Background: Athletic success depends not only on physical performance and psychological well-being but also on the effective emotional regulation of adaptive processes to prevent sports injuries in stressful situations such as competition. This study analyzes the relationship between emotional state, pre-competitive anxiety, and injury incidence in female volleyball players throughout an entire competitive season. Methods: The POMS and CSAI-2 questionnaires were administered before 16 league matches to 21 high-performance players (mean age = 29.66 ± 5.19 years). Results: Players exhibited an iceberg mood profile with low levels of pre-competitive anxiety. Negative moods were higher at the start and decreased over time, while positive moods increased as matches progressed (p < 0.05). Anxiety remained stable throughout. Additionally, 28.6% of players experienced injuries; injured players showed higher cognitive anxiety, lower self-confidence, and emotional instability, suggesting a potential psychological risk profile for injury, even though group differences did not reach statistical significance. Significant correlations were found between Total Mood Disturbance (TMD) and cognitive anxiety (r = 0.49, p < 0.05) and between vigor and self-confidence (r = 0.52, p < 0.01), indicating a bidirectional relationship. A bidirectional relationship between mood and anxiety was confirmed, highlighting the POMS Total Mood Disturbance (TMD) index as a global emotional indicator. Conclusions: These findings suggest that managing worries, self-confidence, and emotional balance are key factors in injury prevention, emphasizing the importance of regularly monitoring and managing psychological indicators as part of injury prevention strategies.

The aim is to establish an specific, non-invasive, sub-maximum and applicable day-to-day protocol to assess the internal training load (IL) for basketball players using Heart Rate Variability (HRV) analysis before practice or competitions. Another aim is to propose a new IL index as a standardized parameter (%), to manage IL before practice sessions or competition. Twelve amateur male basketball players (age: 26.5 ± 8.8 years) completed HRV tests before a submaximal and intermittent drill (Activity Lay Up Wheel; ALUWIL 6min-test). Players performed a 5on5 scrimmage (MATCH) the following day during 10 min, completing rate of perceived exertion (RPE), total quality recovery (TQR) and wellness questionnaires, and continuous heart rate recordings. Players showed higher values of IL parameters based on heart rate (summatory heart rate zones, SHRZ; and training impulse, TRIMP), higher RPE values and lower recovery values during MATCH than ALUWIL (p<0.01). The parameter % of summatory of heart rate zones (SHRZ) showed stronger correlations than SHRZ and TRIMP during MATCH (p<0.001), and significant relations with RMSSD (square of the mean root of the adjacent R-R intervals) during the HRV test (p<0.05). During the ALUWIL test, %SHRZ shows higher and stronger correlations than SHRZ with RRmean (mean of the R-R intervals) (-.807) but similar than SHRZ with RMSSD. In this specific context, ALUWIL test could offer reliable and applied information as a standardized and integrated protocol to assess internal training load in basketball players using cardiac parameters before practice and games. The parameters RRMean, RMSSD and %SHRZ could be a specific indicator for IL management on basketball. However, more research is needed to validate these proposals in a complex context. Key words: HRV, internal training load, basketball, heart rate, submaximal test, SHRZ.

Review question / Objective: The objective of this scoping review is to identify the EMA methodologies through mHealth technology to monitor the sport load or the stress-recovery process in athletes. The specific objectives are: - To describe the relationship between the external (distance, accelerations, decelerations, etc.) and internal (physiological, cardiovascular, neuromuscular, subjective, etc.) parameters, and the technology used for the monitoring. - To describe and classify the methodologies and the technology used according to individual or team sports. - To analyse the relationship between the subjective and objective parameters of the internal measures.

Background: This scoping review aimed to identify how Ecological Momentary Assessment methodologies using mobile health technologies are applied to monitor training load and the stress-recovery process in athletes. The review focused on mapping the technologies and methodologies employed, examining their use in team and individual sports, and exploring the relationships between external and internal load measures, as well as the extent to which subjective and objective indicators are integrated within monitoring systems. Method: Following PRISMA-ScR guidelines, a systematic search across four databases identified 71 studies published between 2012 and 2025 that met eligibility criteria. Results: Half of studies focused on elite or international athletes (50.68%), with a predominance of male participants (63.4%). Team sports represented the vast majority (87.3%), particularly soccer (42.5%) and basketball (15.1%). A wide range of technologies was reported, from advanced wearable systems to smartphone applications, with external load commonly tracked via GPS and accelerometry, and internal load through heart rate indices, Training Impulse, Rating of Perceived Exertion, and wellness questionnaires. However, only seven studies directly compared subjective and objective measures of internal load, revealing partial convergence and underscoring the value of multimodal monitoring strategies. Conclusions: Ecological Momentary Assessment-based mobile health systems provide valuable insights into athlete load and recovery, but important gaps remain in individual sports, female representation, and recovery-related behaviors. Future research should prioritize methodological transparency, broader inclusion of populations, and the adoption of emerging non-invasive biosensing technologies to achieve a more holistic and ecologically valid model of athlete monitoring.