Supplementary Table 1. Detailed characteristics of the included studies by analytical category
Description
This dataset summarizes the detailed characteristics of studies included in a review on training load monitoring, recovery, fatigue, readiness, periodization, predictive modelling, and decision-support systems in handball and comparable team sports. The table organizes the literature into six analytical categories: internal and external load monitoring; microcycle structure, competitive congestion, and weekly periodization; well-being, recovery, fatigue, and readiness; predictive models, machine learning, and decision-support systems; handball-specific studies; and complementary evidence from comparable team sports. For each study, the dataset records the year of publication, authors, title, research objective, study design, methodology, main results, and conclusions. Overall, the table shows that contemporary team-sport research increasingly supports integrated, multivariable approaches to training-load management. Across the included studies, internal load measures, external load indicators, wellness questionnaires, recovery markers, neuromuscular assessments, contextual factors, and predictive models are commonly combined to better understand athlete responses and support individualized training decisions. The evidence suggests that training load and recovery responses vary according to sport, playing position, player role, competition time, microcycle structure, match congestion, and season phase. In handball-specific studies, particular emphasis is placed on the need to individualize monitoring and recovery strategies according to positional demands, match exposure, accumulated workload, and congestion. The dataset can be used to support evidence mapping, literature synthesis, systematic review coding, and the development of multicomponent models for training planning and load regulation in team sports.