Abstract:Little is known about how recreational triathletes prepare for an Olympic distance event. The aim of this study was to identify the training characteristics of recreational-level triathletes within the competition period and assess how their preparation for a triathlon influences their health and their levels of fatigue. During the 6 weeks prior to, and the 2 weeks after, an Olympic distance triathlon, nine recreational athletes (five males, four females) completed a daily training log. Participants answered t… Show more
“…Exercise-induced fatigue is a common phenomenon during exercise, and its mechanisms mainly include peripheral and central mechanisms [9]. Central fatigue is a protective inhibition of the central nervous system; the purpose is to prevent excessive functional failure of the body [10]. It is known that central fatigue can be affected by many factors and there are significant individual differences, and the environment is one of the main factors [11].…”
Exercise-induced fatigue is a common phenomenon during exercise, and its mechanisms mainly include peripheral and central mechanisms. This article discusses the causes of the throwing athletes’ fatigue and the effective recovery methods used, in order to have a certain reference value for making throwing training plans more scientifically and rationally and participating in competitions. Central fatigue will seriously affect the athletic state of athletes, and environmental factors are one of the important factors affecting the central fatigue of athletes. Because the influence of central fatigue and environmental factors on throwing athletes is more prominent, the correlation between environmental factors and central fatigue in throwing sports is studied, and a general prediction model and grouping prediction model of athletes’ central fatigue under various environmental factors are established based on ANN. Experiments show that the established general prediction model of central fatigue of throwing athletes has good performance, and the correlation coefficient between the prediction results and the actual measured value is 0.68; for different groups of athletes, the established prediction model of central fatigue of throwing athletes has better performance. The prediction accuracy is high, and the correlation coefficient between the prediction result and the actual measurement value is higher than 0.70.
“…Exercise-induced fatigue is a common phenomenon during exercise, and its mechanisms mainly include peripheral and central mechanisms [9]. Central fatigue is a protective inhibition of the central nervous system; the purpose is to prevent excessive functional failure of the body [10]. It is known that central fatigue can be affected by many factors and there are significant individual differences, and the environment is one of the main factors [11].…”
Exercise-induced fatigue is a common phenomenon during exercise, and its mechanisms mainly include peripheral and central mechanisms. This article discusses the causes of the throwing athletes’ fatigue and the effective recovery methods used, in order to have a certain reference value for making throwing training plans more scientifically and rationally and participating in competitions. Central fatigue will seriously affect the athletic state of athletes, and environmental factors are one of the important factors affecting the central fatigue of athletes. Because the influence of central fatigue and environmental factors on throwing athletes is more prominent, the correlation between environmental factors and central fatigue in throwing sports is studied, and a general prediction model and grouping prediction model of athletes’ central fatigue under various environmental factors are established based on ANN. Experiments show that the established general prediction model of central fatigue of throwing athletes has good performance, and the correlation coefficient between the prediction results and the actual measured value is 0.68; for different groups of athletes, the established prediction model of central fatigue of throwing athletes has better performance. The prediction accuracy is high, and the correlation coefficient between the prediction result and the actual measurement value is higher than 0.70.
“…The latter had also been preparing for draft-legal OD competition. The OD triathlon personal best times of our males were, nonetheless, faster than those of the athletes who participated in Falk Neto et al’s prospective study of age-group-level OD training [ 16 ]. They were also faster (at 2:13:25 ± 0:16:07 vs. 2:12:24 ± 0:02:54; in hh:mm:ss) than Aoyagi et al’s (2021) nine younger “faster” well-trained males [ 6 ].…”
Section: Discussionmentioning
confidence: 93%
“…In no individual training block or individual triathlon discipline did the average proportion of swim, cycle and run training that the athletes spend in zone 1 exceed 56%. Falk Neto et al [16], whose intensity zones were set via RPE and guidelines in the literature and whose training data were prospective, reported that their slower age-group athletes spent 47% of training time in z1, 25% in z2 and 28% in z3. Vleck (2010) [14,35], using the same method of ascribing training intensity level as was used in this study, but over 30 weeks of prospective longitudinal data collection, reported that their 8 faster triathletes spent 70.4%, 6.1% and 9.1% of their overall training time in their intensity levels 1-2, 3 and 4-5, respectively, i.e., in z1, z2 and z3, respectively.…”
Section: Discussionmentioning
confidence: 99%
“…Fairly recently, Falk Neto et al [ 16 ] prospectively assessed the training and maladaptation of nine recreational triathletes. They did so over the 6 weeks that led up to, and for 2 weeks after, an OD triathlon that was a key event of the athletes’ competitive season.…”
Section: Introductionmentioning
confidence: 99%
“…Both because this was an exploratory study and to increase subject numbers, we used a retrospective study design. Such a design is less sensitive than the longitudinal prospective one that was implemented by [ 14 , 16 ]. However, the training volume and intensity distribution were, in this case, examined across successive training blocks, rather than across successive weeks, of the entire year leading up to the 2013 ITU World Age-Group Championships.…”
We assessed the training, work and Life Stress demands of a mixed gender group of 48 top amateur short-distance triathletes using an online retrospective epidemiological survey and the Life Events Survey for Collegiate Athletes. On superficial inspection, these mainly masters athletes appeared to undergo all the types of training that are recommended for the aging athlete. However, there were significant scheduling differences between their weekday vs. their weekend training, suggesting that age-groupers’ outside sports commitments may affect their training efficacy. The triathletes claimed to periodize, to obtain feedback on and to modify their training plans when appropriate—and some evidence of this was obtained. Over the year preceding the ITU World Age-Group Championships, they averaged 53%, 33% and 14% of their combined swim, cycle and run training time, respectively, within intensity zones 1, 2 and 3. Although the triathletes specifically stated that their training was focused on preparation for the ITU World Age-Group Championships, the way that they modified their training in the month before the event suggested that this aim was not necessarily achieved. Sports-related stress accounted for most—42.0 ± 26.7%—of their total Life Stress over the preceding year (vs. 12.7 ± 18.6% for Relationship-, 31.3 ± 25.9% for Personal- and 14.0 ± 21.1% for Career-related Stress). It affected most athletes, and was overwhelmingly negative, when it related to failure to attain athletic goal(s), to injury and/or to illness.
(1) Background: Studies on injury prevention programs are lacking for triathletes. The aim of the present study was to describe the results of a holistic (injury) training prevention program (HITP), based on training load control and strength training, in elite triathletes. (2) Methods: The study was conducted over 2021–2023 and involved 18 males and 10 females from the same training group. The HITP itself included various methods of fatigue monitoring, strength training focused on the prevention of overuse injuries (OIs), cycling skills training, and recovery strategies. The total number and type of injuries that were sustained, subsequent training/competition absence time, and injury incidence were determined. (3) Results: Twenty-four injuries were recorded over all three seasons, i.e., 0.65 injuries per 1000 h of training and competition exposure. Fourteen injuries were traumatic injuries (TIs) and ten were OIs. Of the OIs, four were of minimal severity, two were mild, three were moderate, and one was severe (accounting for 1–3, 4–7, 8–28, and >28 days of training absenteeism, respectively). A total of 46.4% of the participants did not present any type of injury and 71,4% did not incur any OIs. Average absenteeism was 17.3 days per injury. (4) Conclusions: The HITP design and implementation resulted in low OI and severe injury incidence. Due to their unpredictable nature, the number of TIs was not reduced. The TIs were suffered more frequently by men. Women are more likely to suffer from OIs, so it is particularly important to prevent OIs in women.
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