The present study aimed to determine the epidemiology of sport-related injuries in amateur and professional adolescent athletes and the incidence of different risk factors on those injuries. Four hundred ninety-eight athletes aged 14 to 21 voluntarily participated in this prospective injury surveillance, conducted from 1 January 2019 to 31 December 2019. The information collected included: personal data, sports aspects, characteristics of the injuries, and lifestyle. Forty point four percent of the participants suffered an injury in 2019 (39% of them in a previously injured area). The average injury rate was 2.64 per 1000 h. Soccer presented the highest rate (7.21). The most common injuries were: lumbar muscle strains (12.24%), ankle sprains (11.98%), and bone fractures (9.31%). Ankles (36.12%), knees (19.32%), and shoulders (6.47%) concentrated the highest number of injuries. Fifty-nine point twenty-eight percent of the injuries occurred during practices, and 40.72% during competition or peri-competition. Higher injury rates were associated (in this order) with the following factors: (a) Greater number of hours of practice per week. (b) Not performing warm-ups. (c) Using inadequate sports facilities. (d) Being aged 14–17. (e) Not performing physical preparation. (f) Inappropriate training load. (g) Not performing injury-preventive activities. (h) Performing sports technique without the supervision of one sports coach. (i) Inadequate sports equipment. In conclusion, since most injury risk factors are modifiable, it is imperative to implement strategies to reduce amateur and professional adolescent athletes’ injury rates.

The pacing behaviors used by elite athletes differ among individual sports, necessitating the study of sport-specific pacing profiles. Additionally, pacing behaviors adopted by elite runners differ depending on race distance. An "all-out" strategy, characterized by initial rapid acceleration and reduction in speed in the later stages, is observed during 100 m and 200 m events; 400 m runners also display positive pacing patterns, which is characterized by a reduction in speed throughout the race. Similarly, 800 m runners typically adopt a positive pacing strategy during paced "meet" races. However, during championship races, depending on the tactical approaches used by dominant athletes, pacing can be either positive or negative (characterized by an increase in speed throughout). A U-shaped pacing strategy (characterized by a faster start and end than during the middle part of the race) is evident during world record performances at meet races in 1500 m, 5000 m, and 10,000 m events. Although a parabolic J-shaped pacing profile (in which the start is faster than the middle part of the race but is slower than the endspurt) can be observed during championship 1500 m races, a negative pacing strategy with microvariations of pace is adopted by 5000 m and 10,000 m runners in championship races. Major cross country and marathon championship races are characterized by a positive pacing strategy; whereas a U-shaped pacing strategy, which is the result of a fast endspurt, is adopted by 3000 m steeplechasers and half marathoners. In contrast, recent world record marathon performances have been characterized by even pacing, which emphasizes the differences between championship and meet races at distances longer than 800 m. Studies reviewed suggest further recommendations for athletes. Throughout the whole race, 800 m runners should avoid running wide on the bends. In turn, during major championship events, 1500 m, 5000 m, and 10,000 m runners should try to run close to the inside of the track as much as possible during the decisive stages of the race when the speed is high. Staying within the leading positions during the last lap is recommended to optimize finishing position during 1500 m and 5000 m major championship races. Athletes with more modest aims than winning a medal at major championships are advised to adopt a realistic pace during the initial stages of long-distance races and stay within a pack of runners. Coaches of elite athletes should take into account the observed difference in pacing profiles adopted in meet races vs. those used in championship races: fast times achieved during races with the help of one or more pacemakers are not necessarily replicated in winner-takes-all championship races, where pace varies substantially. Although existing studies examining pacing characteristics in elite runners through an observational approach provide highly ecologically valid performance data, they provide little information regarding the underpinning mechanisms that explain the behaviors shown. Therefore, further research is needed in order to make a meaningful impact on the discipline. Researchers should design and conduct interventions that enable athletes to carefully choose strategies that are not influenced by poor decisions made by other competitors, allowing these athletes to develop more optimal and successful behaviors.

Endurance running has become an immensely popular sporting activity, with millions of recreational runners around the world. Despite the great popularity of endurance running as a recreational activity during leisure time, there is no consensus on the best practice for recreational runners to effectively train to reach their individual objectives and improve physical performance in a healthy manner. Moreover, there are lots of anecdotal data without scientific support, while most scientific evidence on endurance running was developed from studies observing both recreational and professional athletes of different levels. Further, the transference of all this information to only recreational runners is difficult due to differences in the genetic predisposition for endurance running, the time available for training, and physical, psychological, and physiological characteristics. Therefore, the aim of this review is to present a selection of scientific evidence regarding endurance running to provide training guidelines to be used by recreational runners and their coaches. The review will focus on some key aspects of the training process, such as periodization, training methods and monitoring, performance prediction, running technique, and prevention and management of injuries associated with endurance running.

Casado, A, Hanley, B, Santos-Concejero, J, and Ruiz-Pérez, LM. World-class long-distance running performances are best predicted by volume of easy runs and deliberate practice of short-interval and tempo runs. J Strength Cond Res 35(9): 2525–2531, 2021—The aim of this novel study was to analyze the effect of deliberate practice (DP) and easy continuous runs completed by elite-standard and world-class long-distance runners on competitive performances during the first 7 years of their sport careers. Eighty-five male runners reported their best times in different running events and the amounts of different DP activities (tempo runs and short- and long-interval sessions) and 1 non-DP activity (easy runs) after 3, 5, and 7 years of systematic training. Pearson's correlations were calculated between performances (calculated using the International Association of Athletics Federations' scoring tables) and the distances run for the different activities (and overall total). Simple and multiple linear regression analysis calculated how well these activities predicted performance. Pearson's correlations showed consistently large effects on performance of total distance ( r ≥ 0.75, p < 0.001), easy runs ( r ≥ 0.68, p < 0.001), tempo runs ( r ≥ 0.50, p < 0.001), and short-interval training ( r ≥ 0.53, p < 0.001). Long-interval training was not strongly correlated ( r ≥ 0.22). Total distance accounted for significant variance in performance ( R ² ≥ 0.57, p < 0.001). Of the training modes, hierarchical regression analysis showed that easy runs and tempo runs were the activities that accounted for significant variance in performance ( p < 0.01). Although DP activities, particularly tempo runs and short-interval training, are important for improving performance, coaches should note that the non-DP activity of easy running was crucial in better performances, partly because of its contribution to total distance run.

This review aimed to examine the current evidence for 3 primary training intensity distribution types: (1) pyramidal training, (2) polarized training, and (3) threshold training. Where possible, the training intensity zones relative to the goal race pace, rather than physiological or subjective variables, were calculated. Three electronic databases (PubMed, Scopus, and Web of Science) were searched in May 2017 for original research articles. After analysis of 493 resultant original articles, studies were included if they met the following criteria: (1) Their participants were middle- or long-distance runners; (2) they analyzed training intensity distribution in the form of observational reports, case studies, or interventions; (3) they were published in peer-reviewed journals; and (4) they analyzed training programs with a duration of 4 wk or longer. Sixteen studies met the inclusion criteria, which included 6 observational reports, 3 case studies, 6 interventions, and 1 review. According to the results of this analysis, pyramidal and polarized training are more effective than threshold training, although the latest is used by some of the best marathon runners in the world. Despite this apparent contradictory finding, this review presents evidence for the organization of training into zones based on a percentage of goal race pace, which allows for different periodization types to be compatible. This approach requires further development to assess whether specific percentages above and below race pace are key to inducing optimal changes.

The aim of the present study was to describe a novel training model based on lactate-guided threshold interval training (LGTIT) within a high-volume, low-intensity approach, which characterizes the training pattern in some world-class middle- and long-distance runners and to review the potential physiological mechanisms explaining its effectiveness. This training model consists of performing three to four LGTIT sessions and one VO_2max intensity session weekly. In addition, low intensity running is performed up to an overall volume of 150–180 km/week. During LGTIT sessions, the training pace is dictated by a blood lactate concentration target (i.e., internal rather than external training load), typically ranging from 2 to 4.5 mmol·L⁻¹, measured every one to three repetitions. That intensity may allow for a more rapid recovery through a lower central and peripheral fatigue between high-intensity sessions compared with that of greater intensities and, therefore, a greater weekly volume of these specific workouts. The interval character of LGTIT allows for the achievement of high absolute training speeds and, thus, maximizing the number of motor units recruited, despite a relatively low metabolic intensity (i.e., threshold zone). This model may increase the mitochondrial proliferation through the optimization of both calcium and adenosine monophosphate activated protein kinase (AMPK) signaling pathways.