## 2 Materials and Methods
### Design  
This observational and descriptive study examined the impact of playing back-to-back official games on physical demands and subjective well-being. All games were completed between Saturday afternoon (18:30 h tip-off) and Sunday morning (12:30 h tip-off) and were played following the official International Basketball Association (FIBA) rules. Participants who played \(<\)10 min of playing time on the court were excluded from the data analysis of that game [17]. The final sample had 96 individual game records, with each player analyzed multiple times (mean participation = 5.6 times, from 2 to 10 games). The team played ten home back-to-back games during five different weekends between October and March (Figure 1). Each game was preceded by a standardized 45 min warm-up consisting of muscle activation, dynamic stretching, mobility exercises, and basketball-specific skills, such as shooting, passing, and rdibling. Additionally, the team followed a team sports-specific methodology called \"structured training\" [18] to prepare the players to compete in team sports based on two types of training: coadjuvant (general off-court training, e.g., split squat and single-arm press) and optimizing (sport-specific, on-court training, e.g., small-sided games and 5-on-5 scrimmage). Within each microcycle, the team always played two games (Saturday and Sunday), rested the day after the competition (Monday), and accumulated four morning training sessions (Tuesday to Friday). The players' physical demands were continuously monitored with a local positioning system of anchors (LPS) (WIMU PRO(tm), RealTrack Systems(r) SL, Almeria, Spain), a system valid for measuring physical demands in training sessions and games [19; 20]. This ultra-wideband system includes six antennas, forming a rectangle for better signal emission and reception (Figure 2). With a sampling frequency for positioning data of 20 Hz, the LPS operates using triangulations between the antennas and the units (the six antennas send a signal to the units every 50 ms). The device then calculates the time required to receive the signal and derives the unit position (coordinates X and Y) using one of the antennas as a reference. The devices (81 \(\times\) 45 \(\times\) 15 mm, 70 g) were placed in the center of the player's upper back using a custom-made adjustable harness (IMAX). Each player wore the same assigned device during the season to limit intersystem variability [21]. The system-specific software, SPRO(tm) (version 987, RealTrack Systems(r) SL, Almeria, Spain), was downloaded and used to analyze the data on physical demands. Like previous research [17], the following variables related to game physical demands were measured: (1) relative distance covered (RD) (m\(\cdot\)min\({}^{-1}\)); (2) high-speed running distance covered (HSR) (m\(\cdot\)min\({}^{-1}\)); (3) the count of accelerations over 3 m\(\cdot\)s\({}^{-2}\) (ACC) (n\(\cdot\)min\({}^{-1}\)); and (4) the count of decelerations below 3 m\(\cdot\)s\({}^{-2}\) (DEC) (n\(\cdot\)min\({}^{-1}\)). In addition, the distance was measured via positional differentiation (change in location with each signal). Acceleration and deceleration were calculated via double differentiation from the positional data recorded by the local positioning system [22]. Moreover, absolute values of physical demands were normalized by dividing the metrics by the playing time the players remained on the court, including in-game stoppages such as time between fouls and free throws and excluding breaks among quarters and timeouts [23]. Additionally, an analysis of peak demands (PD) was conducted. Using a sampling frequency of 18 Hz, the WIMU PRO(tm) software (version 987, RealTrack Systems(r) SL, Almeria, Spain) identified 1080 consecutive data points (18 samples per 60 s) and calculated a moving average for the variables of interest over a 60 s period, identifying the maximum value from this average. This maximum value was then included in the analysis.