An understanding of physical demands during official competitions is essential to achieving the highest performance in handball. The aim of this systematic review was to summarise the available scientific evidence associated with physical demands during official competitions in elite handball according to playing positions, competition level and gender. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, 17 studies were selected after a systematic search and selection process of three digital databases: PubMed, Web of Science and Sport Discus. The quality of the selected studies was evaluated using the Strengthening the Reporting of Observational Studies in Epidemiology checklist; the average score was 18.47 points. The sample consisted of 1175 handball players, of whom 1042 were men (88.68%) and 133 were women (11.32%). The results show that an elite handball player covered on average 3664.4 ± 1121.6 m during a match. The average running pace was 84.8 ± 17.2 m∙min⁻¹. The total distance covered was largely greater in national competitions (4506.7 ± 647.9 m) compared with international competitions (2190.3 ± 1950.5 m) (effect size (ES) = 1.2); however, the running pace did not present any significant difference between the international or national level (ES = 0.06). In regard to gender, the total distance covered was moderately greater in female competitions (4549.1 ± 758.6 m) compared with male competitions (3332.6 ± 1257.7 m) (ES = 0.9), and the running pace was largely greater in female competitions (110.5 ± 7.2 m∙min⁻¹) compared with male competitions (78.4 ± 19.7 m∙min⁻¹) (ES = 1.6). In relation to playing position, backs and wings covered a moderately greater total distance (ES = 0.7 and 0.6) and slightly more meters per minute (ES = 0.4 and 0.2) than pivots. Moreover, the technical activity profile differed between playing positions. Backs performed moderately more throws than pivots and wings (ES = 1.2 and 0.9), pivots exhibited largely more body contact than backs and wings, and wings performed moderately more fast breaks (6.7 ± 3.0) than backs (2.2 ± 2.3) (ES = 1.8). Therefore, this research study provides practical applications for handball coaches and strength and conditioning professionals with respect to designing and implementing more individualised training programmes to maximise performance and reduce injury risk.

The aim of the present study was to compare external loads (EL) between elite, junior, male and female basketball players. Male (n = 25) and female players (n = 48) were monitored during 11 competitive matches (3 matches per team). EL was measured using local positioning system and microsensor technology to determine total, high-intensity (14–21 km·h⁻¹), and sprint (>21 km·h⁻¹) distance (m) covered, total (n) and relative (n·min⁻¹) accelerations and decelerations, ratio of accelerations:decelerations, and total (arbitrary units [AU]) and relative (AU·min⁻¹) player load. EL was compared between sexes overall and according to each playing position (guards, forwards, and centers). Males covered larger (p < 0.05) high-intensity and sprint distances, and completed more (p < 0.05) decelerations than females; while female players experienced a greater (p < 0.05) ratio of accelerations:decelerations. Greater decelerations (p < 0.05) were observed for males in the guard position compared to females, while more (p < 0.05) accelerations·min⁻¹ were apparent for females in the forward position compared to males. The current findings indicate differences in EL, particularly the high-intensity and acceleratory demands, exist between elite, junior, male and female basketball players during competition and are affected by playing position. These outcomes can be used in developing sex- and position-specific training plans, and in turn improving the physical preparedness of junior basketball players for competition demands at the elite level.

Given the intermittent nature of basketball and the different demands that occur during playing time that are specific to every level of competition, the ratio of accelerations/decelerations and the intensity level across quarters were evaluated in female elite junior basketball players (n = 48; age: 16.8 ± 0.7 years; height: 1.76 ± 0.07 cm; body mass: 67.2 ± 6.2 kg). The following variables were analyzed to determine physical persistency across game quarters:(a) total distance covered (m), (b) high-intensity running (HIR) (14–21 km·h⁻¹) distance covered (m), (c) sprint (21–30 km·h⁻¹) distance covered (m), (d) total accelerations (n), (e) total decelerations (n), (f) relative accelerations (n·min⁻¹), (g) relative decelerations (n·min⁻¹), (h) ratio of acceleration/deceleration (A/D), (i) total jumps (j) relative jumps (n·min⁻¹) (k) player load (AU). using the WIMU PRO^® system. Higher but shorter acceleration intensity occurred during the last quarters due to the tight results of the matches. The results suggest that high-intensity efforts such as sprints and HIR seem to increase the A/D ratio (guard and forward positions). Therefore, specific conditioning, as well as eccentric strength training, could be included by practitioners in training programs to improve the performance of these positions during competition, especially as a prior preparation to a game-congested event. Centers seem to have a more variable performance through quarters than do other positions, perhaps highlighting the need for specific conditioning strategies.

Organised sport is one potential antidote to the global youth inactivity crisis. Therefore, understanding why young people drop out constitutes a key research endeavour. In part I of this series, we developed and validated a new Youth Sport Dropout Questionnaire (YSDQ). In part II, we used the YSDQ-LV (49-item long version) to examine dropout in 960 university students from seven European countries. A four-stage analysis investigated the relative and combined importance of dropout reasons. Three items—the rocks—were statistically more important: “I prioritised schoolwork and had no time left to take part in sport”; and “I found other things that I enjoyed doing more than sport”; and “I found it stressful when I did not perform/play as well as I expected”. On average, however, these rocks were rated as “moderately important”, along with 19 reasons (the pebbles) rated as “slightly important to moderately important”, and the remaining 27 reasons (the sand) rated as “slightly important to not at all important”. These findings suggest that sport dropout is not caused by a single reason but is underpinned by a dynamic tricky mix of reasons—a series of rocks, pebbles, and sand unique to each young person.

Background: Combining sports and studies could be stressful, but beneficial for the athletes’ career development. This study explores resources and barriers in the combination of the sports and academic life spheres during the lifespan of elite Spanish track-and-field athletes. Methods: Seven elite Spanish track-and-field athletes participated in a semistructured interview about their experiences to establish a dual career combining sports and studies/work. Interpretive phenomenological analysis (IPA) followed to analyze data. Results: Findings show that elite Spanish track-and-field athletes face educational and institutional barriers to developing a dual career. Time management, social support, and additional resources could play a key role in the success or failure to develop a dual career. Conclusions: This study shows that, to overcome dual-career barriers, athletes are resourceful if social support is provided at both the micro (coaches, families, etc.) and macro (political and educational institutions) levels. It also shows that pursuing an academic career can help in alleviating inherent tensions to athletic life and in finding personal balance.

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.