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Measures of Rowing Performance

Sports Medicine volume 42, pages 343–358 (2012)Cite this article

Abstract

Accurate measures of performance are important for assessing competitive athletes in practical and research settings. We present here a review of rowing performance measures, focusing on the errors in these measures and the implications for testing rowers. The yardstick for assessing error in a performance measure is the random variation (typical or standard error of measurement) in an elite athlete’s competitive performance from race to race: ~1.0%for time in 2000m rowing events. There has been little research interest in on-water time trials for assessing rowing performance, owing to logistic difficulties and environmental perturbations in performance time with such tests. Mobile ergometry via instrumented oars or rowlocks should reduce these problems, but the associated errors have not yet been reported. Mea- surement of boat speed tomonitor on-water training performance is common; one device based on global positioning system (GPS) technology contributes negligible extra randomerror (0.2%) in speedmeasured over 2000m, but extra error is substantial (1‐10%) with other GPS devices or with an impeller, especially over shorter distances. The problems with on-water testing have led to widespread use of the Concept II rowing ergometer. The standard error of the estimate of on-water 2000m time predicted by 2000m ergometer perfor- mance was 2.6% and 7.2% in two studies, reflecting different effects of skill, body mass and environment in on-water versus ergometer performance. However, well trained rowers have a typical error in performance time of only ~0.5% between repeated 2000m time trials on this ergometer, so such trials are suitable for tracking changes in physiological performance and factors affecting it. Many researchers have used the 2000m ergometer performance time as a criterion to identify other predictors of rowing performance. Standard errors of the estimate vary widely between studies even for the same predictor, but the lowest errors (~1‐2%) have been observed for peak power output in an incremental test, some measures of lactate threshold and mea- sures of 30-second all-out power. Some of these measures also have typical error between repeated tests suitably low for tracking changes. Combining measures via multiple linear regression needs further investigation. In sum- mary, measurement of boat speed, especially with a good GPS device, has adequate precision for monitoring training performance, but adjustment for environmental effects needs to be investigated. Time trials on the Concept II ergometer provide accurate estimates of a rower’s physiological ability to output power, and some submaximal and brief maximal ergometer performance measures can be used frequently to monitor changes in this ability. On water performancemeasured via instrumented skiffs that determine individual power output may eventually surpass measures derived from the Concept II.

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Table I
Table II
Table III

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Acknowledgements

No sources of funding were used to assist in the preparation of this review. The authors have no conflicts of interest that are directly relevant to the content of this review.

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Authors and Affiliations

  1. Department of Sport & Leisure Studies, University of Waikato, Private Bag, 3105, Hamilton, New Zealand

    T. Brett Smith

  2. Sport Performance Research Institute NZ, AUT University, Auckland, New Zealand

    Will G. Hopkins

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Correspondence to T. Brett Smith.

Appendix

Appendix

Calculation of the standard error of the estimate.[56]

If X and Y are the practical and criterion in the validity study, r is their correlation, eX and eY are their random errors, n is the sample size, SD is standard deviation, and SEE is the standard error of the estimate, then:

$$\rm e_X = \sqrt{[SD_{X}{^2} (1-r^2 \ SD{_Y}{^2} / (SD{_Y}{^2}-e{_Y}{^2}))];}$$
$$\rm observed \ slope \ of \ regression \ line = r(SD_Y\ / \ SD_X);$$
$$\rm observed \ SEE = SD_Y\sqrt{[(1-r^2)(n-1)/(n-2)];}$$
$$\rm true \ slope = (observed \ slope)/(1-e{_X}{^2}/SD{_X}{^2});$$
$$\rm true \ SEE \ without \ criterion \ error = (true \ slope) \ e_X;$$
$$\rm true \ SEE \ with \ criterion \ error = \sqrt{[(true \ SEE)^2+e{_Y}{^2}].}$$

The adjusted SEE shown in the tables is the true SEE with criterion error. The random error in the criterion, eY, was assumed to be 1% for 2000 m single-scull performance time (see table I) and 0.5% for 2000 m Concept II performance time (see table III).

This approach cannot be used for measures derived by multiple linear regression unless the authors provide the mean and standard deviation of the predicted values.

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Smith, T.B., Hopkins, W.G. Measures of Rowing Performance. Sports Med 42, 343–358 (2012). https://doi.org/10.2165/11597230-000000000-00000

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Keywords

  • Global Position System
  • Time Trial
  • Lactate Threshold
  • Race Time
  • Global Position System Device