Training load and intensity distribution for sprinting among world-class track cyclists.

BACKGROUND: Only few studies analyzed real training programs of sprinters while that should be a valuable step in the understanding of sprint training. The present study aimed at characterizing track cycling sprinter training by training load and intensity distribution. METHODS: Twenty-nine weeks of prechampionship training data were retrospectively analyzed for 6 world-class athletes. Training load was measured by the ratio of volume completed to maximal volume and categorized by five intensity zones (endurance: zones1-2; sprinting: zones3-5) and exercise type (on-bike or resistance). Intra-week (training monotony) and inter-week (acute-chronic workload ratio) variation was also studied. RESULTS: On-bike training represented 77.4±15.3% of total training load; resistance training, 22.6±15.2% (note high standard deviation). Total weekly training load significantly varied (P=0.0002) with high acute-chronic workload ratio (12.0±3.2 weeks >1.5 or <0.8), but low intra-week variations (training monotony, 1.81±0.20). Zone4 and zone5 made up 74.4±16.9% of total training load; zone1, 15.8±11%. Training load was seldom in zone2 (6.4±5.3%) or zone3 (3.3±4.2%). From the first to the second half of the period, zone3-4 training load decreased (39.3±3.3 to 27.4±1.7%; P=0.01), while zone5 increased (34.9±2.4 to 50±3.7%; P=0.002). CONCLUSIONS: In this reduced group of elite athletes, training appeared to mainly consist of on-bike exercises within the highest intensity zones. As demonstrated by monotony and acute-chronic workload ratio overloading and unloading are based on high variations over weeks, not days. Essentially, this study describes a polarized intensity distribution on the highest intensities which increased with world championships approach.

Relative age effects in track-and-field: Identification and performance rebalancing.

Introduction: Relative Age Effect (RAE) consists of a biased distribution of the dates of birth in a same-age group. Objectives: This study aimed to investigate Relative Age Effect among French athletes in different track-and-field events, and propose a corrective adjustment method to highlight the true potential of an athlete with respect to his/her relative age. Methods: 358,610 performances from 2009 to 2019 of female and male athletes between 12 and 21 years old were collected. Relative age distributions of performances were analyzed by level of competitiveness ("All," "Top50%," "Top10%" where "all" represents all athletes, top50% and top10% represent the best 50% and 10% of athletes per age category respectively) and age category, with chi-square and odd-ratio statistics. A linear relationship between distribution of performances and age leads to a calibration coefficient allowing to rebalance the performance by considering the effect of Relative Age Effect. Validation is obtained by Wilcoxon statistical test on actual athlete data. Results: Relative Age Effect is present in all types of events. It is larger when the level of competitiveness increases. In male 100 m sprint, 1 year difference between two athletes birth date represents an average gain of 931.01 ms (6.5%) in the U13 (Under 13 years old) and 229.65 ms (1.9%) in the U17 (Under 17 years old) categories. Our validated rebalancing methods allows to compensate for the biases induced by the relative age effect. By comparing the rebalanced performance and the realised performance of each athlete, we cannot say that they are significantly different. On average, there is no significant difference between these two performances. Conclusion: This study showed that there is a relative age effect among young French athletes, with an even greater effect as the level of competition increases. Thanks to the rebalancing method that has been validated, performances can now be better appreciated according to category and event.