appropriate workload monitoring strategies seems fundamental to prescribe adequate training stimuli. 4 – 6 In the last few years, an increasing number of studies quantified training loads (TLs) and game loads (GLs) in female basketball players, 4 – 6 whereas to the best of our knowledge, only one study has
Search Results
Monitoring Workload in Elite Female Basketball Players During the In-Season Phase: Weekly Fluctuations and Effect of Playing Time
Henrikas Paulauskas, Rasa Kreivyte, Aaron T. Scanlan, Alexandre Moreira, Laimonas Siupsinskas, and Daniele Conte
The Relationship Between Subjective Wellness and External Training Load in Elite English Premier League Goalkeepers and a Comparison With Outfield Soccer Players
Sophie Grimson, Gary Brickley, Nicholas J. Smeeton, Adam Brett, and Will Abbott
, consequently indicating the importance of training load (TL) monitoring in GKs. 11 When compared with outfield positions, GKs report higher subjective perceptions of TL. 12 Noteworthy, GKs undertake more power and high-intensity-based activities which could psychologically influence rating of perceived
Validity of Session Rating of Perceived Exertion Assessed via the CR100 Scale to Track Internal Load in Elite Youth Football Players
Sharna A. Naidu, Maurizio Fanchini, Adam Cox, Joshua Smeaton, Will G. Hopkins, and Fabio R. Serpiello
Ratings of perceived exertion (RPE) have been proposed as a simple, noninvasive method to assess exercise intensity. 1 When multiplied by exercise duration, RPE can be used to assess internal training load (TL), this being named session-RPE (sRPE). 2 Traditionally, sRPE has been obtained by using
Training Characteristics of Male and Female Professional Road Cyclists: A 4-Year Retrospective Analysis
Teun van Erp, Dajo Sanders, and Jos J. de Koning
adjusted accordingly every season. Furthermore, according to previous research, 2 , 3 the percentage of time spent at different POs was calculated over 11 power bands with steps of 0.75 W·kg −1 , ranging from <0.75 to >7.50 W·kg −1 . To investigate the differences in male and female training load, 4
Quantifying Training Load: A Comparison of Subjective and Objective Methods
Jill Borresen and Michael I. Lambert
Purpose:
To establish the relationship between a subjective (session rating of perceived exertion [RPE]) and 2 objective (training impulse [TRIMP]) and summated-heart-rate-zone (SHRZ) methods of quantifying training load and explain characteristics of the variance not accounted for in these relationships.
Methods:
Thirty-three participants trained ad libitum for 2 wk, and their heart rate (HR) and RPE were recorded to calculate training load. Subjects were divided into groups based on whether the regression equations over- (OVER), under- (UNDER), or accurately predicted (ACCURATE) the relationship between objective and subjective methods.
Results:
A correlation of r = .76 (95% CI: .56 to .88) occurred between TRIMP and session-RPE training load. OVER spent a greater percentage of training time in zone 4 of SHRZ (ie, 80% to 90% HRmax) than UNDER (46% ± 8% vs 25% ± 10% [mean ± SD], P = .008). UNDER spent a greater percentage of training time in zone 1 of SHRZ (ie, 50% to 60% HRmax) than OVER (15% ± 8% vs 3% ± 3%, P = .005) and ACCURATE (5% ± 3%, P = .020) and more time in zone 2 of SHRZ (ie, 60% to 70%HRmax) than OVER (17% ± 6% vs 7% ± 6%, P = .039). A correlation of r = .84 (.70 to .92) occurred between SHRZ and session-RPE training load. OVER spent proportionally more time in Zone 4 than UNDER (45% ± 8% vs 25% ± 10%, P = .018). UNDER had a lower training HR than ACCURATE (132 ± 10 vs 148 ± 12 beats/min, P = .048) and spent more time in zone 1 than OVER (15% ± 8% vs 4% ± 3%, P = .013) and ACCURATE (5% ± 3%, P = .015).
Conclusions:
The session-RPE method provides reasonably accurate assessments of training load compared with HR-based methods, but they deviate in accuracy when proportionally more time is spent training at low or high intensity.
Training-Load-Guided vs Standardized Endurance Training in Recreational Runners
Moritz Schumann, Javier Botella, Laura Karavirta, and Keijo Häkkinen
Purpose:
To compare the effects of a standardized endurance-training program with individualized endurance training modified based on the cumulative training load provided by the Polar training-load feature.
Methods:
After 12 wk of similar training, 24 recreationally endurance-trained men were matched to a training-load-guided (TL, n = 10) or standardized (ST, n = 14) group and continued training for 12 wk. In TL, training sessions were individually chosen daily based on an estimated cumulative training load, whereas in ST the training was standardized with 4–6 sessions/wk. Endurance performance (shortest 1000-m running time during an incremental field test of 6 × 1000 m) and heart-rate variability (HRV) were measured every 4 wk, and maximal oxygen consumption (VO2max) was measured during an incremental treadmill test every 12 wk.
Results:
During weeks 1–12, similar changes in VO2max and 1000-m time were observed in TL (+7% ± 4%, P = .004 and –6% ± 4%, P = .069) and ST (+5% ± 7%, P = .019 and –8% ± 5%, P < .001). During wk 13–24, VO2max statistically increased in ST only (3% ± 4%, P = .034). The 1000-m time decreased in TL during wk 13–24 (–9% ± 5%, P = .011), but in ST only during wk 13–20 (–3% ± 2%, P = .003). The overall changes in VO2max and 1000-m time during wk 0–24 were similar in TL (+7% ± 4%, P = .001 and –9% ± 5%, P = .011) and ST (+10% ± 7%, P < .001 and –13% ± 5%, P < .001). No between-groups differences in total training volume and frequency were observed. HRV remained statistically unaltered in both groups.
Conclusions:
The main finding was that training performed according to the cumulative training load led to improvements in endurance performance similar to those with standardized endurance training in recreational endurance runners.
Successful Return to Performance After COVID-19 Infection in an Elite Athlete
Cyril Besson, Kenny Guex, Laurent Schmitt, Boris Gojanovic, and Vincent Gremeaux
Elite athletes must find an adequate balance between training load (TL), competitions, recovery phases, and everyday demands to perform. Fatigue may be related to infections, and COVID-19 may have severe medical consequences for an athlete (eg, myocarditis); hence, the necessity for sports
Testosterone and Dihydrotestosterone Changes in Male and Female Athletes Relative to Training Status
Christian J. Cook, Blair T. Crewther, Liam P. Kilduff, Linda L. Agnew, Phillip Fourie, and Benjamin G. Serpell
(1E), ST (1G), and SDHT (1I) concentration for males was significantly higher than for females (all large ES differences). Also, we identified significantly higher concentrations for the TT, DHT, ST, and SDHT measures with heavy training load status compared with light training load status (all small
Modeling the Prediction of the Session Rating of Perceived Exertion in Soccer: Unraveling the Puzzle of Predictive Indicators
Youri Geurkink, Gilles Vandewiele, Maarten Lievens, Filip de Turck, Femke Ongenae, Stijn P.J. Matthys, Jan Boone, and Jan G. Bourgois
content of a training session is usually prescribed by the coach and can be defined as the external training load. The total external training load comprises all of the players’ actions during a training session 2 and is generally quantified using tracking technology. 3 The external training load
Injury Prediction in Competitive Runners With Machine Learning
S. Sofie Lövdal, Ruud J.R. Den Hartigh, and George Azzopardi
Staying healthy and injury free is one of the most important factors for optimal performance in sports. 1 , 2 Therefore, for decades, researchers and practitioners across different sports have collected data on training loads of athletes and the occurrence of injuries. 3 – 7 Recent years have
