## 2 Materials and Methods
### Quantitative Data Analysis  
The quantitative data analysis involved extracting performance-related data, including the rankings and points scored from publicly accessible UCI databases. The data extracted included the season classification, nationality, birth date, and UCI points score. The age was calculated according to the UCI junior category regulations, taking the difference between the year of the classification and the rider's birth year. The data covered 4 different track cycling disciplines, 2 endurance (points race and scratch) and 2 sprints (sprint and keirin), for both male and female athletes in the junior and elite categories over ten years, with a two-year gap between the junior and elite databases (i.e., 2009-2018 and 2011-2020, respectively). The time frames were selected based on the year of availability of the databases, ensuring sufficient time for the cyclists to transition from the youth to senior categories, and considering the stability of the UCI point classification rules during the period. The athletes were ranked in their respective databases according to UCI regulations ([[https://www.uci.org/inside-uci/constitutions-regulations/regulations](https://www.uci.org/inside-uci/constitutions-regulations/regulations)]([https://www.uci.org/inside-uci/constitutions-regulations/regulations](https://www.uci.org/inside-uci/constitutions-regulations/regulations)), accessed on 14 March 2022). The study focused on the top 10% of ranked junior cyclists and the top 20 male and top 10 female elite cyclists. A similar approach was previously described in a previous study [8]. A total of 2348 observations were collected, and 1564 cyclists were analyzed after eliminating the redundant names. Among these cyclists, there were 1008 men and 556 women. A cyclist's name was considered redundant if it appeared multiple times within the same category and discipline. To address this, certain variables were calculated from the original database to retain only one occurrence per name. These variables included the corrected score, age at maximal scoring, age at first appearance in the database, number of appearances in the junior category, time taken to reach the elite category, and month of birth. The corrected score was calculated based on the UCI score, aiming to mitigate the effects of potential changes in the scoring regulations and differences in points availability between the seasons. The formula used for this calculation was as follows: \(Corrected\ score=(Score_{Rider}-Score_{Year})/\sigma_{Score_{year}}\), where \(Score_{Rider}\) represents the score of the rider; \(Score_{Year}\) denotes the mean score of the riders from the same year, sex, category, and discipline; and \(\sigma_{Score_{Year}}\) represents the standard deviation of the score within that same population. In the secondary database, the rankings and corrected scores were presented as the median/average, maximum, and minimum values for each rider.  
This allowed us to summarize the performance while ensuring only one occurrence per name. The reference for the time to reach the first elite top classification was set as 1, being a successful transition achieved in the first season after leaving the junior category. The months of birth were divided into quartiles according to the methodology described by [PERSON] et al. to account for the RAE [14]. Furthermore, riders were labeled as \"achievers\" if they reached, at least once, the top classification in both the junior and elite classifications within the same discipline. The \"achiever\" category pertains to the observations within that population during the junior years.