Normative data and percentile curves for long-term athlete development in swimming

It is now common practice to express child growth status in the form of SD scores. The LMS method provides a way of obtaining normalized growth centile standards which simplifies this assessment, and which deals quite generally with skewness which may be present in the distribution of the measurement (eg height, weight, circumferences or skinfolds). It assumes that the data can be normalized by using a power transformation, which stretches one tail of the distribution and shrinks the other, removing the skewness. The optimal power to obtain normality is calculated for each of a series of age groups and the trend summarized by a smooth (L) curve. Trends in the mean (M) and coefficient of variation (S) are similarly smoothed. The resulting L, M and S curves contain the information to draw any centile curve, and to convert measurements (even extreme values) into exact SD scores. A table giving approximate standard errors for the smoothed centiles is provided. The method, which is illustrated with US girls' weight data, should prove useful both for the construction and application of growth standards.

Refence centile curves show the distribution of a measurement as it changes according to some covariate, often age. The LMS method summarizes the changing distribution by three curves representing the median, coefficient of variation and skewness, the latter expressed as a Box-Cox power. Using penalized likelihood the three curves can be fitted as cubic splines by non-linear regression, and the extent of smoothing required can be expressed in terms of smoothing parameters or equivalent degrees of freedom. The method is illustrated with data on triceps skinfold in Gambian girls and women, and body weight in U.S.A. girls.

The search for talent is pervasive in youth sports. Selection/exclusion in many sports follows a maturity-related gradient largely during the interval of puberty and growth spurt. As such, there is emphasis on methods for assessing maturation. Commonly used methods for assessing status (skeletal age, secondary sex characteristics) and estimating timing (ages at peak height velocity (PHV) and menarche) in youth athletes and two relatively recent anthropometric (non-invasive) methods (status-percentage of predicted near adult height attained at observation, timing-predicted maturity offset/age at PHV) are described and evaluated. The latter methods need further validation with athletes. Currently available data on the maturity status and timing of youth athletes are subsequently summarised. Selection for sport and potential maturity-related correlates are then discussed in the context of talent development and associated models. Talent development from novice to elite is superimposed on a constantly changing base-the processes of physical growth, biological maturation and behavioural development, which occur simultaneously and interact with each other. The processes which are highly individualised also interact with the demands of a sport per se and with involved adults (coaches, trainers, administrators, parents/guardians).