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Understanding the external load, particularly the peak demands (PDs), experienced by players is essential. Several factors, such as the playing time, team venue, score outcome, and match nature, can influence basketball performance. Accelerometry-based methods allow for the estimation of the load borne by athletes and the peaks they reach. The aim of this study was to analyze the influence of these factors on PDs across different time windows (30 s, 1 min, and 3 min). Eleven national-level athletes were monitored during 29 matches using measurement devices. Inertial movement units were used to measure peak PlayerLoad™ (PL) across any time window. Mixed linear models were used to compare the groups, and effect size was calculated to quantify the differences. Significant differences (p < 0.05, small effects) were found between occasional players (who play fewer minutes) and core players (who play intermediate minutes), with the latter reaching higher PDs, though with small effect sizes. Core players also reached higher PDs than top players (who play the most minutes), but the differences were not significant (p > 0.05, trivial effects). In summary, core players reach higher external PDs during competition compared to occasional players, while other contextual factors did not show a significant influence on external PDs. [ABSTRACT FROM AUTHOR]

The main aim of this narrative review is to assess the existing body of scientific literature on heart rate variability (HRV) in relation to basketball, focusing on its use as a measure of internal load and vagal nerve responses. Monitoring HRV offers insights into the autonomic function and training-induced adaptations of basketball players. Various HRV measurement protocols, ranging from short-term to longer durations, can be conducted in different positions and conditions, such as rest, training, and sleep, to determine this key metric. Consistency and individualization in measurement protocols, responding to the athlete's specific characteristics, is crucial for reliable HRV data and their interpretation. Studies on HRV in basketball have explored psychological adaptation, training effects, individual differences, recovery, and sleep quality. Biofeedback techniques show positive effects on HRV and anxiety reduction, potentially enhancing performance and stress management. The scientific literature on HRV in basketball could benefit from studies involving longer monitoring periods to identify significant trends and results related to training and recovery. Longitudinal HRV monitoring in teams with intense travel schedules could reveal the impact on athletes of all levels and ages, and, in this regard, individualized interpretation, considering the subjective recovery and fitness levels of athletes, is recommended to optimize training programs and performance. HRV provides insights into training and competitive loads, aiding in determining exercise intensities and training status. Additionally, HRV is linked to recovery and sleep quality, offering valuable information for optimizing player performance and well-being. Overall, HRV is a reliable tool for adjusting training programs to meet the specific needs of basketball players. [ABSTRACT FROM AUTHOR]

The National Basketball Association (NBA) is the major professional basketball league in the United States. Home-court advantage (HA) and home win percentage (HW) have been identified as decisive factors in determining the final outcome of a game. This study analyzes a total of 24 regular seasons, with two main objectives: (i) comparing HA and HW within the two conferences and (ii) examining the influence of team ability on HA and HW. HA (%) was calculated as (total home wins/total wins) × 100, and HW (%) as (total home wins/total home games) × 100. Teams were categorized into four different groups based on their season win percentage using cluster analyses. Regarding the first aim, we used an Independent Samples T-test and Mann–Whitney to assess differences between conferences. Subsequently, we evaluated the second objective using one-way ANOVA or Kruskal–Wallis. The results indicated no significant differences in HA within conferences. However, Western teams tended to have a higher HW than Eastern teams. The analyses revealed significantly higher HA in contender teams compared to the rest of the team abilities (p < 0.001). High–medium-ability teams also showed a significantly higher HA (p < 0.001) compared to low-ability teams. However, non-significant differences were found between the remaining groups for HA. Regarding HW, we observed significantly higher values in the contender teams compared to the teams with other ability levels (p < 0.001). Additionally, the high–medium-ability teams also exhibited significantly higher HW values (p < 0.001) when compared to the medium–low- and low-ability teams. Furthermore, the medium–low-ability teams showed significantly higher HW values (p < 0.001) when compared to the low-ability teams. Those findings suggest that team ability influences HA and HW in the NBA, where contender teams have significantly higher HW and HA values compared to the teams with other team ability levels. Understanding these dynamics provides valuable insights for team strategies, particularly during playoff stages where home-court advantage can be critical for success. [ABSTRACT FROM AUTHOR]

The purpose of this study was to identify the external demands during official under-18 basketball matches that included four quarters (Q1, Q2, Q3, Q4) and/or overtime (OT) periods. Variables included: 1) distance covered and distance covered within four intensity zones (standing-walking S-W, jogging JOG, running RUN, and high-speed running HSR); 2) explosive efforts per minute (EEs); 3) PlayerLoad (PL); 4) the number of jumps per minute; 5) the number of accelerations above 2 m·s2 (ACCs); and 6) the number of decelerations above -2 m·s2 per minute (DECs). The values for total distance, JOG, RUN, HSR, PL, ACC, and DEC were significantly smaller during periods Q2, Q3, Q4, and OT compared to Q1. In addition, the number of EEs during Q1 was significantly greater than during Q3, Q4, and OT. When comparing OT periods to Q2, there were significantly smaller values for total distance, RUN, and PL. Similarly, when comparing OT periods to Q3, significantly smaller values were found for PL. Furthermore, when comparing OT periods to Q4, significantly smaller values were achieved for total distance and PL. These findings indicate that players experienced a decrease in external physical demands as the match progressed to an OT period. This decrease may be indicative of player fatigue and/or strategic changes that should be considered by practitioners in the preparation and management of players for overall team success in junior basketball competitions. [ABSTRACT FROM AUTHOR]

This study aimed to (i) compare the extent of home-court advantage (HA) and home win percentage (HW) between Spanish basketball leagues across different playing levels (i.e., leagues) and (ii) analyze the influence of team ability on HA and HW within each playing level. We gathered data for game locations and results from open online sources for all games in the First Division (ACB), Second Division (LEB Gold), and Third Division (LEB Silver) Spanish male basketball leagues between 2010–2023. The dataset included 12 seasons, 635 teams (215 First Division, 203, Second Division, and 217 Third Division), and 19,539 games (7075 First Division, 6344 Second Division, and 5520 Third Division). We calculated HA [(total home wins/total wins) * 100] and HW [(total home wins/total home games) * 100] for each team across each season. We performed Kruskal Wallis tests, calculated partial eta squared (η p2), and performed Mann-Whitney U tests with rank biserial correlation (r b ) effect sizes and Dwass-Steel-Critchlow-Fligner pairwise comparisons to compare HA and HW between leagues and between team abilities (low, medium, and/or high) within each league. There was a significant effect for HA between leagues (p =.01) with post hoc comparisons revealing a higher HA for the First Division than for the Third Division (p =.01), but HW was not significantly different between leagues. In turn, variations in HA and HW between team abilities were consistent across playing levels, with HW significantly increasing in a progressive manner with higher team abilities (p <.001) and with HA significantly lower among high-level teams compared to lower-ability team clusters (p <.01). These findings emphasize the importance of considering playing level and team ability and interpreting HA and HW together to contextualize an apparent home advantage in Spanish basketball. [ABSTRACT FROM AUTHOR]

To compare the extent of home-court advantage (HA) and home win percentage (HW) based on sex and team ability in Spanish basketball leagues. Data from the first divisions of male and female basketball over 12 seasons (2010-2023) were analyzed. HA (%) was calculated as (total home wins/total wins) * 100 and HW (%) as (total home wins/total home games) * 100. Teams were categorized into higher-and lower-ability based on their season win percentage using cluster analyses. Mann-Whitney test was used to compare HA and HW between sexes and team ability clusters. Results showed that males exhibited higher HA and HW compared to females (p < 0.05). Additionally, males had higher HA than females within both higher- and lower-ability teams (p < 0.05) and higher HW only within lower-ability teams (p < 0.001). Lower-ability teams had higher HA than higher-ability teams (p < 0.001). while higher-ability teams had higher HW (p < 0.001). These findings suggest that team sex and ability significantly influence HA and HW effects in Spanish basketball leagues. Female teams demonstrate a more even distribution of wins between home and away venues, while lower-ability teams rely more on home games for wins. Understanding these effects can aid in developing strategies tailored to sex and ability among Spanish basketball teams. [ABSTRACT FROM AUTHOR]

This study aimed to compare the most demanding scenarios (MDS) of under-19 professional soccer players during official matches, controlling for contextual factors such as playing position, the level of opponent teams, playing venue, match status, playing surface, pitch size, and playing status of players. A total of 42 players were monitored across 27 games using Global Positioning System (GPS) technology to collect the external loads, including total distance covered, high-speed running, sprint distance, accelerations, and decelerations. MDS were calculated across 1-minute, 5-minute, and 10-minute time windows for each variable. Significant differences were found based on the contextual factors. (i) Opponent level did not show significant differences; (ii) full-backs covered more distance at 1 minute in home games; (iii) midfielders in winning vs. drawing scenarios exhibited higher decelerations at 1 minute but less distance at 10 minutes; (iv) in drawing vs. losing scenarios, central defenders had greater distance at 5 minutes and accelerations at 5 minutes, while midfielders showed greater distances at 1 minute, 5 minutes, and 10 minutes; (v) offensive midfielders and forwards displayed specific performance differences; (vi) no significant differences were found for the playing surface; (vii) regarding pitch size, full-backs covered more distance at 5 minutes on larger pitches, while midfielders covered more distance at 5 minutes and 10 minutes; and (viii) starters generally outperformed non-starter players across various variables depending on the playing positions. The findings suggest that contextual factors have a significant impact on soccer player performance across different playing positions. [ABSTRACT FROM AUTHOR]

Our main aim in this study was to analyze any differences in Win Percentages at Home (HW) that might represent a Home-Court Advantage (HA) in women's professional basketball. A secondary objective was to analyze how team ability might modify the HA effect by comparing any interaction effect between HW and team ability in games played with and without fans. We collected data from first Spanish female basketball divisions, using a linear mixed model (LMM) for repeated measures to identify differences between time periods (games with fans vs. games without fans) for HA and HW. When comparing games with and without fans, we found no significant HA and HW differences (p =.283 and p =.872, respectively). In fact, interestingly, we observed higher win values when fans were absent. Additionally, during the COVID-19 shut down stage, HA increased; but it returned to pre-pandemic levels afterward, with no significant differences between these periods (p =.482). Similarly, while HW seemed to increase during the COVID-19 shut down period and continued improving in the post-pandemic phase, there were actually no statistically significant differences (p =.772). Higher HA and HW were evident without fans during the pandemic compared to the pre-pandemic period when fans were present in women's professional basketball. During the post-pandemic period, HA decreased upon fans' return, while HW continued increasing. We discuss possible bases for these unexpected findings. [ABSTRACT FROM AUTHOR]

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.

Our aim in this study was to examine the impact of fans (vs. no fans), geographical location of league, and team ability on home winning percentage (HW%) or home advantage (HA) in professional European basketball. Data were collected from five prestigious professional, national basketball leagues within Europe (Spain, Germany, Italy, Greece and Israel) across 16 regular seasons (2005-2006 to 2020-2021). We conducted comparisons between matches with and without fans, location of leagues, team ability (High, Medium, Low), and combinations of these factors via non-parametric tests (e.g., Mann-Whitney tests, Kruskal-Wallis). We found significantly greater HA during matches with fans for leagues in Germany ( p = .001), Italy ( p = .012) and Spain ( p = .002). For matches with fans, HA and HW% were significantly different between several, but not all, leagues for high ( p < .05), medium ( p < .05) and low ( p < .02) team abilities. In conclusion, HA and HW% were enhanced by spectator attendance, with this phenomenon varying by location/region and team ability. Consideration of these multiple contextual factors may assist coaches and sport organizations to develop key strategies for enhanced team success., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

To quantify and compare the external peak demands (PD) encountered according to game result (win vs. loss), quarter result (win vs. tie vs. loss), and quarter point difference (± difference in score) in under-18 years (U18), male basketball players. Thirteen basketball players had external load variables monitored across 9 games using local positioning system technology, including distance covered, distance covered in different intensity zones, accelerations, decelerations, and PlayerLoad™. PD were calculated across 30-s, 1-min, and 5-min time windows for each variable. Linear mixed models were used to compare PD for each variable according to game result (win vs. loss), quarter result (win vs tie vs loss), and quarter point difference (high vs. low). External PD were comparable between games that were won and lost for all variables and between quarters that were won and lost for most variables (p > 0.05, trivial-small effects). In contrast, players produced higher (p < 0.05, small effects) 1-min high-speed running distance and 5-min PlayerLoad TM in quarters that were won compared to quarters that were lost. Additionally, high quarter point differences (7.51 ± 3.75 points) elicited greater (p < 0.05, small effects) external PD (30-s PlayerLoad TM , 30-s and 5-min decelerations, and 1-min and 5-min high-speed running distance) than low quarter point differences (-2.47 ± 2.67 points). External PD remain consistent (trivial-small effects) regardless of game result, quarter result, and quarter point difference in U18, male basketball players. Accordingly, external PD attained during games may not be a key indicator of team success., (Copyright © Biology of Sport 2023.)