Key result
The distance from the next match significantly determined workload dynamics, with training sessions two days before a match (MD-2) eliciting the highest cognitive, internal, and external loads (p < 0.001).
Why the study?
The study was conducted to describe training load dynamics, determine differences in cognitive, external, and internal load across sessions, and assess relationships among these load variables to monitor athlete performance.
Observational (n=10)
No
p-value: p=<0.001
In professional women's basketball, the distance from the next match determines workload dynamics, with increasing uncertainty and specificity throughout the microcycle causing increased cognitive load.
Load monitoring with cognitive metrics may refine periodization in women's basketball; leaves open whether integrated CL-EL-IL tracking improves outcomes.
This study aims to describe the dynamics of training loads during specific training sessions, to determine the possible differences among the metrics of Cognitive Load (CL), External Load (EL) and Internal Load (IL) between training sessions and to assess the possible relationship between the CL, EL and IL variables to completely monitor the athletes’ performance level. Ten professional female basketball players (age 26.45 ± 3.5 years) took part in this descriptive study throughout the second round of competition, completing a total of 11 competitive microcycles. The training sessions were classified according to the distance between the previous game and the next one (MD +/− X), making distinctions between MD + 2, MD-4, MD-3, MD-2 and MD-1. The following descriptive variables of the tasks were recorded: specificity, number of players, playing space, time pressure, decision-making and competitive stimulus. The analyzed variables were rate of perceived cognitive exertion (RPE Cog) and heart rate variability (HRV) for CL, total amount of high intensity actions (HI-T) and total sum of accelerations – decelerations (AD-T) for EL, and rate of perceived exertion (RPE) and summated heart rate zones (SHRZ) for IL. The load dynamics showed an increase in uncertainty throughout the microcycle, progressing from less to more specific, and a load distribution in which MD + 2 and MD-1 show the lowest values and MD-4, MD-3 and MD-2 the highest. Significant differences ( p < 0.01) were found between sessions for all the analyzed variables. Possible relationships between the CL, EL and IL metrics were also established. This study shows the reality of a professional team, where the distance from the next match determines the dynamics of the workload, promoting an increase in uncertainty and specificity throughout the microcycle, thus causing an increase in cognitive load.
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Fuster et al. (2025) conducted an observational in Professional women's basketball (training load monitoring) (n=10). Training sessions classified by distance to next match vs. Comparisons across different days (MD+2, MD-4, MD-3, MD-2, MD-1) was evaluated on Differences in training load variables (RPE, RPE Cog, sRPE, sRPE Cog, SHRZ, HI-T, AD-T) across microcycle sessions (p=<0.001). The distance from the next match significantly determined workload dynamics, with training sessions two days before a match (MD-2) eliciting the highest cognitive, internal, and external loads (p < 0.001).
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