Tracking: Concepts, methods and tools

Is there stability in the performance of elite half-marathoners?

The purpose of this study was to investigate the performance stability of elite half-marathoners of both sexes. The study was composed of 24 elite athletes (12 female and 12 male), ranked among the Senior World TOP20 half-marathoners, who completed a half-marathon race for at least three consecutive years. Tracking was tested using autocorrelations and Kappa Cohen. Autocorrelation revealed a significant association, but a decrease in correlation among the years in both sexes. The overall weighted kappa showed lower stability in performance for both sexes (K ​= ​0.191 and K ​= ​−0.245) than for males. These findings suggest that both female and male elite half-marathoners showed low stability in performance during three events. Besides that, athletes with a better performance tended to present the highest performance stability. It is recommended that coaches track the developmental trajectories of the athletes to comprised the changes in performance across the years, as to provide environmental characteristics that can influence performance.

Tracking Technical Skill Development in Young Basketball Players: The INEX Study

This study investigated developmental stability, or tracking, in the development of technical skills in youth male basketball players and retrospectively profiled stable and unstable tracking patterns over time. A total of 97 basketball players were tracked bi-annually over 3 consecutive years. Players were divided into two age-categories according to their age at baseline: under-12; and under-14. Technical skills were assessed using the American Alliance for Health, Physical Education, Recreation and Dance test battery. Anthropometric, body composition, biological maturation and physical performance data were collected. Cohen's kappa (κ) was used to estimate tracking. With the exception of defensive movement in the under-12 age-category, tracking was low in all skill tests for both under-12 (0.22 ≤ κ ≤ 0.33) and -14 (0.20 ≤ κ ≤ 0.26) groupings. The overall technical skill showed moderate tracking for under-12 players (κ = 0.47) and low tracking for under-14 players (κ = 0.26). At baseline, players who were consistently more skilled or became more skillful (in the under-12 age-category) over time had a better growth-motor performance profile and most of them were selected to be members of regional teams. In conclusion, tracking of individual skill trajectories was low-to-moderate. Moreover, a better growth-motor performance profile seems crucial to maintain high levels of skill performance over time. It is recommended that basketball coaches track the developmental trajectories of their players to better understand the erratic nature of skill development and help design more effective practice regimes.

Change and Stability in Sibling Physical Fitness: The Portuguese Sibling Study

PURPOSE

This study aims to 1) describe mean changes in muscular and motor fitness components in sibships over 2 yr, 2) analyze individual tracking of fitness within sibships, 3) investigate sibling resemblance in fitness over time, and 4) examine the joint influence of biological, behavioral, and familial characteristics on fitness.

METHODS

The sample comprises 166 Portuguese biological sibling pairs (brother-brother, sister-sister, brother-sister) age 9-17 yr assessed at baseline and 2 yr later. Physical fitness components were measured with standardized tests. Percentage body fat and biological maturation were assessed, and physical activity, diet, screen time, and familial characteristics were obtained by questionnaires. Multilevel models were used to analyze the clustered longitudinal data.

RESULTS

Crude results showed that, on average, all sib-types increased their muscular and motor fitness components from baseline to follow-up (except sister-sister pairs in standing long jump and shuttle run). When adjusted for covariates, the mean changes were no longer significant. Individual tracking was moderate to high for the muscular component but low to moderate for the motor component. Consistency in sibling resemblance was higher in sister-sister pairs than in brother-brother and brother-sister pairs. More mature sibs were fitter in both components, whereas siblings with higher body fat percentage were less fit. Screen time, physical activity, and parental occupation were not associated with fitness components.

CONCLUSIONS

Biological characteristics were more strongly associated with fitness components than individual behaviors and familial characteristics. Furthermore, the muscular component tracked better than the motor component. Sister-sister pairs had greater resemblance in fitness over time compared with brother-brother or sister-brother pairs.

A methodological approach to short-term tracking of youth physical fitness: the Oporto Growth, Health and Performance Study

In this paper, three different statistical approaches were used to investigate short-term tracking of cardiorespiratory and performance-related physical fitness among adolescents. Data were obtained from the Oporto Growth, Health and Performance Study and comprised 1203 adolescents (549 girls) divided into two age cohorts (10-12 and 12-14 years) followed for three consecutive years, with annual assessment. Cardiorespiratory fitness was assessed with 1-mile run/walk test; 50-yard dash, standing long jump, handgrip, and shuttle run test were used to rate performance-related physical fitness. Tracking was expressed in three different ways: auto-correlations, multilevel modelling with crude and adjusted model (for biological maturation, body mass index, and physical activity), and Cohen's Kappa (κ) computed in IBM SPSS 20.0, HLM 7.01 and Longitudinal Data Analysis software, respectively. Tracking of physical fitness components was (1) moderate-to-high when described by auto-correlations; (2) low-to-moderate when crude and adjusted models were used; and (3) low according to Cohen's Kappa (κ). These results demonstrate that when describing tracking, different methods should be considered since they provide distinct and more comprehensive views about physical fitness stability patterns.

Modeling stability and change in strength development: a study in adolescent boys

The purpose of this study was to investigate stability and change in different expressions of strength development in adolescent boys using structural equation modeling. Three models were used: Markov simplex to study stability or tracking, Wiener or random walk to investigate fanning-out or spread effects in change, and latent growth to study differences in individual pathways of change as well as group changes. In the Leuven Growth Study, 588 male subjects were followed for 6 years with a mean age of 12.7 years at the onset of the study. Vertical jump, arm pull, and bent arm hang were used to mark the following strength factors: explosive strength, static strength, and functional strength. All models were tested with robust estimation procedures based on the software EQS 6.0. Main results and conclusions are as follows: 1) all strength factors showed moderate to high tracking, with low values of instability in relative position of the subjects in their developmental channels; 2) the fanning-out effect is not obvious, although some evidence showed a spread effect in functional and explosive strength; 3) there are marked interindividual differences in developmental pathways of strength manifestations; 4) strength development is linear and also has some curvilinearity, something akin to a breaking effect; 5) linear trend is negatively correlated with initial status and the leveling-off effect is also negatively correlated with the linear change.

PC program for assessing the effect of a treatment when subjects are growing: comparative studies

We describe, illustrate, and make available a menu-driven PC program which can be used to assess the effect of a treatment on growth when random allocation of subjects to the treatment and control groups is not feasible. Three different estimators of, and confidence intervals for, this effect are computed, namely, the simple gains, standardized gains, and covariance adjusted estimators. It is shown by means of several examples that these estimators can differ substantially, and some guidelines for choosing between them in specific circumstances are provided.

PC program for assessing the effect of a treatment when subjects are growing: the randomized parallel groups design

A method for separating the effects of a treatment from those of normal development in the case of a randomized parallel groups design with pre- and post-treatment measures is described and implemented. The program allows the user to enter either summary statistics (published data are often in this form), or the pre- and post-treatment measurements for each individual. The program is illustrated using data reflecting the extent to which a treatment can be expected to impede normal growth, but the method and program are more general than this. All that is required is that the measurement be one that normally increases over time.

Analysis of longitudinal data in craniofacial research: some strategies

Although it is generally acknowledged that longitudinal data provide the most information on growth and development and other time-dependent phenomena, such data are often analyzed by conventional (cross-sectional) statistical methods. This widespread practice ignores the distinctive characteristics (e.g., covariance structure) of longitudinal data and may yield misleading results. The purpose of this article is to present some strategies and make available computer programs for the appropriate analysis of longitudinal data. User-friendly PC programs for the estimation of average growth curves, computation of tracking indices, prediction of future values, diagnosis, classification, clustering, estimation of missing values, and testing hypotheses concerning individual and group differences are presented. Benefits of these methods over the usual techniques are illustrated with the example of maxillary growth in the rhesus monkey.

Clustering on the basis of longitudinal data

A menu-drive PC program, ZDIST, for computing the distances between the estimated polynomial growth curves of subjects who have been followed longitudinally is described, illustrated, and made available to interested readers. These distances can be computed on the basis of the individual growth curves themselves and/or from estimates of individuals' growth velocity and acceleration curves. The resulting distance matrices can be saved in ASCII format and subsequently imported into any clustering program which accepts this type of input, e.g. SYSTAT.