Minimal measurement error (reliability) during the collection of interval- and ratio-type data is critically important to sports medicine research. The main components of measurement error are systematic bias (e.g. general learning or fatigue effects on the tests) and random error due to biological or mechanical variation. Both error components should be meaningfully quantified for the sports physician to relate the described error to judgements regarding 'analytical goals' (the requirements of the measurement tool for effective practical use) rather than the statistical significance of any reliability indicators. Methods based on correlation coefficients and regression provide an indication of 'relative reliability'. Since these methods are highly influenced by the range of measured values, researchers should be cautious in: (i) concluding acceptable relative reliability even if a correlation is above 0.9; (ii) extrapolating the results of a test-retest correlation to a new sample of individuals involved in an experiment; and (iii) comparing test-retest correlations between different reliability studies. Methods used to describe 'absolute reliability' include the standard error of measurements (SEM), coefficient of variation (CV) and limits of agreement (LOA). These statistics are more appropriate for comparing reliability between different measurement tools in different studies. They can be used in multiple retest studies from ANOVA procedures, help predict the magnitude of a 'real' change in individual athletes and be employed to estimate statistical power for a repeated-measures experiment. These methods vary considerably in the way they are calculated and their use also assumes the presence (CV) or absence (SEM) of heteroscedasticity. Most methods of calculating SEM and CV represent approximately 68% of the error that is actually present in the repeated measurements for the 'average' individual in the sample. LOA represent the test-retest differences for 95% of a population. The associated Bland-Altman plot shows the measurement error schematically and helps to identify the presence of heteroscedasticity. If there is evidence of heteroscedasticity or non-normality, one should logarithmically transform the data and quote the bias and random error as ratios. This allows simple comparisons of reliability across different measurement tools. It is recommended that sports clinicians and researchers should cite and interpret a number of statistical methods for assessing reliability. We encourage the inclusion of the LOA method, especially the exploration of heteroscedasticity that is inherent in this analysis. We also stress the importance of relating the results of any reliability statistic to 'analytical goals' in sports medicine.

The requirements for soccer play are multifactorial and distinguishing characteristics of elite players can be investigated using multivariate analysis. The aim of the present study was to apply a comprehensive test battery to young players with a view to distinguishing between elite and sub-elite groups on the basis of performance on test items. Thirty-one (16 elite, 15 sub-elite) young players matched for chronological age (15-16 years) and body size were studied. Test items included anthropometric (n = 15), physiological (n = 8), psychological (n = 3) and soccer-specific skills (n = 2) tests. Variables were split into separate groups according to somatotype, body composition, body size, speed, endurance, performance measures, technical skill, anticipation, anxiety and task and ego orientation for purposes of univariate and multivariate analysis of variance and stepwise discriminant function analysis. The most discriminating of the measures were agility, sprint time, ego orientation and anticipation skill. The elite players were also significantly leaner, possessed more aerobic power (9.0 +/- 1.7 vs 55.5 +/- 3.8 ml x kg(-1) x min(-1)) and were more tolerant of fatigue (P < 0.05). They were also better at dribbling the ball, but not shooting. We conclude that the test battery used may be useful in establishing baseline reference data for young players being selected onto specialized development programmes.

Objective. The existence of the home advantage in sport is well known. There is growing evidence that crowd noise plays a crucial part in this phenomenon. Consequently, a quantitative study was undertaken to examine influence of crowd noise upon refereeing decisions in association football (soccer). The association between years of experience and any imbalance in refereeing decisions was also addressed.Methods. To investigate whether the presence or absence of crowd noise might influence qualified referees when assessing various tackles/challenges recorded on videotape. Binary logistic regression was used to assess the effect of crowd noise and years of experience on referees' decisions.Results. The presence of crowd noise had a dramatic effect on the decisions made by referees. Those viewing the challenges with background crowd noise were more uncertain in their decision making and awarded significantly fewer fouls (15.5%) against the home team, compared with those watching in silence.Conclusions. The noise of the crowd influenced referees' decisions to favour the home team. It is suggested that referees' decisions are influenced by the salient nature of crowd noise, the potential use of heuristic strategies, and the need to avoid potential crowd displeasure by making a decision in favour of the home team. 

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Summary. This paper examines how selected physiological performance variables, such as maximal oxygen uptake, strength and power, might best be scaled for subject differences in body size. The apparent dilemma between using either ratio standards or a linear adjustment method to scale was investigated by considering how maximal oxygen uptake (l" rain-1), peak and mean power output (W) might best be adjusted for differences in body mass (kg). A curvilinear power function model was shown to be theoretically, physiologically and empirically superior to the linear models. Based on the fitted power functions, the best method of scaling maximum oxygen uptake, peak and mean power output, required these variables to be divided by body mass, recorded in the units kg 2/3. Hence, the power function ratio standards (ml.kg -2/3.min -1) and (W.kg-2/3) were best able to describe a wide range of subjects in terms of their physiological capacity, i.e. their ability to utilise oxygen or record power maximally, independent of body size. The simple ratio standards (ml. kg-1. min-1) and (W. kg -1) were found to best describe the same subjects according to their performance capacities or ability to run which are highly dependent on body size. The appropriate model to explain the experimental design effects on such ratio standards was shown to be log-normal rather than normal. Simply by taking logarithms of the power function ratio standard, identical solutions for the design effects are obtained using either ANOVA or, by taking the unscaled physiological variable as the dependent variable and the body size variable as the covariate, ANCOVA methods.

[ research report ] B allet dancers are described as both artists and athletes, 19,25 performing complex artistic routines that require a high level of athletic ability due to the extreme physical demands placed on them. 51 Consequently, ballet dancers are at risk for injuries that can potentially disrupt performance and curtail a career.23,51 The van Mechelen et al 56 injury prevention model indicates the need to understand the extent of the injury problem. However, within dance, this has been challenging due to methodological deficiencies and inconsistencies in published epidemiological studies. 4,22,27 These include the choice of research design, such as injury surveys 3,26,28,46 and retrospective data collection, 17,37 and variations in injury definitions, including medical attention 17,37 and financial cost. 18When examined prospectively, the incidence of dance injury has been reported to be between 0.62 and 5.6 injuries per 1000 dancing hours. 19,30,38 Two of these studies were based on preprofessional dancers, 19,30 which may render the findings less generalizable to a professional ballet company. 22,53Although epidemiological studies can aid in the understanding of the injury profile, allowing appropriate interventions to reduce the risk of injury, 34,35,40 the epidemiology of injuries in ballet is not well understood. Therefore, the purpose of this study was to undertake injury surveillance of professional ballet dancers to enhance our understanding of injuries and to provide a foundation for future interventions to reduce injury incidence. Specific objectives were to report the incidence, severity, and etiology of injuries sustained by a cohort of professional ballet dancers, including the nature of the injuries as intrinsic or extrinsic, whether they were traumatic or from overuse, and the episode of injury (first occurrence, exacerbation, or recurrence). Furthermore, the objective was to look at the impact of dance activity and the dancers' rank on injuries and whether differences occur between genders. METHODS Aprofessional ballet company composed of 52 dancers (female, 27; male, 25) was prospectively studied over 1 performance year. Female dancers had a mean  SD age of 25  6 years, height of 162.2  3.7 cm, weight of 49.2  4.0 kg, and body mass index of 18.9  1.6 kg/m 2 . Male dancers had a mean  SD age of 23  5 years, height of 179.6  4.3 cm, weight of 71.7  4.7 kg, and body mass index of 22.2  1.4 kg/ m 2 . All dancers were assigned a rank for the entire year based on their position in the company. The highest rank within the company is principal, followed by soloist, T T STUDY DESIGN: Prospective, descriptive single-cohort study. T T OBJECTIVE:To assess the incidence and severity of injuries to a professional ballet company over 1 year. T T METHODS: Data for an elite-level ballet company of 52 professional dancers were collected by an in-house medical team using a time-loss injury definition. T T RESULTS:A total of 355 injuries were recorded, with an overall injury incidence of 4.4 inju...

Objective-The consensus of opinion suggests that when assessing measurement agreement, the most appropriate statistic to report is the "95% limits of agreement". The precise form that this interval takes depends on whether a positive relation exists between the differences in measurement methods (errors) and the size of the measurements-that is, heteroscedastic errors. If a positive and significant relation exists, the recommended procedure is to report "the ratio limits of agreement" using log transformed measurements.

The aims of this study were to assess 1) whether the stature-adjusted body mass index (BMI) is a valid proxy for adiposity across both athletic and nonathletic populations, and 2) whether skinfold measurements increase in proportion to body size, thus obeying the principle of geometric similarity. The research design was cross-sectional, allowing the relationship between skinfold calliper readings (at eight sites and between specific athletic and nonathletic groups, n ¼ 478) and body size (either mass, stature, or both) to be explored both collectively, using proportional allometric MAN-COVA, and individually (for each site) with follow-up ANCOVAs. Skinfolds increase at a much greater rate relative to body mass than that assumed by geometric similarity, but taller subjects had less rather than more adiposity, calling into question the use of the traditional skinfold-stature adjustment, 170.18/stature. The best body-size index reflective of skinfold measurements was a stature-adjusted body mass index similar to the BMI. However, sporting differences in skinfold thickness persisted, having controlled for differences in body size (approximate BMI) and age, with male strength-and speed-trained athletes having significantly lower skinfolds (32% and 23%, respectively) compared with controls. Similarly, female strength athletes had 29% lower skinfold measurements compared to controls, having controlled for body size and age. These results cast serious doubts on the validity of BMI to represent adiposity accurately and its ability to differentiate between populations. These findings suggest a more valid (less biased) assessment of fatness will be obtained using surface anthropometry There can be no doubt that people in the Western world are getting fatter. Indeed, some authors refer to this trend in increasing fatness as an ''obesity epidemic' ' (Davey and Stanton, 2004;Jeffreys et al., 2003;Popkin, 2001). Clearly, there is a need to monitor these systematic changes in fatness, using reliable and valid measures of adiposity. In population studies, the two most commonly reported indices of fatness or obesity are 1) body mass index (BMI ¼ body mass/stature 2 ), where body mass and stature are recorded in kilograms (kg) and meters (m), respectively, and 2) relative adiposity, commonly estimated either by waist/hip girth ratios or from summing measurements of raised skinfolds.Numerous studies investigated the relationship between body fat and stature-adjusted body mass with a view to obtaining a simple index to identify the overweight or obese members of the community (reviewed in Cole, 1991). In such studies, BMI emerges as the overwhelming favorite. Despite its convenience and popularity, some researchers still consider BMI a relatively crude index of adiposity, predominantly due to the fact that it fails to quantify body composition. Indeed, healthy adults can be misdiagnosed by BMI as overweight or obese, if fat mass is verified by a criterion method (Hortobagyi et al., 1994). For instance, a slender-framed fema...