Long-term sports participation and performance development are major issues in popular sports and talent development programs. This study aimed to provide longitudinal trends in youth female long jump performance development, participation, and relative age effects (RAEs), as longitudinal data for female athletes are missing. 51′894 season’s best results of female long jump athletes (n = 16′189) were acquired from the Swiss Athletics online database and analyzed within a range of 6–22 years of age. To examine longitudinal performance development and RAEs, data from athletes who participated in at least three seasons were selected (n = 41′253) and analyzed. Performance development was analyzed using age groups (AGs) and exact chronological age (CA) at competition. Differences between performances of birth quarters were analyzed using 83% confidence intervals (CIs) and smallest worthwhile change. Odds ratios (ORs) with 95% CI were used to quantify RAEs. With the traditional classification into age groups (AG), performances of athletes born between January and March (Q1) were significantly better than those born between October and December (Q4) from U8 to U17. Using exact CA resulted in similar performances in Q1 and Q4 until the U20 age category. The peak of participation was reached in the U12 category, and then decreased until the U23 category with a substantial drop at U17. Significant RAEs were observed from U8 to U19 and at U22. RAEs continuously decreased from U8 (large effect) to U14 (small effect). The present results show that differences in performance arise from the comparison of athletes in AGs. Thus, going beyond AGs and using exact CA, Q4 athletes could benefit from a realistic performance comparison, which promotes fair performance evaluation, un-biased talent development, realistic feedback, and long-term participation.
Abstract The purpose of this study was to investigate changes in post-exercise heart rate recovery (HRR) and heart rate variability (HRV) during an overload-tapering paradigm in marathon runners and examine their relationship with running performance. 9 male runners followed a training program composed of 3 weeks of overload followed by 3 weeks of tapering (-33 ± 7%). Before and after overload and during tapering they performed an exhaustive running test (T(lim)). At the end of this test, HRR variables (e.g. HRR during the first 60 s; HRR(60 s)) and vagal-related HRV indices (e.g. RMSSD(5-10 min)) were examined. T(lim) did not change during the overload training phase (603 ± 105 vs. 614 ± 132 s; P = 0.992), but increased (727 ± 185 s; P = 0.035) during the second week of tapering. Compared with overload, RMSSD(5-10 min) (7.6 ± 3.3 vs. 8.6 ± 2.9 ms; P = 0.045) was reduced after the 2(nd) week of tapering. During tapering, the improvements in T(lim) were negatively correlated with the change in HRR(60 s) (r = -0.84; P = 0.005) but not RMSSD(5-10 min) (r = -0.21; P = 0.59). A slower HRR during marathon tapering may be indicative of improved performance. In contrast, the monitoring of changes in HRV as measured in the present study (i.e. after exercise on a single day), may have little or no additive value.
Accurate assessment of training load (TL) and training load responses (TLR) might be useful for an optimized training regulation and prevention of overtraining. No consensus on a gold-standard for measuring TL or intensity in endurance sports has been reported in the available literature so far. The aim of the present article is i) to identify feasible parameters to measure TL and TLR in daily training and ii) to compare these scientific approaches with the needs of elite endurance coaches. Therefore, the first part provides a systematic review of the current literature and the second part concentrates on the results of a questionnaire that assessed the coaches’ requirements for monitoring daily endurance training. The systematic review revealed that the combination of both quantitative and qualitative data seems most promising to evaluate TL and TLR. Thus, validated questionnaires or rating of perceived exertion (RPE), combined with physiological parameters, such as heart rate, are often used and seem to provide the most reliable results. From the coaches’ perspective, duration and kind of training, RPE, as well as personal remarks in the athletes’ training diaries are considered to be essential information. Further, the coaches favor a feasible system that collects large amounts of directly measurable and perceived data and that is able to learn from previous events in order to present the most important information in a short individual overview. When comparing both parts of the present study, it becomes clear that the scientific research cannot yet fully respond to the coaches’ requests, however, based on the coaches’ propositions, scientific research might be stimulated to tackle this challenge in the near future.
