 min) than players who completed higher total playing times (25.0 ± 3.4 min). The PD for total distance (30-s, 45-s, 1-min, and 2-min windows), high-speed running distance (30-s and 5-min windows), and PlayerLoad (1-min and 2-min windows) were significantly (p < .05) higher for players who accumulated lower playing times before each PD episode than players who accumulated higher playing times before each PD episode. Players who undertake less playing time overall and prior to each PD episode can reach higher peak external loads aggregated across varied time windows. These findings can inform tactical coaching decisions during games for high external loads to be accomplished during important passages of play.

The most demanding scenarios of 5-on-5 modified scrimmage situations in elite basketball

BACKGROUND

The most demanding scenarios and physical demands of elite basketball 5-on-5 scrimmages are unknown to trainers, although recent advances in microtechnology allows the gaps in this research to be filled. The purpose of this study was to describe and compare the physical demands, through the most demanding scenarios and traditional average measures, of two different 5-on-5 scrimmage situations executed during training sessions in elite male basketball players.

METHODS

Physical demand measures (i.e., total distance covered, high-speed running distance, number of high-intensity accelerations actions, number of high-intensity decelerations actions) were collected from 12 players from the Spanish first Division using a Local Positioning System. Measures were compared via a Bayesian inference analysis, considering playing in half-court (HALF) and half-court and transition (HTRAN) conditions for the 5-on-5 scrimmage.

RESULTS

This study showed that, irrespective of the approach used to quantify the physical demands (traditional [average measures per minute] and novel rolling average time epoch [most demanding scenarios]), during the HALF condition players covered less and performed a lower number of high-intensity accelerations and decelerations than in HTRAN (Bayesian factor >10 and standardized effect size >0.6). Furthermore, players' physical demands during 5-on-5 scrimmage situations, independently of the court size, were underestimated consistently by the traditional approach.

CONCLUSIONS

Quantifying players' physical demands through the rolling approach may provide a more accurate measure of the most intense periods of activity. Based on the physical demands described, HTRAN may be used to help train players to perform optimally during the most physically-stressful scenarios of match-play whereas HALF may be more suitable to be included in warm-ups, recovery sessions and sessions immediately before a match.