The evaluation of physical fitness in team sports is enjoying greater importance in the training of professional teams. The objectives of this research were to characterize physical fitness and game indicators based on the game position. This is an empirical study, with a quantitative, descriptive and cross-sectional methodology. In addition, different relationships between the level of physical fitness and the game indicators during the competition were determined. Finally, a predictive analysis of the selected variables was carried out in order to know the importance of the variables in the performance and at what time of the season they had the greatest impact. For this, a professional female basketball team (n = 12) with a mean age of 25.25 ± 7.617 years, height 178.25 ± 9.206 cm and a body mass of 72.33 ± 11.657 kg was analyzed. Each player was equipped with a WIMUPRO inertial device, and all competition statistics were analyzed. The results obtained show that there were no differences among all the skills evaluated and game indicators depending on the game position. Likewise, a relationship was determined between the level of physical fitness and the technical–tactical contribution, being different between different times of the season. Moreover, physical fitness only predicted the player’s final performance in the competition for female player centers in the first and second rounds of the championship, and for forwards in the first round. Four physical-physiological profiles with contributions to the different ones during the competition were also determined. Finally, three groups of female players by playing position were identified according to their sport performance, namely PIR, high, medium and low ratings, associated with physical performances. In all groups, there were significant differences between playing positions, PIR and physical performances.

There is research that has shown how individual characteristics and performance indicators influence the load in basketball; however, studies on the influence of situational variables on performance are lacking. The aim of this study was to determine the influence of certain situational and individual variables on the training load (weekly load, game load and pre-game recovery) and the individual performance (statistical game evaluation) of female basketball players of Liga Femenina 2 during competition. The 28 games played by the 13 players of a group B team of the Liga Femenina 2 of the Spanish Basketball Federation (FEB) during the 2020/2021 season were analyzed. Data on rate of perceived exertion (RPE), perceived performance and recovery were collected through the Quanter mobile application as well as performance statistics from the FEB website. Five mixed linear analyses for repeated measures were performed to evaluate the effect of each situational and individual variable on each dependent variable (weekly load, game load, game RPE, pre-game recovery, and game statistical assessment). The results show how the weekly load increases after playing against a low-level opponent (p < 0.001). In games, the players who play the most minutes and accumulate the most load are also the most valued (p < 0.001). The pre-game recovery worsens as the season progresses (p < 0.001). After playing against a high-level opponent, the pre-game recovery values for the next game are lower (p = 0.031). The results obtained indicate that the situational and individual variables should be taken into account to monitor the workload. These results help coaches and physical trainers to better plan training weeks, taking into account the situational variables studied.

Despite significant advances in basketball analytics, professional women's leagues remain underrepresented in performance research. Understanding normative performance benchmarks in professional women's basketball is essential for informed player development, scouting, and tactical planning; however, this area remains underexplored. This study analysed ten seasons (2012-2022) of performance data from 609 players, Spain's top-tier women's league (LF Endesa). Principal Component Analysis (PCA) confirmed the adequacy of 15 key indicators normalized per minute. A two-step clustering approach identified six functional player profiles (Primary Post, Secondary Post, Playmaker, 3&D Specialist, Role Player and Versatile). Players were further stratified into high, mid, and low performers within each role using z-score tertiles. Linear mixed models revealed that High performers consistently outscored Low performers in key metrics such as 2-point and 3-point field goals made, assists, and defensive rebounds (p < 0.01). Convergent validity was supported by the overrepresentation of High performers among First Team selections and players from top-ranked teams. Normative values for each role and performance tier are presented, providing a valuable reference for talent identification and role-based benchmarking in professional women's basketball. Future research should integrate contextual variables and advanced tracking data to refine these classifications across broader competitive settings.

Growing evidence supports that early sport specialization in children and adolescents may compromise long-term athlete development and high-performance acquisition. This study aimed to determine the presence of specialised shooting roles in formative men's basketball players compared to professionals. Data from shot charts of U14 and professional basketball players during the 2020-21 and 2021-22 seasons were retrieved. Shooting zones were classified by machine learning and clustering analyses. Shooting patterns were defined as extreme field goal attempts (FGA%) from a particular shooting zone. Players who exhibited an outlier shooting pattern were considered specialists. U14 basketball players described singular shooting patterns that largely differed from professionals' requirements (p < 0.001, ES = 0.51). U14 players lacked shooting versatility (2.3% vs. 36.3%) and 3-point shooting ability (1.8 vs. 17.2%). In contrast, the professional competition was characterised by having either versatile players without specialisation (62.7%) or one-zone specialist shooters accumulating most of their %FGA in one court zone (38%). These findings suggested that increasing shooting versatility or becoming a one-zone specialist shooter could significantly impact the development and progression of young basketball players in the long term. Current formative basketball training approaches should be revised accordingly to enhance shooting skills and promote the development of polyvalent players.

Background: Basketball matches involve numerous conditioning factors which, when put together, make for a complex prediction event. However, unraveling all these elements in different studies allows the control of certain conditioning factors of the game, giving rise to more stable and controlled games. Objectives: Due to the absence of studies that analyze professional matches in women’s basketball, the aim of the present research is to analyze the influence of the result, partial result and specific positions on the load in official competition between two women’s teams that play a match simultaneously. Methods: Using an ex post facto design, 19 professional players were measured in an official match of the Spanish second division of women’s basketball, monitoring both opponents simultaneously, obtaining at all times the contrast of loads between both teams. Inertial devices were used to measure the external and internal load of each player. Parametric and non-parametric statistical difference analyses were performed, as well as two linear mixed models. Results: The results reveal significant differences in external loading when loads are analyzed as a function of match outcome. Differences between external and internal load are found when taking into account specific positions, and when including several comparisons in the analysis. The team that obtained the highest kinematic and neuromuscular load demands was the one that won the match. The specific position of guard obtained a greater physical load at the end of the match than the centers. Conclusions: Coaches should prioritize high-intensity training that replicates match demands, considering positional differences in workload to optimize player conditioning and recovery strategies for sustained performance.