Exercise intensity during repeated days of racing in professional triathletes

Using Physiological Laboratory Tests and Neuromuscular Functions to Predict Extreme Ultratriathlon Performance

Purpose: This study aims to investigate the relationship between split disciplines and overall extreme ultra-triathlon (EUT) performance and verify the relationship among physiological and neuromuscular measurements with both fractional and total EUT performance while checking which variables could predict partial and overall EUT race time. Methods: Eleven volunteers (37 ± 6 years; 176.9 ± 6.1 cm; 77.9 ± 10.9 kg) performed two maximal graded tests (cycling and running) for physiological measurements and muscle strength/power tests to assess neuromuscular functions. Results: The correlation of swimming split times to predict overall EUT race times was lower than for cycling and running split times (r2 = 0.005; p > .05; r2 = 0.949; p < .001 and r2 = 0.925; p < .001, respectively). VO2peak obtained during running test (VO2peakrun) and VT power output assessed during cycling test (VTPO) were the highest predictors of cycling performance (r2 = 0.92; p = .017), whereas VO2peakrun and peakpower output in the cycling test (PPO) were the highest predictors of running performance (r2 = 0.94; p = .008). Conclusion: VO2peakrun and VTPO, associated to jump height assessed during countermovement jump (CMJ) test were the highest correlated variables to predict total EUT performance (r2 = 0.99; p = .007). In practical terms, coaches should include the assessment of VO2peakrun, VTPO, and CMJ to evaluate the athletes' status and monitor their performance throughout the season. Future studies should test how the improvement of these variables would affect EUT performance during official races.

Elite Triathlete Profiles in Draft-Legal Triathlons as a Basis for Talent Identification

Draft-legal triathlons are the main short-distance races worldwide and are those on which talent-identification programs are usually focused. Performance in these races depends on multiple factors; however, many investigations do not focus on elite triathletes. Therefore, the aim of this narrative review was to carry out a systematic literature search to define the elite female and male triathlete profiles and their competition demands in draft-legal triathlons. This will allow us to summarize the main determinant factors of high-level triathletes as a basis for talent detection. A comprehensive review of Web of Science and Scopus was performed using the search strategy: Triathl* and (performance or competition or profile) and (elite or professional or “high performance” or “high level” or talent). A total of 1325 research documents were obtained, and after screening following the criteria, only 83 articles were selected. After data synthesis, elite triathlete aspects such as age, physiological, anthropometric, and psychosocial profile or competition demands were studied in the scientific literature. Thus, it is essential that when implementing talent identification programs, these factors must be considered. However, constant updating is needed due the continuous regulatory changes and the need of triathletes to adapt to these new competition demands.

Exercise Intensity during Olympic-Distance Triathlon in Well-Trained Age-Group Athletes: An Observational Study

The aim of this study was to examine the exercise intensity during the swimming, cycling, and running legs of nondraft legal, Olympic-distance triathlons in well-trained, age-group triathletes. Seventeen male triathletes completed incremental swimming, cycling, and running tests to exhaustion. Heart rate (HR) and workload corresponding to aerobic and anaerobic thresholds, maximal workloads, and maximal HR (HR_max) in each exercise mode were analyzed. HR and workload were monitored throughout the race. The intensity distributions in three HR zones for each discipline and five workload zones in cycling and running were quantified. The subjects were then assigned to a fast or slow group based on the total race time (range, 2 h 07 min–2 h 41 min). The mean percentages of HR_max in the swimming, cycling, and running legs were 89.8% ± 3.7%, 91.1% ± 4.4%, and 90.7% ± 5.1%, respectively, for all participants. The mean percentage of HR_max and intensity distributions during the swimming and cycling legs were similar between groups. In the running leg, the faster group spent relatively more time above HR at anaerobic threshold (AnT) and between workload at AnT and maximal workload. In conclusion, well-trained male triathletes performed at very high intensity throughout a nondraft legal, Olympic-distance triathlon race, and sustaining higher intensity during running might play a role in the success of these athletes.

Race performance and exercise intensity of male amateur mountain runners during a multistage mountain marathon competition are not dependent on muscle strength loss or cardiorespiratory fitness

The aims of this study were to quantify the cardiorespiratory fitness level of amateur mountain runners and to characterize the related cardiorespiratory and muscular strain during a multistage competition. Therefore, 16 male amateur participants performed an incremental treadmill test before the Transalpine-Run 2010. Besides race time, heart rate (HR) was monitored using portable HR monitors during all stages, and countermovement jump ability was assessed after each stage. Overall race time and race times of the single stages were not related to any of the cardiorespiratory fitness parameters assessed during the incremental treadmill test (e.g., V[Combining Dot Above]O2max, ventilatory threshold). Average HR during the first stage was 81 ± 7% of the maximal HR and decreased to 73 ± 6% during the following stages. Creatine kinase activity as an indirect marker of muscle damage and strain amounted to 1,100 ± 619 U·L-1 after the third stage and was related to the decrease in the mean HR between stage 1 and stage 2 (r = -0.616, p < 0.05). Jump ability decreased continuously in the course of the race but was not related to exercise intensity. In conclusion, this study showed that race performance during a multistage mountain marathon does not depend on cardiorespiratory fitness parameters determined in the laboratory. Furthermore, the mean HR decreased after the first stage and remained constant during the following stages independent of the decreased muscle strength. We interpret these data to mean that performance differences were a result of insufficient recovery after the first day of multistage mountain running and the different individual pacing strategies. It is worth mentioning that also other factors, not determined in this investigation, could be responsible for the present outcomes (e.g., nutrition, genetics, psychological and environmental factors, or different training programs).