Does exercise intensity affect wellness scores in a dose-like fashion?

Simulated Soccer Game Protocols: A Systematic Review on Validated Protocols That Represent the Demands of the Game

ABSTRACT

Brito, P, Costa, J, Figueiredo, P, and Brito, J. Simulated soccer game protocols: A systematic review on validated protocols that represent the demands of the game. J Strength Cond Res 38(1): 192-205, 2024-Several laboratory and field testing protocols have been developed attempting to simulate the activity pattern and physiological demands of soccer. In the present systematic review, we aimed to analyze and discuss the appropriateness, strengths, and limitations of soccer-specific simulated tests. A systematic review of the literature was conducted based on the PRISMA guidelines. Studies conducted in soccer, simulated soccer match tests, and validated simulation protocols performed on-the-field or on a treadmill were considered. No sex restriction was applied, and age >18 years (i.e., adults) was considered. At least 1 outcome measure (e.g., neuromuscular performance, external load, internal load, or psychometric state) of post-simulated-match test or protocol had to be reported. Within the 14 studies included, the average methodological quality of the included articles was 0.61 ± 0.09 (mean ± SD) of 1. Overall, 9 validated protocols were identified. In the protocols, only amateur, university, or semiprofessional soccer players were analyzed. Only one study evaluated female soccer players. None of the studies evaluated the effect on performance over the 2-3 days after the protocol. Accelerations and decelerations, and changes in direction typically present in a game have not been clearly described in any protocol. Future research should address this issue and validate soccer-specific protocols in women.

Relationship Between Athlete-Reported Outcome Measures and Subsequent Match Performance in Team Sports: A Systematic Review

ABSTRACT

Sansone, P, Rago, V, Kellmann, M, and Alcaraz, PE. Relationship between athlete-reported outcome measures and subsequent match performance in team sports: A systematic review. J Strength Cond Res 37(11): 2302-2313, 2023-Athlete-reported outcome measures (AROMs; e.g., fatigue, stress, readiness, recovery, and sleep quality) are commonly implemented in team sports to monitor the athlete status. However, the relationship between AROMs and match performance indicators is unclear and warrants further investigation. This systematic review examined the relationship between precompetitive AROMs and subsequent match performances of team sport athletes. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, 3 (PubMed, Scopus, and Web of Science) databases were systematically searched to retrieve studies investigating the effects or association of AROMs and match: (a) technical-tactical performance (match-related statistics), (b) physical performance, (c) physiological and (d) perceptual demands, and (e) other measures of performance in adult team sport athletes. Quality assessment of included studies was performed using a modified Black and Downs checklist. Fifteen articles representing 289 team sport athletes were included. Mean quality of included studies was 7.6 ± 1.0 (of 11). Across the included studies, 22 AROMs parameters were used, and 16 different statistical approaches were identified. Approximately 11 of 15 studies used nonvalidated AROMs. Overall, associations or effects of AROMs were found consistently for match-related statistics (7/9 studies), whereas results were unclear for physical performances (3/7 studies), perceptual demands (1/2 studies), or other measures of performance (2/4 studies). Considering the importance of key match-related statistics for success in team sports, this review suggests that monitoring precompetitive AROMs has potential to provide valuable information to coaches. However, it is indispensable to validate AROMs questionnaires and to uniform data collection and statistical procedures before substantiated indications to practitioners can be made.

Monitorización y periodización del rendimiento desde la fisioterapia deportiva ¿Hacia dónde vamos?

RESUMEN Introducción El concepto de monitorización y periodización es un visión que se ha desarrollado en la última década, donde se busca que se pueda tener un control de la carga interna y externa en los deportistas de distintas disciplinas deportivas producidas por el proceso de interacción con variables de prescripción de ejercicio que causan modificaciones a nivel fisiológico, bioquímico, biomecanico, muscular, neuromuscular  ocasionando la tensión en los subsistemas del movimiento corporal humano generando adaptaciones especificas ante una carga determinada la cual puede ser medida mediante el uso de tecnología especifica o test indirectos Metodología Revisión de la literatura con la combinación de palabras clave como Monitoring, Performance, sports training load, Periodization en bases de datos como Pubmed, Ebsco, Medline, Scopus, Science Direct Resultados se pudo identificar 65 artículos que referencian la existencia  de herramientas tecnológicas para realizar un proceso de monitorización y periodización desde la rehabilitación , prevención, control de carga, recuperación y readaptación deportiva que permiten la generación de datos estadísticos y crear perfiles desde cada área de actuación del fisioterapeuta deportivo. Conclusión la fisioterapia es una profesión encargada de muchos procesos deportivos que deben ser monitorizados y generen datos que permitan estandarizar procesos, crear perfiles de seguimiento específicos para facilitar la toma de decisiones desde el equipo biomédico e investigaciones en el deporte de alto rendimiento fusionando la practica con la evidencia científica.

Training Load Monitoring Considerations for Female Gaelic Team Sports: From Theory to Practice

Athlete monitoring enables sports science practitioners to collect information to determine how athletes respond to training loads (TL) and the demands of competition. To date, recommendations for females are often adapted from their male counterparts. There is currently limited information available on TL monitoring in female Gaelic team sports in Ireland. The collection and analysis of female athlete monitoring data can provide valuable information to support the development of female team sports. Athletic monitoring can also support practitioners to help minimize risk of excessive TL and optimize potential athletic performance. The aims of this narrative review are to provide: (i) an overview of TL athlete monitoring in female team sports, (ii) a discussion of the potential metrics and tools used to monitor external TL and internal TL, (iii) the advantages and disadvantages of TL modalities for use in Gaelic team sports, and (iv) practical considerations on how to monitor TL to aid in the determination of meaningful change with female Gaelic team sports athletes.

Analysing the predictive capacity and dose-response of wellness in load monitoring

This study aimed to identify the predictive capacity of wellness questionnaires on measures of training load using machine learning methods. The distributions of, and dose-response between, wellness and other load measures were also examined, offering insights into response patterns. Data (n= 14,109) were collated from an athlete management systems platform (Catapult Sports, Melbourne, Australia) and were split across three sports (cricket, rugby league and football) with data analysis conducted in R (Version 3.4.3). Wellness (sleep quality, readiness to train, general muscular soreness, fatigue, stress, mood, recovery rating and motivation) as the dependent variable, and sRPE, sRPE-TL and markers of external load (total distance and m.min^-1) as independent variables were included for analysis. Classification and regression tree models showed high cross-validated error rates across all sports (i.e., > 0.89) and low model accuracy (i.e., < 5% of variance explained by each model) with similar results demonstrated using random forest models. These results suggest wellness items have limited predictive capacity in relation to internal and external load measures. This result was consistent despite varying statistical approaches (regression, classification and random forest models) and transformation of wellness scores. These findings indicate practitioners should exercise caution when interpreting and applying wellness responses.