Search Results

Purpose: This study investigated (1) the transition rate of elite world-class throwers, (2) the age of peak performance in either elite junior and/or elite senior athletes, and (3) if relative age effect (RAE) influences the chance of being considered elite in junior and/or senior category. Methods: The career performance trajectories of 5108 throwers (49.9% females) were extracted from the World Athletics database. The authors identified throwers who had reached the elite level (operationally defined as the World all-time top 50 ranked for each age category) in either junior and/or senior category and calculated the junior-to-senior transition rate. The age of peak performance and the RAE were also investigated. Results: The transition rate at 16 and 18 years of age was 6% and 12% in males and 16% and 24% in females, respectively. Furthermore, elite senior throwers reached their personal best later in life than elite junior throwers. The athletes of both genders considered elite in the junior category showed a large RAE. Interestingly, male athletes who reached the elite level in senior category also showed appreciable RAE. Conclusions: Only a few of the athletes who reach the top 50 in the world at 16 or 18 years of age manage to become elite senior athletes, underlining that success at the beginning of an athletic career does not predict success in the athlete’s senior career. Moreover, data suggest that being relatively older may confer a benefit across the whole career of male throwers.

Purpose: To quantify how many of the top 50 under-18 (U18) sprinters in the world managed to become top 50 ranked as adult competitors. The authors also described the career trajectory of athletes ranked in the top 50 during either U18 or senior category. Methods: A total of 4924 male and female athletes competing in sprint races and ranked in the International Association of Athletics Federations (now World Athletics) lists in any of the seasons between the 2000 and 2018 were included in the study. The athletes ranked in the top 50 positions of all-time lists during U18, senior, or both categories were analyzed. Results: Only 17% of the male and 21% of the female top 50 ranked U18 managed to become top 50 ranked senior athletes. The top 50 ranked senior athletes consistently produced yearly larger improvements during late adolescence and early adulthood compared with those who ranked in the top 50 at U18. Furthermore, top 50 ranked senior athletes reached their peak performance later compared with the top 50 ranked only in U18. Conclusions: This study confirms that early success in track and field is not a good predictor of success at senior level in sprinting events. The yearly performance improvements and their tracking provide the most suitable approach to identify athletes more likely to succeed as elite performers in adulthood. The authors hope that the results of this study can provide useful comparative data and reference criteria for talent-identification and -development programs.

Purpose: This study aimed to describe the career performance progression of elite early- and later-success international swimmers competing in sprint events (ie, 50 and 100 m). Methods: The career performance trajectories of 6003 swimmers (50.9% females; 58,760 unique records) competing in the 4 swimming strokes were evaluated. Swimmers with early and later success were identified. The authors identified the top 50 all-time swimmers competing in junior career who did not reach the top 50 rankings in their senior career, and vice versa, and successful swimmers in both junior and senior career. Results: Early-success swimmers mainly achieved their peak performance before the age of 20 years and approximately 5–6 years before successful senior swimmers or approximately 3–4 years before successful swimmers both in junior and senior careers. The annual performance improvements of later-success swimmers were higher (about 1%–2%) until the age of 20 to 24 years, whereas early-success swimmers showed a performance stagnation at about 16 to 18 years in females and 19 to 20 years in males. Conclusions: Early-success swimmers who achieved peak performance at a young age were unable to maintain the same level of competitiveness in adulthood as they experienced a plateau in performance from the age of 20 years. The procedure of considering early performances solely for talent identification (and not the current rate of progression) might represent a limited approach for selecting future elite swimmers. Our results indicate that performance progression in the transition toward adult careers might be a strong indicator of performance potential.

Purpose: The primary aim of this study was to evaluate whether the internal (session rating of perceived exertion [sRPE] and Edwards heart-rate-based method) and external training load (jumps) affect the presession well-being perception on the day after (ie, +22 h), according to age and tactical position, in elite (ie, Serie A2) female volleyball training. Methods: Ten female elite volleyball players (age = 23 [4] y, height = 1.82 [0.04] m, body mass = 73.2 [4.9] kg) had their heart rate monitored during 13 team (115 individual) training sessions (duration: 101 [8] min). Mixed-effect models were applied to evaluate whether sRPE, Edwards method, and jumps were correlated (P ≤ .05) to Hooper index factors (ie, perceived sleep quality/disorders, stress level, fatigue, and delayed-onset muscle soreness) in relation to age and tactical position (ie, hitters, central blockers, opposites, and setters). Results: The results showed a direct relationship between sRPE (P < .001) and presession well-being perception 22 hours apart, whereas the relationship was the inverse for Edwards method internal training load. Age, as well as the performed jumps, did not affect the well-being perception of the day after. Finally, central blockers experienced a higher delayed-onset muscle soreness than hitters (P = .003). Conclusions: Findings indicated that female volleyball players’ internal training load influences the pretraining well-being status on the day after (+ 22 h). Therefore, coaches can benefit from this information to accurately implement periodization in a short-term perspective and to properly adopt recovery strategies in relation to the players’ well-being status.

Purpose: The present study aimed to verify if practicing tackles during rugby union training sessions would affect the players’ internal training load and acute strength loss. Method: A total of 9 male Italian Serie A rugby union players (age: 21 [2] y) were monitored by means of an integrated approach across 17 sessions, 6 with tackles (WT) and 11 with no tackles (NT). Edwards training load was quantified using heart-rate monitoring. Global positioning system devices were used to quantify the total distance and time at >20 W. Work-to-rest ratio was quantified by means of a video analysis. Before (PRE) and after (POST) the session, the players’ well-being and rating of perceived exertion were measured, respectively. The countermovement jump and plyometric push-up jump tests were performed on a force plate to record the players’ PRE–POST concentric peak force. Linear mixed models were applied to quantify the differences between WT and NT in terms of training load and PRE–POST force deltas, even controlling for other training factors. Results: The Edwards training load (estimated mean [EM]; standard error [SE]; WT: EM = 214, SE = 11.8; NT: EM = 194, SE = 11.1; P = .01) and session rating of perceived exertion (WT: EM = 379, SE = 21.9; NT: EM = 277, SE = 16.4; P < .001) were higher in WT than in NT. Conversely, no difference between the sessions emerged in the countermovement jump and plyometric push-up concentric peak force deltas. Conclusions: Although elite rugby union players’ external and internal training load can be influenced by practicing tackles, upper- and lower-limb strength seem to not be affected.

Purpose: To evaluate if the internal training load (ITL; Edwards heart rate [HR]-based and session-rating of perceived exertion [RPE] methods) is affected by the presession well-being perception, age, and position in elite (ie, Serie A2) female volleyball training. Methods: Twelve female elite volleyball players (age: 22 [4] y, height: 1.80 [0.06] m, body mass: 74.1 [4.3] kg) were monitored using an HR monitor during 32 team training sessions (duration: 1:36:12 [0:22:24], in h:min:s). Linear mixed-effects models were applied to evaluate if well-being perception (ie, perceived sleep quality/disorders, stress level, fatigue, and delayed-onset muscle soreness) may affect ITL depending on age and tactical position. Results: Presession perceived fatigue influenced ITL according to the session-RPE (P = .032) but not according to the Edwards method. Age was inversely correlated to the Edwards method (P < .001) and directly correlated to the session-RPE (P = .027). Finally, central blockers experienced a higher training load than hitters (P < .001) and liberos (P < .001) for the Edwards method, as well as higher than hitters (P < .001), liberos (P = .003), and setters (P = .008) for  session-RPE. Conclusions: Findings indicated that female volleyball players’ perceived ITL is influenced by presession well-being status, age, and position. Therefore, coaches can benefit from this information to specifically predict players’ ITL in relation to their individual characteristics.