Basketball is a stochastic physically demanding team sport in which both the aerobic and anaerobic energy systems are stressed during games (Stojanovic et al., 2018). In addition to cognitive requirements, jumps, sprints, accelerations, decelerations and change of directions are crucial to perform specific movements in basketball (Taylor et al., 2017). For instance, rebounding, blocking, shooting, finishing, dribbling or defending in multiple directions are teams' means to achieve their ultimate goal, namely to score and not to concede points (Ben Abdelkrim et al., 2007; 2010a; McInnes et al., 1995). Thus, knowing physical demands during basketball competition could help coaches, athletic performance staff and medical staff to optimize training and game performance.
Previous investigations (McInnes et al., 1995; Oba and Okuda, 2011; Scanlan et al., 2012; 2015) have examined the physical demands of basketball through the use of video-based movement analysis methodologies based on a subjective visual prediction of sport-specific movement intensity. However, their validity and reliability were shown to be limited and they are also a time-consuming strategy (Barris and Button, 2008). Recently, advances in technology have allowed the use of inertial micro-sensors (Montgomery et al., 2010; Reina et al., 2019; Vazquez-Guerrero et al., 2018a) to quantify variables such as high-intensity accelerations, decelerations, jumps and impacts on semiprofessionals (Fox et al., 2018; Scanlan et al., 2019) and professional male basketball players (Svilar et al., 2018a; Vazquez-Guerrero et al., 2018a). Due to the fact that global positioning systems (GPS) only work outdoors (Puente et al., 2017), local positioning systems (LPS) also allow basketball practitioners to complement information from inertial devices with positioning-derived variables such as player speed and total distance covered in different speed zones. Furthermore, it is important to highlight that LPS has been shown to be valid and reliable (Bastida-Castillo et al., 2018) in monitoring players' physical requirements (Gomez-Carmonaet al., 2019; Vazquez-Guerrero et al., 2018b).
It is still controversial whether physical demands tend to diminish at the end of basketball games. While some studies (Scanlan et al., 2012; 2015) have not been able to report significant differences after the analysis of distance and speed parameters, other investigations have found a significant decrease between the first and last quarters in high-intensity actions (Ben Abdelkrim et al., 2007; 2010a; Delextrat et al., 2017; Reina et al., 2019; Vazquez-Guerrero et al., 2019b) and player load (Scanlan et al., 2019; Vazquez-Guerrero et al., 2019b), which presents a valid and reliable estimation of whole-body load provided by inertial micro-sensors (Nicolella et al., 2013). Nevertheless, to date no study has investigated the differences in physical exertion between quarters of official games among professional basketball players using LPS.
Besides being useful in studying possible changes between quarters, microtechnology has also been used to determine the differences in physical demands between specific playing positions. For instance, the exclusive use of inertial microsensors has been applied to report differences in activity demands on professional players across positional roles during training (Svilar et al., 2018b; Vazquez-Guerrero et al., 2018b) and competition (Reina et al., 2019; Vazquez-Guerrero et al., 2018a). Although the authors of this research have no knowledge of any study that have combined inertial devices with LPS to examine game demands on professional players, this methodology have already been used to detect differences in under-18 (U18) elite basketball players (Vazquez-Guerrero et al., 2019a; 2019b; 2019c). Therefore, the aim of this study was to describe and compare physical demands between quarters and specific playing positions among male professional basketball players using inertial devices and LPS during official competition.
The subjects in this research were professional male basketball players (mean [+ or -] SD, age: 19.8 [+ or -] 1.7 years; height: 2.00 [+ or -] 0.08 m; and body mass: 91.8 [+ or -] 15.9 kg), who competed with the same team in three different playing positions: guards (n = 7), forwards (n = 3) and centers (n = 3). All players belonged to a reserve squad of a Euroleague team and participated in the Spanish second division, namely LEB Oro, during the 2018/2019 season and finished in 17th position in the league after winning nine out of the regular season's thirty-four matches. All players and coaches agreed to participate by giving their written consent after being informed about the purpose of the investigation, the research protocol and requirements, as well as the benefits and risks associated with the study. Furthermore, no ethics committee approval was needed because the data were obtained after the players were routinely monitored during training and matches in the course of the competitive season (Winter and Maughan, 2009). Nevertheless, the study fulfilled the provisions of the Declaration of Helsinki (Harriss and Atkinson, 2015).
This observational study was conducted to compare physical demands during official basketball competition. Thirteen elite basketball players were monitored during all 17 official home games in the 2018/2019 season (September-May). Players who suffered injury or played less than 10 minutes in a match were excluded, resulting in a total of 708 single records.
All games were completed on the same court in similar environmental conditions. The team played one game a week, usually between Friday and Sunday, after a standard 45-minute warm-up consisting of individual skills such as dribbling, shooting and passing. Players were allowed to drink water ad libitum during recovery periods. Furthermore, the team followed the Futbol Club Barcelona's "structured training" methodology, which has been specially designed to optimize team-sports performance and is based on coadjuvant and optimizer training. While the former training type aims to allow players to train and maximize their conditional capabilities, the latter focuses on allowing basketball players to compete and perform at their highest potential in competition (Gomez et al., 2019; Martin-Garcia et al., 2018; Tarrago et al., 2019)
Player movements were recorded using WIMU PRO[TM] (Realtrack Systems S.L., Almeria, Spain), which includes four 3D accelerometers (full-scale output ranges are [+ or -]16 g, [+ or -]16 g, [+ or -]32 g, [+ or -]400 g. 100 Hz sample frequency), a gyroscope (8000[degrees]/s full-scale output range. 100 Hz sample frequency), a 3D magnetometer (100 Hz sample frequency), a GPS (10 Hz sample frequency) and an ultra-wide band positioning system (18 Hz sample frequency). Each inertial device (81*45*16 mm, 70 g) has a gigahertz microprocessor, 8GB flash memory and a high-speed USB interface to record, store and upload data. The units were placed in a custom-made vest located in the center area of the upper back using an adjustable harness, as recommended by the manufacturer (IMAX, Lleida, Spain).
As in previous studies (Puente et al., 2017; Stojanovic et al., 2018; Vazquez-Guerrero et al., 2018a), the following variables were used to monitor physical demands, including: A) peak velocity (PV) in km*[h.sup.-1], as the highest value obtained during each game; B) total distance covered (TDC) in meters; C) distance covered >18 km*[h.sup.-1] (D18) in meters; D) player load (PL), expressed in arbitrary units and calculated as the sum of the squared rates of change in acceleration (also known as jerk) in each of the three vectors divided by 100 (Fox et al., 2018; Nicolella et al., 2013; Vazquez-Guerrero et al., 2019c) and E) the number of impacts that surpassed 8 g-forces...