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

Power Profile during Cycling in World Triathlon Series and Olympic Games

This study aimed to analyze the power profile (PP) during the cycling segment of international-level triathletes in the World Triathlon Series (WTS) and Olympics and to evaluate the influence of circuit type, race distance (Sprint or Olympic distance) and race dynamics on the development of the cycling leg and the final race position. Four male triathletes participated in the study. Twenty races were analyzed using geolocation technology and power-meter data to analyze PP, race dynamics, and course characteristics. Before the races, incremental tests of volitional exhaustion with gas analysis were performed to determine power intensity zones. Nonparametric Mann-Whitney U tests and correlation analyses were conducted to identify differences and relationships between various variables. A correlation between the time spent above maximal aerobic power (MAP) and dangerous curves per kilometer (r = 0.46; p < 0.05) and bike split result (BSR) (r = -0.50; p < 0.05) was observed. Also, moderate correlation was found between BSR and the final race position (r = 0.46; p < 0.01). No differences were found between sprint and Olympic distance races in any variable. Power output variability, influenced by technical circuit segments, remains the main characteristic in international short-distance races. The results of the present study suggest that the triathletes who are better adapted to intermittent high intensity efforts perform better cycling legs at international high-level races.

Work, Training and Life Stress in ITU World Olympic Distance Age-Group Championship Triathletes

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.

Discovering the sluggishness of triathlon running - using the attractor method to quantify the impact of the bike-run transition

Running in a triathlon, a so-called brick run, is uniquely influenced by accumulated load from its preceding disciplines. Crucially, however, and irrespective of race type, the demands of a triathlon always exceed the sum of its parts. Triathletes of all levels commonly report subjectively perceived incoordination within the initial stages of the cycle run transition (T2). Although minimizing it, and its influence on running kinematics, can positively impact running and overall triathlon performance, the mechanisms behind the T2 effect remain unclear. In the present study, we assessed the influence of the pre-load exercise mode focusing on the biomechanical perspective. To analyze inertial sensor-based raw data from both legs, the so-called Attractor Method was applied. The latter represents a sensitive approach, allowing to quantify subtle changes of cyclic motions to uncover the transient effect, a potentially detrimental transient phase at the beginning of a run. The purpose was to analyze the impact of a pre-load on the biomechanics of a brick run during a simulated Olympic Distance triathlon (without the swimming section). Therefore, we assessed the influence of pre-load exercise mode on running pattern (δM) and precision (δD), and on the length of the transient effect (t_T) within a 10 km field-based run in 22 well-trained triathletes. We found that δD, but not δM, differed significantly between an isolated run (I_Run) and when it was preceded by a 40 km cycle (T_Run) or an energetically matched run (R_Run). The average distance ran until overcoming the transient phase (t_T) was 679 m for T_Run, 450 m for R_Run, and 29 4 m for I_Run. The results demonstrated that especially the first kilometer of a triathlon run is prone to an uncoordinated running sensation, which is also commonly reported by athletes. That is, i) the T2 effect appeared more linked to variability in running style than to running style per se ii) run t_T distance was influenced by preceding exercise load mode, being greater for a T_Run than for the R_Run condition, and iii) the Attractor Method seemed to be a potentially promising method of sensitively monitoring T2 adaptation under ecologically valid conditions.

Does the Physiological Response of a Triathlete Change in the Use or Absence of Drafting?

Background: Currently, tactics play an important and decisive role in sprint distance triathlons. One of the most decisive tactical elements is drafting in the cycling sector, depending on whether or not it is allowed by the test regulations. The objective was to analyze the physiological responses in running, in relation to drafting in the cycling sector, according to level and sex. Methods: To do this, a total of n = 44 subjects were divided into two levels (elite: they got a podium in the national championship, 15.68 ± 0.82 years; amateurs: they compete at the regional level, 15.68 ± 1.62 and 37.9 ± 1.74 years), undergoing two training sessions of four cycling-running multitransitions with variability in the permissibility of drafting were analyzed. A descriptive analysis of the variables was carried out, together with an inferential analysis to know the relationships and associations between the dependent and independent variables. Results: The results showed significant differences in the parameters, as related to running technique, heart rate, speed, and displacement (both between levels and sex). Conclusions: This study concludes that drafting in the cycling sector generates decisive physiological responses for the running sector.

The completely recover of quadriceps muscle peripheral fatigue after running in Olympic but not in Sprint triathlon

ABSTRACTThis study compared central and peripheral fatigue development between Sprint and Olympic distance triathlon. Fifteen male triathletes performed Sprint and Olympic triathlon simulations in a randomized and counterbalanced order. Central and peripheral fatigue was evaluated from changes in voluntary activation level (VAL) and twitch responses of quadriceps muscle (Q_tw,pot), respectively. Q_tw,pot reduced from baseline to post-swimming similarly between triathlon simulations (Sprint, -17±11%; Olympic, -13±9%). In post-cycling, Q_tw,pot further declined to a similar extent between triathlon distances (Sprint, -31±15%; Olympic, -28±11%). In post-running, Q_tw,pot was fully recovered in Olympic triathlon (-4±10%), whereas there was only a partial recovery of Q_tw,pot in Sprint triathlon (-20±11%). VAL was not reduced in post-swimming, but reduction was similar between triathlon distances in post-cycling (Sprint, -10±9%; Olympic, -8±8%) and post-running (Sprint, -15±14%; Olympic, -16±8%). In Sprint triathlon, the swimming speed (1.07±0.13 m ·s^-1) was above (p<.001) critical speed (1.01±0.14 m ·s^-1), the cycling power (179.7±27.2W) was below the respiratory compensation point (216.3±27.8W, p<.001) and running speed (13.7±1.05km·h^-1) similar to the respiratory compensation point (13.2±0.70 km·h^-1, p=.124). In Olympic triathlon, swimming speed (1.03±0.13m·s^-1) was similar to critical speed (p=.392), and both cycling power (165.3±27.3W) and running speed (12.6±1.05km·h^-1) were below the respiratory compensation point (p≤.007). In conclusion, peripheral fatigue progressed until post-cycling regardless of triathlon distances. However, peripheral fatigue was fully recovered after running in Olympic but not in Sprint triathlon. The central fatigue started in post-cycling and progressed until post-running regardless of triathlon distances.

Transferability of Cardiopulmonary Parameters between Treadmill and Cycle Ergometer Testing in Male Triathletes—Prediction Formulae

Cardiopulmonary exercise testing (CPET) on a treadmill (TE) or cycle ergometry (CE) is a common method in sports diagnostics to assess athletes’ aerobic fitness and prescribe training. In a triathlon, the gold standard is performing both CE and TE CPET. The purpose of this research was to create models using CPET results from one modality to predict results for the other modality. A total of 152 male triathletes (age = 38.20 ± 9.53 year; BMI = 23.97 ± 2.10 kg·m⁻²) underwent CPET on TE and CE, preceded by body composition (BC) analysis. Speed, power, heart rate (HR), oxygen uptake (VO₂), respiratory exchange ratio (RER), ventilation (VE), respiratory frequency (fR), blood lactate concentration (LA) (at the anaerobic threshold (AT)), respiratory compensation point (RCP), and maximum exertion were measured. Random forests (RF) were used to find the variables with the highest importance, which were selected for multiple linear regression (MLR) models. Based on R² and RF variable selection, MLR equations in full, simplified, and the most simplified forms were created for VO_2AT, HR_AT, VO_2RCP, HR_RCP, VO_2max, and HR_max for CE (R² = 0.46–0.78) and TE (R² = 0.59–0.80). By inputting only HR and power/speed into the RF, MLR models for practical HR calculation on TE and CE (both R² = 0.41–0.75) were created. BC had a significant impact on the majority of CPET parameters. CPET parameters can be accurately predicted between CE and TE testing. Maximal parameters are more predictable than submaximal. Only HR and speed/power from one testing modality could be used to predict HR for another. Created equations, combined with BC analysis, could be used as a method of choice in comprehensive sports diagnostics.

The Training Characteristics of Recreational-Level Triathletes: Influence on Fatigue and Health

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 the Daily Analysis of Life Demands Questionnaire (DALDA), the Training Distress Scale (TDS) and the Alberta Swim Fatigue and Health Questionnaire weekly. The Recovery-Stress Questionnaire (REST-Q) was completed at the beginning of the study, on the day before the competition, and at the end of week 8. Training loads were calculated using session-based rating of perceived exertion (sRPE). The data from every week of training was compared to week 1 to determine how athletes’ training and health changed throughout the study. No changes in training loads, duration or training intensity distribution were seen in the weeks leading up to the competition. Training duration was significantly reduced in week 6 (p = 0.041, d = 1.58, 95% CI = 6.9, 421.9), while the number of sessions was reduced in week 6 (Z = 2.32, p = 0.02, ES = 0.88) and week 7 (Z = 2.31, p = 0.02, ES = 0.87). Training was characterized by large weekly variations in training loads and a high training intensity. No significant changes were seen in the DALDA, TDS or REST-Q questionnaire scores throughout the 8 weeks. Despite large spikes in training load and a high overall training intensity, these recreational-level triathletes were able to maintain their health in the 6 weeks of training prior to an Olympic distance triathlon.