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Effect of Blood Lactate Sample Site and Test Protocol on Training Zone Prescription in Rowing

Stephen W. Garland and Greg Atkinson

Purpose:

To assess the effect of sample site (earlobe vs toe) and incremental exercise protocol (continuous vs discontinuous) on training zone prescription in rowing.

Methods:

Twenty-six rowers performed two incremental exercise tests on an ergometer: (1) a five-step discontinuous test with 4-min stages and 30-W increment, with blood samples taken from the earlobe and toe at the start of the 1-min break between steps; (2) a continuous test, with 2-min stages and 30-W increment, with blood samples taken from the right first toe at the end of each stage. Blood was analyzed for lactate concentration.

Results:

At a lactate concentration of 2 mmol·L−1, the mean (95% CI) power output was 8.1 (± 15.4) W greater for the continuous protocol, the random error between the methods (1.96 × SD of differences) was ± 58.8 W, and there was no evidence of any relationship between power output and error between methods. At a lactate concentration of 4 mmol·L−1, the mean (95% CI) power output was 24.2 (± 17.0) W greater for the continuous protocol, and the random error was ± 64.8 W. At 4 mmol·L−1, systematic bias between methods increased with high power outputs.

Conclusions:

The continuous protocol with toe sampling led to higher power outputs for a given lactate concentration compared with the discontinuous protocol with earlobe sampling. This was partly due to the choice of sample site and largely due to the choice of protocol. This bias, and also random variability, makes direct comparison of these tests inappropriate.

Open access

A Comment on “Does Mathematical Coupling Matter to the Acute to Chronic Workload Ratio? A Case Study From Elite Sport”

Lorenzo Lolli, Alan M. Batterham, Gregory MacMillan, Warren Gregson, and Greg Atkinson

Open access

Monitoring Fatigue Status in Elite Team-Sport Athletes: Implications for Practice

Robin T. Thorpe, Greg Atkinson, Barry Drust, and Warren Gregson

The increase in competition demands in elite team sports over recent years has prompted much attention from researchers and practitioners to the monitoring of adaptation and fatigue in athletes. Monitoring fatigue and gaining an understanding of athlete status may also provide insights and beneficial information pertaining to player availability, injury, and illness risk. Traditional methods used to quantify recovery and fatigue in team sports, such as maximal physical-performance assessments, may not be feasible to detect variations in fatigue status throughout competitive periods. Faster, simpler, and nonexhaustive tests such as athlete self-report measures, autonomic nervous system response via heart-rate-derived indices, and to a lesser extent, jump protocols may serve as promising tools to quantify and establish fatigue status in elite team-sport athletes. The robust rationalization and precise detection of a meaningful fluctuation in these measures are of paramount importance for practitioners working alongside athletes and coaches on a daily basis. There are various methods for arriving at a minimal clinically important difference, but these have been rarely adopted by sport scientists and practitioners. The implementation of appropriate, reliable, and sensitive measures of fatigue can provide important information to key stakeholders in team-sport environments. Future research is required to investigate the sensitivity of these tools to fundamental indicators such as performance, injury, and illness.

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The Effect of Active Video Gaming on Children’s Physical Activity, Behavior Preferences and Body Composition

Lee E.F. Graves, Nicola D. Ridgers, Greg Atkinson, and Gareth Stratton

Active video game interventions typically provide children a single game that may become unappealing. A peripheral device (jOG) encourages step-powered gaming on multiple games. This trial evaluated the effect of jOG on children’s objectively measured PA, body fat and self-reported behaviors. 42 of 58 eligible children (8–10 y) randomly assigned to an intervention (jOG) or control (CON) completed the trial. Intervention children received two jOG devices for home use. Analyses of covariance compared the intervention effect at 6 and 12 weeks from baseline. No differences were found between groups for counts per minute (CPM; primary outcome) at 6 and 12 weeks (p > .05). Active video gaming increased (adjusted change 0.95 (95% CI 0.25, 1.65) h·d−1, p<.01) and sedentary video gaming decreased (-0.34 (-1.24, 0.56) h·d−1, p > .05) at 6 weeks relative to CON. No body fat changes were observed between groups. Targeted changes in video game use did not positively affect PA. Larger trials are needed to verify the impact of active video games on children’s PA and health.

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The Percentage of Mature Height as a Morphometric Index of Somatic Growth: A Formal Scrutiny of Conventional Simple Ratio Scaling Assumptions

Lorenzo Lolli, Amanda Johnson, Mauricio Monaco, Valter Di Salvo, Greg Atkinson, and Warren Gregson

Purpose: To assess conventional assumptions that underpin the percentage of mature height index as the simple ratio of screening height (numerator) divided by actual or predicted adult height (denominator). Methods: We examined cross-sectional data from 99 academy youth soccer players (chronological age range, 11.5 to 17.7 y) skeletally immature at the screening time and with adult height measurements available at follow-up. Results: The y-intercept value of −60 cm (95% confidence interval, −115 to −6 cm) from linear regression between screening height and adult height indicated the failure to meet the zero y-intercept assumption. The correlation coefficient between present height and adult height of .64 (95% confidence interval, .50 to .74) was not equal to the ratio of coefficient of variations between these variables (CV x /CV y  = 0.46) suggesting Tanner’s special circumstance was violated. The non-zero correlation between the ratio and the denominator of .21 (95% confidence interval, .01 to .39) indicated that the percentage of mature height was biased low for players with generally shorter adult height, and vice versa. Conclusion: For the first time, we have demonstrated that the percentage of mature height is an inconsistent statistic for determining the extent of completed growth, leading to potentially biased inferences for research and applied purposes.

Open access

The Influence of Changes in Acute Training Load on Daily Sensitivity of Morning-Measured Fatigue Variables in Elite Soccer Players

Robin T. Thorpe, Anthony J. Strudwick, Martin Buchheit, Greg Atkinson, Barry Drust, and Warren Gregson

Purpose:

To determine the sensitivity of a range of potential fatigue measures to daily training load accumulated over the previous 2, 3, and 4 d during a short in-season competitive period in elite senior soccer players (N = 10).

Methods:

Total highspeed-running distance, perceived ratings of wellness (fatigue, muscle soreness, sleep quality), countermovement-jump height (CMJ), submaximal heart rate (HRex), postexercise heart-rate recovery (HRR), and heart-rate variability (HRV: Ln rMSSD) were analyzed during an in-season competitive period (17 d). General linear models were used to evaluate the influence of 2-, 3-, and 4-d total high-speed-running-distance accumulation on fatigue measures.

Results:

Fluctuations in perceived ratings of fatigue were correlated with fluctuations in total high-speed-running-distance accumulation covered on the previous 2 d (r = –.31; small), 3 d (r = –.42; moderate), and 4 d (r = –.28; small) (P < .05). Changes in HRex (r = .28; small; P = .02) were correlated with changes in 4-d total high-speed-running-distance accumulation only. Correlations between variability in muscle soreness, sleep quality, CMJ, HRR%, and HRV and total high-speed-running distance were negligible and not statistically significant for all accumulation training loads.

Conclusions:

Perceived ratings of fatigue and HRex were sensitive to fluctuations in acute total high-speed-running-distance accumulation, although sensitivity was not systematically influenced by the number of previous days over which the training load was accumulated. The present findings indicate that the sensitivity of morning-measured fatigue variables to changes in training load is generally not improved when compared with training loads beyond the previous day’s training.

Open access

A Tool to Explore Discrete-Time Data: The Time Series Response Analyser

Benjamin J. Narang, Greg Atkinson, Javier T. Gonzalez, and James A. Betts

The analysis of time series data is common in nutrition and metabolism research for quantifying the physiological responses to various stimuli. The reduction of many data from a time series into a summary statistic(s) can help quantify and communicate the overall response in a more straightforward way and in line with a specific hypothesis. Nevertheless, many summary statistics have been selected by various researchers, and some approaches are still complex. The time-intensive nature of such calculations can be a burden for especially large data sets and may, therefore, introduce computational errors, which are difficult to recognize and correct. In this short commentary, the authors introduce a newly developed tool that automates many of the processes commonly used by researchers for discrete time series analysis, with particular emphasis on how the tool may be implemented within nutrition and exercise science research.

Restricted access

Tracking Morning Fatigue Status Across In-Season Training Weeks in Elite Soccer Players

Robin T. Thorpe, Anthony J. Strudwick, Martin Buchheit, Greg Atkinson, Barry Drust, and Warren Gregson

Purpose:

To quantify the mean daily changes in training and match load and any parallel changes in indicators of morningmeasured fatigue across in-season training weeks in elite soccer players.

Methods:

After each training session and match (TL), session ratings of perceived exertion (s-RPE) were recorded to calculate overall session load (RPE-TL) in 29 English Premier League players from the same team. Morning ratings of fatigue, sleep quality, and delayed-onset muscle soreness (DOMS), as well as submaximal exercise heart rate (HRex), postexercise heart-rate recovery (HRR%), and heart-rate variability (HRV) were recorded before match day and 1, 2, and 4 d postmatch. Data were collected for a median duration of 3 wk (range 1–13) and reduced to a typical weekly cycle including no midweek match and a weekend match day. Data were analyzed using withinsubject linear mixed models.

Results:

RPE-TL was approximately 600 arbitrary units (AU) (95% confidence interval 546–644) higher on match day than following day (P < .001). RPE-TL progressively decreased by »60 AU per day over the 3 days before a match (P < .05). Morning-measured fatigue, sleep quality, and DOMS tracked the changes in RPE-TL, being 35–40% worse on postmatch day vs prematch day (P < .001). Perceived fatigue, sleep quality, and DOMS improved by 17–26% from postmatch day to 3 d postmatch, with further smaller (7%–14%) improvements occurring between 4 d postmatch and prematch day (P < .01). There were no substantial or statistically significant changes in HRex, HRR%, or HRV over the weekly cycle (P > .05).

Conclusions:

Morning-measured ratings of fatigue, sleep quality, and DOMS are clearly more sensitive than HR-derived indices to the daily fluctuations in session load experienced by elite soccer players in a standard in-season week.

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Monitoring Fatigue During the In-Season Competitive Phase in Elite Soccer Players

Robin T. Thorpe, Anthony J. Strudwick, Martin Buchheit, Greg Atkinson, Barry Drust, and Warren Gregson

Purpose:

To quantify the relationship between daily training load and a range of potential measures of fatigue in elite soccer players during an in-season competitive phase (17 d).

Methods:

Total high-intensity-running (THIR) distance, perceived ratings of wellness (fatigue, muscle soreness, sleep quality), countermovement-jump height (CMJ), postexercise heart-rate recovery (HRR), and heart-rate variability (Ln rMSSD) were analyzed during an in-season competitive period (17 d). General linear models were used to evaluate the influence of daily fluctuation in THIR distance on potential fatigue variables.

Results:

Fluctuations in fatigue (r = −.51, large, P < .001), Ln rMSSD (r = −.24, small, P = .04), and CMJ (r = .23, small, P = .04) were significantly correlated with fluctuations in THIR distance. Correlations between variability in muscle soreness, sleep quality, and HRR and THIR distance were negligible and not statistically significant.

Conclusions:

Perceived ratings of fatigue and Ln rMSSD were sensitive to daily fluctuations in THIR distance in a sample of elite soccer players. Therefore, these particular markers show promise as simple, noninvasive assessments of fatigue status in elite soccer players during a short in-season competitive phase.

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Factors Influencing Perception of Effort (Session Rating of Perceived Exertion) During Elite Soccer Training

Paolo Gaudino, F. Marcello Iaia, Anthony J. Strudwick, Richard D. Hawkins, Giampietro Alberti, Greg Atkinson, and Warren Gregson

Purpose:

The aim of the current study was to identify the external-training-load markers that are most influential on session rating of perceived exertion (RPE) of training load (RPE-TL) during elite soccer training.

Methods:

Twenty-two elite players competing in the English Premier League were monitored. Training-load data (RPE and 10-Hz GPS integrated with a 100-Hz accelerometer) were collected during 1892 individual training sessions over an entire in-season competitive period. Expert knowledge and a collinearity r < .5 were used initially to select the external training variables for the final analysis. A multivariateadjusted within-subjects model was employed to quantify the correlations of RPE and RPE-TL (RPE × duration) with various measures of external training intensity and training load.

Results:

Total high-speed-running (HSR; >14.4 km/h) distance and number of impacts and accelerations >3 m/s2 remained in the final multivariate model (P < .001). The adjusted correlations with RPE were r = .14, r = .09, and r = .25 for HSR, impacts, and accelerations, respectively. For RPE-TL, the correlations were r = .11, r = .45, and r = .37, respectively.

Conclusions:

The external-load measures that were found to be moderately predictive of RPE-TL in soccer training were HSR distance and the number of impacts and accelerations. These findings provide new evidence to support the use of RPE-TL as a global measure of training load in elite soccer. Furthermore, understanding the influence of characteristics affecting RPE-TL may help coaches and practitioners enhance training prescription and athlete monitoring.