Document Type

Journal Article

Publication Title

International Journal of Sports Physiology and Performance

Volume

16

First Page

342

Last Page

352

Publisher

Human Kinetics

School

School of Medical and Health Sciences / Graduate Research School

RAS ID

32948

Comments

Accepted author manuscript version reprinted, by permission, from International Journal of Sports Physiology and Performance, 2021, 16(3): 342-352, https://doi.org/10.1123/ijspp.2020-0002. © Human Kinetics, Inc.

Coyne, J. O. C., Newton, R. U., & Haff, G. G. (2021). Relationships between internal training load in a taper with elite weightlifting performance calculated using different moving average methods. International Journal of Sports Physiology and Performance, 16(3), 342-352.

https://doi.org/10.1123/IJSPP.2020-0002

Abstract

Purpose:

A simple and 2 different exponentially weighted moving average methods were used to investigate the relationships between internal training load and elite weightlifting performance.

Methods:

Training impulse data (sessional ratings of perceived exertion × training duration) were collected from 21 elite weightlifters (age = 26.0 [3.2] y, height = 162.2 [11.3] cm, body mass = 72.2 [23.8] kg, previous 12-mo personal best total 96.3% [2.7%] of world record total) during the 8 weeks prior to the 2016 Olympic Games qualifying competition. The amount of training modified or cancelled due to injury/illness was also collected. The training stress balance (TSB) and acute to chronic workload ratio (ACWR) were calculated with the 3 moving average methods. Along with the amount of modified training, TSB and ACWR across the moving average methods were then examined for their relationship to competitive performance.

Results:

There were no consistent associations between performance and training load on the day of competition. The volatility (SD) of the ACWR in the last 21 days preceding the competition was moderately correlated with performance across moving average methods (r = -.41 to .48, P = .03-.07). TSB and ACWR volatility in the last 21 days were also significantly lower for successful performers but only as a simple moving average (P = .03 and .03, g = 1.15 and 1.07, respectively).

Conclusions:

Practitioners should consider restricting change and volatility in an athlete's TSB or ACWR in the last 21 days prior to a major competition. In addition, a simple moving average seemed to better explain elite weightlifting performance than the exponentially weighted moving averages in this investigation.

DOI

10.1123/IJSPP.2020-0002

Research Themes

Society and Culture

Priority Areas

Human movement and performance

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