Athlete monitoring systems (AMSs) provide a centralized platform for integrating, processing, analyzing, and graphing various monitoring data to help coaches manage the rigorous demands of elite men’s basketball players, who frequently participate in high‐stress games with minimal recovery time. This review synthesizes current challenges in deploying AMSs, underscores their role in injury prevention and performance optimization, and discusses technological advances that could enhance their utility. Key challenges include selecting appropriate monitoring methods based on human and financial resources, accuracy of data collection, real‐time data processing, and personalization of training regimens. Due to the weaknesses and limitations of each monitoring method, it is recommended that both objective (e.g., external load data, heart rate measures, and biomarkers) and subjective (athlete‐reported outcome measures) monitoring data be integrated into an AMS to provide a holistic insight of the athlete’s health and readiness. In addition, decision support systems integrated into an AMS can help coaches quickly gain an overview of their players’ current condition and make informed decisions about daily load and recovery management. In this context, future perspectives suggest the potential for AMSs to incorporate predictive analytics and artificial intelligence to further enhance decision‐making processes in elite men’s basketball. Our findings underscore the need for continued innovation and rigorous validation of AMS technologies to ensure they meet the evolving demands of professional sports environments.

Purpose: To evaluate the relationship between items of the Short Recovery and Stress Scale (SRSS) related to physical stress and recovery and the biomarker creatine kinase (CK) in professional handball. Methods: CK and SRSS items (physical performance capability, overall recovery, muscular stress, and overall stress) were assessed in an observational study of 16 adult male professional handball players from a team in the highest German league during the 2019–20 preseason. Their preseason training schedule included several microcycles, each consisting of 3 consecutive days of intense training followed by a rest day. On 5 of these rest days, when players were classified as nonrested, and the 5 immediately following days, when players were classified as rested, players completed the SRSS between 8:00 and 9:00 AM, followed by blood sampling. Correlations between SRSS items were performed using Kendall τ. The relationship between each SRSS item and CK levels over time was examined using a mixed-effects model with a random intercept. Results: CK levels and SRSS stress items were significantly higher and SRSS recovery items were significantly lower in nonrested players. SRSS items were significantly positively or negatively correlated (all items: P < .001) and showed a significant effect indicating lower CK levels in rested players (all items: P ≤ .001; ). Conclusions: The investigated SRSS items may be a viable option for assessing muscle recovery in adult male professional handball players in a cost-effective and noninvasive manner. They can be used as a single monitoring tool or as part of a multimodal approach.

Background: Athlete monitoring is becoming increasingly important in elite team sports to optimize performance and prevent injuries and other athletic health problems. A variety of objective and subjective measures are available to monitor external and internal load, well-being, and readiness to train or compete. A comprehensive Athlete Monitoring System (AMS) should include a meaningful combination of these methods and provide analysis and graphical presentation with decision support for coaches. The selection of monitoring methods to establish an AMS is influenced not only by sport-specific considerations, but also by the resources available. Our study aimed to describe the current practice of athlete monitoring in professional handball, and to examine potential gender differences. Methods: A total of 104 women’s (n = 44) and men’s (n = 60) handball teams competing in the first two national leagues in Germany and Switzerland were invited to participate in an online survey (May-August 2024). The questionnaire used for this cross-sectional study was designed by an interdisciplinary team and consisted of a maximum of 28 questions. The Mann-Whitney U test was used to test for gender differences on the extent of athlete monitoring in the following sub-areas: Injuries and illness surveillance (IIS); external and internal load; well-being and readiness. Results: The minimum response rate was 34.6% (19 men’s teams, 17 women’s teams). An IIS was performed in 75.0% of the responding teams. A total of 19 teams (52.8%) conducted further athlete monitoring, in 84.2% of cases with a comprehensive AMS, which most commonly included player tracking (13 out of 15 teams using external load measures) and the Session-Rating of Perceived Exertion-method (11 out of 19 teams using internal load measures), and customized well-being questionnaires (10 out of 18 teams using well-being measures). Men’s teams engage in significantly more IIS (94.7% men’s teams vs. 52.9% women’s teams, p =.019, δ = –0.356), player tracking (52.6% men’s teams vs. 11.8% women’s teams, p =.003, δ = –0.415) and internal load monitoring (63.2% men’s teams vs. 29.4% women’s teams, p =.015, δ = –0.387). Notably, 88.9% of teams are interested in implementing or developing an AMS. Conclusions: Our findings indicate that the majority of handball teams already use some form of IIS, and more than half of these teams have implemented an AMS, with men’s teams using significantly more player tracking, internal load and well-being measures. The apparent high level of interest in athlete monitoring highlights the importance of data-driven approaches to managing player health and performance, although selection bias must be considered. This information is valuable for practitioners seeking to implement or expand AMS in handball.

Background: Youth football players are at high risk of lower limb injuries, which can affect performance and long-term career development. However, epidemiological data on injury patterns in German elite youth football remain limited. This study aims to (1) provide an overview of lower limb injuries in German elite youth football academies and (2) investigate the association between anthropometric factors, particularly genu varum, and injury risk. Methods: This cross-sectional study included 381 healthy male football players (aged 10–23 years) from two German elite youth academies between 2021 and 2023. Injury history from the most recent full league season, including pre-season and regular season matches, was recorded. Anthropometric assessments included body composition and intercondylar distance of the knee (ICD) to evaluate genu varum. Results: A total of 140 lower limb injuries were documented, resulting in a cumulative injury frequency of 0.39 and an incidence of 1.2 injuries per 1,000 h. Most injuries were muscle-tendon injuries in the thigh (36.4%) and ligament injuries in the ankle (35.0%). Injury hot spots included lateral ligament tears in the ankle (30.0%) and muscle injuries within a triangle of the hamstrings (12.9%), quadriceps (10.7%), and adductors (11.4%) in the thigh. Injury frequency significantly increased from age 13 (p =.013; OR = 2.29), particularly in the thigh (p =.027; OR = 3.28). Regression analysis revealed a significant correlation between age (p =.038; coefficient of variation (COV) = -0.07) and ICD (p =.003; COV = -0.01) on the number of injuries, suggesting a potential link between genu varum and increased injury risk. Conclusion: This study provides the first structured overview of lower limb injuries in two German elite youth football academies and their association with anthropometric data. The findings highlight age-related injury patterns and suggest a potential link between genu varum and injury risk, underlining the need for targeted injury prevention strategies. Establishing a systematic, long-term injury surveillance system in youth football is essential for developing evidence-based interventions to reduce injury risk and support player development.

Hintergrund Das Monitoring von Athleten ist in den letzten Jahren in den Fokus des Spitzensports und der Forschung gerückt. Das Ziel ist die Optimierung der Trainings und Belastungssteuerung. Aufgrund der erheblichen Datenmenge im zeitlichen Verlauf eines Monitorings geht der Trend in Mannschaftssportarten zur Integration einer sinnvollen Auswahl von verschiedenen Monitoringverfahren in eine Softwarelösung. Zusätzlich kommen hier Systeme zur Entscheidungsunterstützung zum Einsatz, um den Trainern eine schnelle Entscheidung im Rahmen der Trainings- und Belastungssteuerung zu ermöglichen. Dieser Artikel soll einen Überblick über die Vielzahl an eingesetzten Monitoringverfahren in Kontakt-Mannschaftssportarten geben, deren Testgütekriterien berücksichtigen und eine sinnvolle Anwendung für den Hallenhandball unter Beachtung der sportartspezifischen Anforderungen prüfen. Methoden PubMed-basierte Literaturrecherche. Narrativer Review mit Fokus auf aktuellen Daten aus den Jahren 2010–2019. Ergebnisse Im Hallenhandball existieren für die Athleten je nach Spielposition verschiedene Anforderungsprofile. Daher ist eine individualisierte Belastungssteuerung notwendig. Monitoringverfahren mit nachgewiesener Validität und Reliabilität sollten idealerweise in einem multivariaten Ansatz angewendet werden, um die verschiedenen Aspekte der Belastung und Beanspruchung, Erholung und Ermüdung, Wohlbefinden und Bereitschaft zu trainieren/zu spielen darzustellen. Dabei ist es wichtig, für jeden Athleten die bedeutsame Änderung in einem Monitoringverfahren zu kennen. Dieser Umstand macht eine individualisierte Herangehensweise für jeden Zielparameter unerlässlich. Es existieren sehr wenige Studien hinsichtlich der Anwendung von Monitoringverfahren bei Handballern, weder im Amateurbereich noch in einer Spitzensportumgebung. Dennoch kann anhand der Evidenz aus anderen Kontakt-Mannschaftssportarten eine Empfehlung für einen kombinierten Einsatz von Monitoringverfahren gegeben werden. Dabei sollte stets ein Kosten-Nutzen-Ansatz berücksichtigt werden. Schlussfolgerung Es besteht Forschungsbedarf bezüglich des Einsatzes eines Athletenmonitorings im Hallenhandball. Der in diesem Artikel vorgeschlagene Monitoringansatz kann als Grundlage für Studien in einer Spitzensportumgebung genutzt werden, um in Zukunft ein zunehmend handballspezifischeres Konzept zu implementieren. Background The monitoring of athletes has become a focus in elite-level team sports and research in recent years. The goal is to optimise load management for maximising performance. Due to the considerable amount of data gathered during monitoring in team sports, the trend is towards integrating different monitoring methods in a software-based tool. In addition, decision-support systems are used in order to enable coaches to make quick decisions to control further burdens. This article is intended to give an overview of the large number of monitoring methods used in contact team sports, to consider their test quality criteria and to check a useful application of monitoring methods for team handball, taking into account the sports-specific requirements. Methods PubMed-based review of the literature. Narrative review focusing on current data from the years 2010 to 2019. Results Demands on athletes in elite team handball vary depending on the playing position. Therefore, individualised load control is necessary. Monitoring methods with proven validity and reliability should ideally be used in a multivariate approach to represent the various aspects of external and internal load, recovery and fatigue, well-being and readiness. It is important to know the meaningful change for each athlete while using a monitoring method. This circumstance necessitates an individualised approach for each parameter. There are not many studies on the use of monitoring methods in team handball, neither in the amateur field nor in an elite sports environment. Nevertheless, based on evidence from other contact team sports, a recommendation for a combined use of monitoring methods can be given. Burden, time and cost/benefit should always be considered. Conclusion There is a considerable need for research regarding the use of athlete monitoring in team handball. The combination of monitoring methods proposed in this article can be used as a framework for studies with handball players in an elite sports environment in order to implement an increasingly handball-specific monitoring concept in the future. Publication Date: 21 August 2020 (online) © Georg Thieme Verlag KG Stuttgart · New York

Background: Athlete health is essential for sustained performance in professional sport, with injuries and illnesses limiting both individual and team success. Although athlete monitoring is widely used to support load and recovery management and reduce injury risk, evidence linking training load, well-being and health outcomes in professional basketball is inconsistent. Holistic monitoring approaches may enhance the understanding of load-related health dynamics. Therefore, this study aimed to investigate the associations between internal load, sleep, and physical and mental well-being and the occurrence of injury and illness in professional male basketball players across a competitive season. Methods: In this prospective observational study (German Clinical Trials Register ID: DRKS00032713; registered 19 October 2023), 16 professional male basketball players were monitored over a 31-week competitive season using a software application (Prevention Management Tool, PMT) provided by the German Accident Insurance for professional team sports. Structured injury and illness surveillance was conducted throughout the study period. Internal load was assessed 30 min after each training session and match using the session rating of perceived exertion (sRPE) method. In addition to sleep duration, PMT-integrated athlete self-reported measures collected each morning assessed sleep quality, physical and mental well-being using 11-point Likert scales (0–10). Linear mixed-effects models were used to investigate the associations between internal load, sleep and well-being and the occurrence of injury and illness. Results: A total of 3,454 athlete records were included in the analyses, corresponding to a completion rate of 88.9%. Mean weekly internal load derived from sRPE was 3,873 ± 1,524 arbitrary units. Mean daily sleep duration was 8.16 ± 1.17 h. Mean scores for sleep quality, physical well-being, and mental well-being were 7.59 ± 1.34, 7.78 ± 1.27, and 7.76 ± 1.28, respectively. The cumulative season incidence rates were 1.31 for acute injuries, 0.50 for overuse injuries, and 2.06 for illnesses. Higher internal load and lower sleep quality were associated with reduced physical and mental well-being. Lower physical well-being was significantly associated with illness occurrence ( P < .001, η ²ₚ = 0.03), whereas physical and mental well-being were not associated with injury occurrence. Conclusions: Higher internal load and lower sleep quality were associated with reduced well-being in professional male basketball players. Decreased physical well-being was associated with illness occurrence, supporting its relevance as a potential early indicator within athlete health monitoring frameworks.