et al, 10 in comparison with rest days. However, HR was increased during the first 3 sleeping hours compared with the control situation. It was speculated that the training loads experienced by the team were not high enough to substantially disturb the cardiac autonomic function during sleep hours
Search Results
Does Night Training Load Affect Sleep Patterns and Nocturnal Cardiac Autonomic Activity in High-Level Female Soccer Players?
Júlio A. Costa, João Brito, Fábio Y. Nakamura, Eduardo M. Oliveira, Ovidio P. Costa, and António N. Rebelo
The Effect of Training Loads on Performance Measures and Injury Characteristics in Rugby League Players: A Systematic Review
Mark Booth, Stephen Cobley, and Rhonda Orr
Elite athlete development necessitates years of structured, progressive, and intense training, 1 incorporating a multidisciplinary approach including skill acquisition, strength and conditioning, and psychological development. In particular, high physical training loads (TLs) over extended time
The Fitness–Fatigue Model: What’s in the Numbers?
Kobe Vermeire, Michael Ghijs, Jan G. Bourgois, and Jan Boone
Quantification of the relationship between training load (TL) and changes in performance can be considered the Holy Grail in sport science, as this would allow coaches to select the most adequate training stimulus to maximize performance of an athlete at a given moment in time. Therefore, already
Monitoring Training Loads: The Past, the Present, and the Future
Carl Foster, Jose A. Rodriguez-Marroyo, and Jos J. de Koning
Training monitoring is about keeping track of what athletes accomplish in training, for the purpose of improving the interaction between coach and athlete. Over history there have been several basic schemes of training monitoring. In the earliest days training monitoring was about observing the athlete during standard workouts. However, difficulty in standardizing the conditions of training made this process unreliable. With the advent of interval training, monitoring became more systematic. However, imprecision in the measurement of heart rate (HR) evolved interval training toward index workouts, where the main monitored parameter was average time required to complete index workouts. These measures of training load focused on the external training load, what the athlete could actually do. With the advent of interest from the scientific community, the development of the concept of metabolic thresholds and the possibility of trackside measurement of HR, lactate, VO2, and power output, there was greater interest in the internal training load, allowing better titration of training loads in athletes of differing ability. These methods show much promise but often require laboratory testing for calibration and tend to produce too much information, in too slow a time frame, to be optimally useful to coaches. The advent of the TRIMP concept by Banister suggested a strategy to combine intensity and duration elements of training into a single index concept, training load. Although the original TRIMP concept was mathematically complex, the development of the session RPE and similar low-tech methods has demonstrated a way to evaluate training load, along with derived variables, in a simple, responsive way. Recently, there has been interest in using wearable sensors to provide high-resolution data of the external training load. These methods are promising, but problems relative to information overload and turnaround time to coaches remain to be solved.
Accumulative Weekly External and Internal Load Relative to Match Load in Elite Male Youth Soccer Players
Vicente de Dios-Álvarez, Pello Alkain, Julen Castellano, and Ezequiel Rey
Quantification and monitoring of both training and match load could help coaches and strength and conditioning specialists to periodize the training process in soccer much better, aiming to increase team performance ( 22 ) and reduce the risk of injury ( 11 ). Generally, training load can be
The Influence of Exercise Intensity on the Association Between Kilojoules Spent and Various Training Loads in Professional Cycling
Teun van Erp, Marco Hoozemans, Carl Foster, and Jos J. de Koning
Competitive road cycling is one of the sports with the highest volume in training load (TL); therefore, professional cyclists experience high physiological demands. It is important to have a valid measure of those physiological demands to optimize training outcomes and to prevent overtraining
Data Reduction Approaches to Athlete Monitoring in Professional Australian Football
Samuel Ryan, Thomas Kempton, and Aaron J. Coutts
excessive physical impairment, mental fatigue, or psychological distress. 1 Player readiness can be informed by objective and subjective information including external training load measures, 2 , 3 internal load measures, 4 exposure to maximum speed, 5 and perceptual wellness assessments. 6 These data
The Road to Rio: A Brief Report of Training-Load Distribution of Open-Water Swimmers During the Olympic Season
Roberto Baldassarre, Marco Bonifazi, Romain Meeusen, and Maria Francesca Piacentini
1975 Declaration of Helsinki. Table 1 Anthropometric Characteristics and Training-Load Distribution Athlete Training Race results sRPE, % EC OG Gender Age, y Height, m Weight, kg Sessions, n Total volume, km Total time, h Zone 1 Zone 2 Zone 3 5 km 10 km 25 km 10 km 1 F 24 1.74 60.0 425 3593.30 854 85
Monitoring Rating of Perceived Exertion Time in Zone: A Novel Method to Quantify Training Load in Elite Open-Water Swimmers?
Cristian Ieno, Roberto Baldassarre, Maddalena Pennacchi, Antonio La Torre, Marco Bonifazi, and Maria Francesca Piacentini
The main finding was an inconsistency between external and internal training load measures and between HR-based and RPE-based data methods. In fact, we found differences in the categorical approaches (SG and sRPE) and in the TIZ methods (SG/TIZ and RPE/TIZ). The TIZ and external load show similar TID
Quantifying Training Demands of a 2-Week In-Season Squash Microcycle
Carl James, Aishwar Dhawan, Timothy Jones, and Olivier Girard
-analytical findings demonstrate that the relationships between training load metrics are influenced by session type within team sports. 20 Therefore, it is unclear if RPE, derived from either a player or a coach, is a suitable proxy for accurate internal load measurement across different training sessions in squash
