Sport training requires a balance between periods of overload and recovery; therefore, monitoring internal and external athlete loads in training and competition are beneficial to prescribing training and tracking recovery. Previous athlete load research has addressed primarily men's field sports and thus, limited information exists for women's basketball. Purpose: To determine markers of internal and external athlete load during the 9-week period of conference play for all practices (n = 39) and games (n = 16). Methods: National Collegiate Athletic Association Division I women's basketball athletes (n = 6; mean ± SD age: 20.2 ± 0.4 years; body mass: 71.8 ± 9.1 kg; body height: 173.17 ± 9.28 cm; body fat: 20.1 ± 5.8%; Vo2max: 42.1 ± 4.1 ml/kg/min) participated. For inclusion in data analysis, athletes played =15 minutes in 80% of the 16-game conference schedule. Internal load markers based upon heart rate (HR) response were measured using portable wireless HR monitors. These internal markers included training impulse (TRIMP), TRIMP per minute (TRIMP/min), and time spent in 5 HR zones based upon maximum HR percentage (%HRmax): (a) recovery (REC: 50-60% HRmax), (b) aerobic#1 (AZ1: 60-70% HRmax), (c) aerobic#2 (AZ2:70-80% HRmax), (d) anaerobic (ANZ: 80-90% HRmax), and (e) high intensity (HITZ: 90-100% HRmax). Markers of external load measured with GPS/GNSS technology included: total jumps (TJ), player load (PL), player load per minute (PL·min-1, and inertial movement analysis (high =3.5 m/s (IMA high). Multiple analysis of variance was used to assess mean differences in all load variables for practices and games (p < 0.05). Results: Game measures were significantly higher than practice for internal load variables of TRIMP (p < 0.001), TRIMP/min (p < 0.001), AZ1 (p = 0.002), AZ2 (p < 0.001), ANZ (p < 0.001), and HITZ (p < 0.001) as well as for external load variables of PL (p < 0.001), PL/min (p < 0.000), IMA high (p < 0.001), and TJ (p < 0.002). External load measures of practice and game intensity and the ratio of practices to games are presented in Table 1 (mean ± SD). In practice, athletes performed 42% of game level IMA high efforts, 66% of game level PL·min-1, 43% of game level PL, and 58% of game level TJ. Conclusions: All athlete load markers were higher in games compared to practices. In order to avoid non-functional overreaching, promote recovery, and reduce the risk of injury, selected practices should be designed with the goal of achieving game load metrics. Practical Application: The monitoring of internal and external athlete load variables enables coaches to compare practice measures with game measures. Such comparisons may provide a better understanding of how specific drills and practice plans affect athletes as well as serve to inform training program design and implementation.
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