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.

Esteve-Lanao, J, Del Rosso, S, Larumbe-Zabala, E, Cardona, C, Alcocer-Gamboa, A, and Boullosa, DA. Predicting marathon performance time throughout the training preparation in recreational runners. J Strength Cond Res 35(11): 3218–3224, 2021—The objective of this study was to predict marathon performance at different time points along the season using different speeds derived from ventilatory thresholds and running economy (RE). Sixteen recreational runners (8 women and 8 men) completed a 16-week marathon training macrocycle. Aerobic threshold (AeT), anaerobic threshold (AnT), and maximal oxygen uptake were assessed at the beginning of the season, whereas speeds eliciting training zones at AeT and AnT, and RE were evaluated at 5-time points during the season (M1–M5). Analyses of variance and hierarchical regression analyses were conducted. Training improved AeT and AnT speeds at M2 vs. M1 (p = 0.001) and remained significantly higher at M3, M4, and M5 (p = 0.001). There was a significant effect of time (p = 0.003) for RE, being higher at M4 and M5 compared with M1 and M3. Significant correlations were found between marathon performance and speeds at AeT and AnT at every time point (r = 0.81–0.94; p < 0.05). Speed at AnT represented the main influence (65.9 and 71.41%) in the final time prediction at M1 and M2, whereas speed at AeT took its place toward the end of the macrocycle (76.0, 80.4, and 85.0% for M3, M4, and M5, respectively). In conclusion, assessment of speeds at AeT and AnT permits for reasonable performance prediction during the training preparation, therefore avoiding maximal testing while monitoring 2 fundamental training speeds. Future research should verify if these findings are applicable to runners of different levels and other periodization models.

The aim of this study was to describe the pacing distribution during 6 editions of the world cross-country championships.Methods: Data from the 768 male runners participating from 2007 to 2013 were considered for this study. Blocks of 10 participants according to final position (eg, 1st to 10th, 11 to 20th, etc) were considered.Results: Taking data from all editions together, the effect of years was found to be significant (F_5,266 = 3078.69, P < .001, ω² = 0.31), as well as the effect of blocks of runners by final position (F_4,266 = 957.62, P < .001, ω² = 0.08). A significant general decrease in speed by lap was also found (F_5,1330 = 2344.02, P < .001, ω² = 0.29). Post hoc analyses were conducted for every edition where several pacing patterns were found. All correlations between the lap times and the total time were significant. However, each lap might show different predicting capacity over the individual outcome.Discussion: Top athletes seem to display different strategies, which allow them to sustain an optimal speed and/or kick as needed during the critical moments and succeed. After the first group (block) of runners, subsequent blocks always displayed a positive pacing pattern (fast to slow speed). Consequently, a much more stable pacing pattern should be considered to maximize final position.Conclusions: Top-10 finishers in the world cross-country championships tend to display a more even pace than the rest of the finishers, whose general behavior shows a positive (fast-to-slow) pattern.

The aim of this study was to evaluate changes in electromyographic activity with the use of gradual compression stockings (GCSs) on middle-distance endurance athletes’ performance, based on surface electromyography measurement techniques. Sixteen well-trained athletes were recruited (mean ± SD: age 33.4 ± 6.3 years, VO_2max 63.7 ± 6.3 mL·kg⁻¹·min⁻¹, maximal aerobic speed 19.7 ± 1.5 km·h). The athletes were divided into two groups and were assigned in a randomized order to their respective groups according to their experience with the use of GCSs. Initially, a maximum oxygen consumption (VO_2max) test was performed to standardize the athletes’ running speeds for subsequent tests. Afterward, electromyographic activity, metabolic, and performance variables for each group were measured with surface electromyography. In addition, blood lactate concentration was measured, both with and without GCSs, during 10 min at 3% above VT2 (second ventilatory threshold), all of which were performed on the track. Next, surface electromyography activity was measured during a 1 km run at maximum speed. No significant changes were found in electromyography activity, metabolic and performance variables with GCSs use (p > 0.164) in any of the variables measured. Overall, there were no performance benefits when using compression garments against a control condition.

Background: This study aimed to provide reference values for estimating training intensities in long-distance runners based on progressive incremental tests, considering differences related to sex and performance level. Methods: A total of 1411 endurance-trained runners (819 men and 592 women) completed a standardized treadmill protocol with gas exchange analysis to determine ventilatory thresholds and peak oxygen consumption (VO_2peak). Heart rate (HR) and running speed at each threshold were expressed relative to their peak values. Results: HR at second ventilatory threshold (VT2) occurred at 93.5 ± 2.5% of HR peak, and HR at first ventilatory threshold at 85.1 ± 4.6%. The relative running speeds at VT2 and VT1 corresponded to 87.6 ± 3.9% and 73.9 ± 5.5% of the speed at VO_2peak, respectively. In men, beginners exhibited higher relative HR and VO₂ values at the ventilatory thresholds than elite runners. In contrast, women displayed higher and more stable relative values across performance levels. Conclusions: These findings establish precise, evidence-based reference ranges derived from a large cohort of runners and highlight the need to consider sex and performance level when estimating exercise intensities. Individualized physiological assessment remains essential for accurate training prescription and performance optimization.