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  • Author: Simon P.T. Kemp x
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Matthew J. Cross, Sean Williams, Grant Trewartha, Simon P.T. Kemp and Keith A. Stokes

Purpose:

To explore the association between in-season training-load (TL) measures and injury risk in professional rugby union players.

Methods:

This was a 1-season prospective cohort study of 173 professional rugby union players from 4 English Premiership teams. TL (duration × session-RPE) and time-loss injuries were recorded for all players for all pitch- and gym-based sessions. Generalized estimating equations were used to model the association between in-season TL measures and injury in the subsequent week.

Results:

Injury risk increased linearly with 1-wk loads and week-to-week changes in loads, with a 2-SD increase in these variables (1245 AU and 1069 AU, respectively) associated with odds ratios of 1.68 (95% CI 1.05–2.68) and 1.58 (95% CI 0.98–2.54). When compared with the reference group (<3684 AU), a significant nonlinear effect was evident for 4-wk cumulative loads, with a likely beneficial reduction in injury risk associated with intermediate loads of 5932–8651 AU (OR 0.55, 95% CI 0.22–1.38) (this range equates to around 4 wk of average in-season TL) and a likely harmful effect evident for higher loads of >8651 AU (OR 1.39, 95% CI 0.98–1.98).

Conclusions:

Players had an increased risk of injury if they had high 1-wk cumulative loads (1245 AU) or large week-to-week changes in TL (1069 AU). In addition, a U-shaped relationship was observed for 4-wk cumulative loads, with an apparent increase in risk associated with higher loads (>8651 AU). These measures should therefore be monitored to inform injury-risk-reduction strategies.

Open access

Sean Williams, Grant Trewartha, Matthew J. Cross, Simon P.T. Kemp and Keith A. Stokes

Purpose:

Numerous derivative measures can be calculated from the simple session rating of perceived exertion (sRPE), a tool for monitoring training loads (eg, acute:chronic workload and cumulative loads). The challenge from a practitioner’s perspective is to decide which measures to calculate and monitor in athletes for injury-prevention purposes. The aim of the current study was to outline a systematic process of data reduction and variable selection for such training-load measures.

Methods:

Training loads were collected from 173 professional rugby union players during the 2013–14 English Premiership season, using the sRPE method, with injuries reported via an established surveillance system. Ten derivative measures of sRPE training load were identified from existing literature and subjected to principal-component analysis. A representative measure from each component was selected by identifying the variable that explained the largest amount of variance in injury risk from univariate generalized linear mixed-effects models.

Results:

Three principal components were extracted, explaining 57%, 24%, and 9% of the variance. The training-load measures that were highly loaded on component 1 represented measures of the cumulative load placed on players, component 2 was associated with measures of changes in load, and component 3 represented a measure of acute load. Four-week cumulative load, acute:chronic workload, and daily training load were selected as the representative measures for each component.

Conclusions:

The process outlined in the current study enables practitioners to monitor the most parsimonious set of variables while still retaining the variation and distinct aspects of “load” in the data.