## 1 Introduction  
Sports performance is a multifactorial phenomenon that depends on the interaction between different scientific fields. That is, it is known that physiology [1], biomechanics [2], nutrition [3], and psychology [4] (among others) play a fundamental role in improving performance. Of these, biomechanics receives much attention because researchers, coaches, and practitioners focus on motion analysis. Motion analysis in sports is considered to be the recording of sports movements and the subsequent computation of meaningful parameters describing the movement from raw kinematic data [5]. Therefore, the information provided to athletes is considered of great importance for the improvement of their performance. In the past, motion analysis in sports was often based on video analysis [6; 7]. However, due to the time-consuming process of data acquisition and handling [8], researchers are choosing a different method. Nowadays, the use of wearables (i.e., any technological device that can be worn or used as an accessory) is becoming a major approach. Wearables detect sport-specific movements and quantify sports demands that other monitoring technologies may not detect [9; 10]. In the case of swimming, the limitations of video analysis are even more challenging because the cameras are mounted in an aquatic environment. Thus, using wearables consumes less time, provides immediate feedback, and allows data recording without the restriction of distance [11]. Additionally, wearables allow the delivery of more comprehensive data to coaches and, consequently, immediate feedback to swimmers. Swimming velocity depends on the interaction between propulsive and resistive forces (i.e., drag) [12]. The literature reports substantial information on the drag of swimmers, indicating that swimmers who have a better hydrodynamic profile are more likely to perform better [13; 14; 15]. However, less information can be found on the swimmers' propulsion despite the theoretical idea that greater propulsion leads to faster swimming velocities. Nonetheless, based on experimental setups, it has been reported that faster stroke frequencies lead to greater propulsive force [16], and greater propulsive force leads to faster swimming velocity [17]. It must be highlighted that these experimental findings were only possible based on wearables that allow the swimmers to perform \"freely\", i.e., without any mechanical restriction. Moreover, it has been argued that increasing propulsion by itself or reducing drag alone may not provide better performance [18]. That is, swimmers must generate a great propulsive force while maintaining the \"best\" possible hydrodynamic position to take advantage of the achieved propulsion and reduce drag as much as possible. It was recently reported that the active drag coefficient (C\({}_{\text{Da}}\)) is the variable that best represents the hydrodynamics of swimmers [19]. Additionally, the authors mentioned that the C\({}_{\text{Da}}\) can be estimated based on drag or propulsive measurements (which in the past was estimated only through drag measurements) [19]. Therefore, in addition to the advantages of using wearables in general, and for propulsive force in particular, researchers and coaches can also obtain access to the C\({}_{\text{Da}}\). The literature on swimming, specifically on maximum trial measurements, usually reports data based on the average of that same maximum trial [14; 20]. However, it was argued that the average of a set of variables may not provide accurate insights about a given performance [21; 22]. In elite-level swimmers competing in European Championships (long-course, i.e., 50 m length, swimming pool), it was observed that sprinting swimmers tend to decrease their swimming velocity along a short-distance event [23]. It was also observed that the stroke frequency and the stroke length tended to increase over the race [23]. Similar findings were observed in high-level swimmers during 25 m maximum trials [17; 21].