Cycling as the Best Sub-8-Hour Performance Predictor in Full Distance Triathlon

A study of triathletes' race strategies in different competition environments

What is known, sports performance is impacted by a variety of factors. While most people understand the importance of training, proper nutrition, and adequate rest, not as many recognize the impact of environmental factors on athletic performance. This paper investigates the race strategies of Chinese triathletes in different competition environments, with a focus on the performance of professional triathletes during the Olympic Distance Triathlon held in China between 2015 and 2021. Data from 984 athletes who competed in 26 races were analyzed to evaluate the sensitivity of the three splits of swimming, cycling, and running to overall triathlon performance under different temperature (low, normal, and high), altitude (low, normal, and high), and waters (sea, river, and still waters) conditions. Results show that the effects of the three split times on overall time vary across different environments. Cycling has the greatest impact on overall performance when the temperature is suitable (at low temperature, at normal temperature) and the altitude is suitable (at low altitude, at normal altitude). While running has the greatest impact in high-temperature and high-altitude environments. For female athletes, in river waters, swimming has a greater effect on overall performance than cycling, but less than running. These findings provide practical suggestions for athletes, coaches, and competition organizers to optimize training and race strategies based on specific environmental conditions.

Cycling is the most important predictive split discipline in professional Ironman® 70.3 triathletes

Introduction

Our study examined 16,611 records of professional triathletes from 163 Ironman® 70.3 races across 97 countries (2004-2020). The aim was to identify the most predictive discipline-swim, bike, or run-for overall race time.

Methods

We used correlation matrices to compare the dependent variable "finish time" with independent variables "swim time," "bike time," and "run time." This analysis was conducted separately for male and female athletes. Additionally, univariate and multiple linear regression models assessed the strength of these associations.

Results

The results indicated that "bike time" had the strongest correlation with finish time (0.85), followed by "run time" (0.75 for females, 0.82 for males) and "swim time" (0.46 for females, 0.63 for males). Regression models confirmed "bike time" as the strongest predictor of overall race time (R² = 0.8), with "run time" and "swim time" being less predictive.

Discussion

The study concludes that in Ironman 70.3 races, "bike time" is the most significant predictor of overall race performance for both sexes, suggesting a focus on cycling in training and competition strategies. It also highlights a smaller performance gap between genders in swimming than in cycling or running.

Performance and pacing of professional IRONMAN triathletes: the fastest IRONMAN World Championship ever-IRONMAN Hawaii 2022

Pacing during cycling and running in an IRONMAN triathlon has been investigated in only one study with elite IRONMAN triathletes. We have, however, no knowledge of how professional triathletes pace during an IRONMAN World Championship. To investigate the split-by-split speed, pacing strategies and pacing variability in professional female and male IRONMAN World Championship participants in the fastest IRONMAN World Championship ever in IRONMAN Hawaii 2022. For both cycling and running, 25 specific split times were recorded in each discipline. The best 30 men and 30 women overall were chosen from the official IRONMAN website database for further analysis. They were divided into three performance groups: Top 10, 11-20th place, and 21st-30th place. Mean speed, individual linear regressions with the corresponding correlation coefficients, and coefficient of variation were calculated to assess split-by-split speed, pacing strategies, and pacing variability, respectively. In both men's and women's cycling and running segments, the top ten participants exhibited faster split times compared to the slower performance groups. Notably, no discernible differences existed between the 11-20th and 21st-30th place in men's cycling and women's running times. Conversely, in men's running and women's cycling segments, those in the 11-20th place displayed quicker times than those in the 21st-30th place. In the cycling segment across all groups, men demonstrated a more negative pacing pattern (indicating an increase in speed), whereas women exhibited more consistent pacing. In the running segment, the top 10 men and all women's groups showcased relatively similar slightly positive pacing profiles. However, men ranking 11-20th and 21st-30th displayed more pronounced positive pacing strategies, implying a more significant decline in speed over time. In terms of cycling, the variability in pacing remained relatively consistent across the three performance groups. Conversely, during the running segment, the top ten male triathletes and those in the 11-20th place displayed lower pacing variability than their counterparts in the 21st-30th position place and all women's groups. In summary, performance and pacing were examined in professional male and female IRONMAN World Championship participants during IRONMAN Hawaii 2022. Top performers showed faster cycling and running split times, with differences in pacing strategies between sexes. The pacing was more consistent in cycling, while running pacing varied more, particularly among male triathletes in different performance groups.

Predicting overall performance in Ironman 70.3 age group triathletes through split disciplines

Knowing which discipline contributes most to a triathlon performance is important to plan race pacing properly. To date, we know that the running split is the most decisive discipline in the Olympic distance triathlon, and the cycling split is the most important discipline in the full-distance Ironman^® triathlon. However, we have no knowledge of the Ironman^® 70.3. This study intended to determine the most crucial discipline in age group athletes competing from 2004 to 2020 in a total of 787 Ironman^® 70.3 races. A total of 823,459 athletes (198,066 women and 625,393 men) from 240 different countries were analyzed and recorded in 5-year age groups, from 18 to 75 + years. Correlation analysis, multiple linear regression, and two-way ANOVA were applied, considering p < 0.05. No differences in the regression analysis between the contributions of the swimming, cycling, and running splits could be found for all age groups. However, the correlation analysis showed stronger associations of the cycling and running split times than the swimming split times with overall race times and a smaller difference in swimming performance between males and females in age groups 50 years and older. For age group triathletes competing in Ironman^® 70.3, running and cycling were more predictive than swimming for overall race performance. There was a progressive reduction in the performance gap between men and women aged 50 years and older. This information may aid triathletes and coaches in planning their race tactics in an Ironman^® 70.3 race.

The beginning of success: Performance trends and cut-off values for junior and the U23 triathlon categories

Background

This study sought to determine cut-off values for each triathlon discipline to achieve podium in Junior (short distance; 750 m swim, 20 km cycle and 5 km run) and U23 (standard/Olympic distance; 1.5 km swim, 40 km cycle and 10 km run) triathlon events. Additionally, we aimed to investigate which discipline has the largest relationship with overall Junior and U23 triathlon performance, and the effect of sex and time in performance trends.

Methods

We included all data from Junior and U23 official races (International Triathlon Federation; ITU) of Junior (n = 3,314 finishes) and U23 (n = 5,092 finishes) categories held from 1999 to 2018.

Results

Men were significantly faster than women in both Junior (11.13%) and U23 (12.28%) categories. Swimming and cycling times were faster in 2009-2018 than in the 1999-2008 decade for men (3.36%; 6.49%), women junior (6.50%; 7.09%), men (0.15%; 3.46%) and women U23 (1.61%; 3.31%) respectively. Cycling was the discipline with the greatest influence on overall triathlon performance in Junior and U23 categories, regardless of sex or rank position. The cut-off values for the Junior category were (men/women): swimming, 9.2/9.4 min; cycling, 31.9/38.2 min; running, 16.8/18.9 min. U23's cut-off values were (men/women): swim, 18.0/19.4 min, cycling: 63.4/70.1 min; run, 33.9/38.7 min.

Conclusion

Cycling was the discipline with the greatest influence on overall performance for both men and women in Junior and U23 categories. Moreover, swimming and cycling performances increased over the years for both sexes.

What Is the Best Discipline to Predict Overall Triathlon Performance? An Analysis of Sprint, Olympic, Ironman® 70.3, and Ironman® 140.6

Objective: To analyze the proportion of dedication in each triathlon discipline (swimming, cycling, and running) and the importance of each separate discipline to predict overall performance of elite triathletes across different triathlon distances.

Methods: Data from 2015 to 2020 (n = 16,667) from official races and athletes in Sprint, Olympic distance, IM 70.3 (Half-Ironman distance), and IM 140.6 (Full-Ironman distance) competitions were included. The proportion of each discipline was calculated individually and compared using general linear models by event distance, sex, and performance level. Automatic linear regression models were applied for each distance considering overall performance as the dependent variable.

Results: A within-distance analysis showed that the best predictor for Sprint is cycling, for Olympic is swimming, for IM 70.3 is cycling, and for IM 140.6 is running. A between-distance analysis revealed that swimming is a better predictor in Olympic distance than in other triathlon distances. Cycling is a poor predictor for overall performance in IM 140.6, and the importance of running to predict overall performance is the highest in IM 140.6 and diminishes with decreasing race distance.

Conclusion: Each discipline represents a different relative portion and importance to predict overall performance depending on the triathlon distance. Swimming is the most important predictor discipline in Sprint- and Olympic-distance triathlon, cycling in IM 70.3, and running in IM 140.6.

Cut-Off Values in the Prediction of Success in Olympic Distance Triathlon

Cut-off points and performance-related tools are needed for the development of the Olympic distance triathlon. The purposes of the present study were (i) to determine cut-off values to reach the top three positions in an Olympic distance triathlon; (ii) to identify which discipline present the highest influence on overall race performance and if it has changed over the decades. Data from 1989 to 2019 (n = 52,027) from all who have competed in an official Olympic distance triathlon events (World Triathlon Series and Olympics) were included. The cut-off value to achieve a top three position was calculated. Linear regressions were applied for performance trends overall and for the top three positions of each race. Men had cut-off values of: swimming = 19.5 min; cycling = 60.7 min; running = 34.1 min. Women's cut-off values were: swimming = 20.7 min; cycling = 71.6 min; running = 38.1 min. The running split seemed to be the most influential in overall race time regardless of rank position or sex. In conclusion, cut-offs were established, which can increase the chances of achieving a successful rank position in an Olympic triathlon. Cycling is the discipline with the least influence on overall performance for both men and women in the Olympic distance triathlon. This influence pattern has not changed in the last three decades.

Influence of a 2-km Swim on the Cycling Power-Duration Relationship in Triathletes

Rothschild, J, Sheard, AC, and Crocker, GH. Influence of a 2-km swim on the cycling power-duration relationship in triathletes. J Strength Cond Res XX(X): 000-000, 2020-Triathletes must cycle after swimming, and so, it is important to understand how cycling performance may be affected by prior swimming. Therefore, the purpose of this study was to determine the effects of a 2-km swim at a self-selected race-pace intensity on the cycling power-duration relationship. Eighteen trained triathletes (12 M, 6 F; 37.1 ± 10.6 years, V[Combining Dot Above]O2max 54.8 ± 10.1 ml·kg·min) performed two 3-minute all-out cycling tests (3MTs) on separate days with one 3 MT immediately after a 2-km swim (swim-bike [SB]) and one without prior swimming (bike-only [BO]). The power-duration relationship was expressed as the total work done (TWD) and subdivided into end-test power (EP) and work done above EP. To assess swimming intensity, heart rate (HR) was continuously monitored during the 2-km swim and blood lactate was assessed on completion of the swim. End-swim lactate was 4.2 ± 1.8 mM, and mean swimming HR was 147 ± 18 b·min. The 2-km swim decreased TWD during the 3MT by 6% (BO: 62.8 ± 12.7 kJ; SB: 58.9 ± 13.4 kJ; p = 0.001) though neither EP (BO: 281 ± 65 W; SB: 269 ± 68 W; p = 0.102) nor work done above EP (BO: 12.1 ± 3.8 kJ; SB: 10.5 ± 4.2 kJ; p = 0.096) differed between trials. In conclusion, TWD while cycling decreases after a 2-km race-pace swim. Results from this study suggest that triathletes should determine racing cycling power following a simulated race-pace swim.

Self-Selected Pacing During a World Record Attempt in 40 Ironman-Distance Triathlons in 40 Days

The present case study analyzed performance, pacing, and potential predictors in a self-paced world record attempt of a professional triathlete to finish 40 Ironman-distance triathlons within 40 days. Split times (i.e., swimming, cycling, running) and overall times, body weight, daily highest temperature, wind speed, energy expenditure, mean heart rate, and sleeping time were recorded. Non-linear regressions were applied to investigate changes in split and overall times across days. Multivariate regression analyses were performed to test which variables showed the greatest influence on the dependent variables cycling, running and overall time. The athlete completed the 40×Ironman distances in a total time of 444:22 h:min. He spent 50:26 h:min in swimming, 245:37 h:min in cycling, 137:17 h:min in running and 11:02 h:min in transition times. Swimming and cycling times became slower across days, whereas running times got faster until the 20th day and, thereafter, became slower until the 40th day. Overall times got slower until the 15th day, became faster to 31st, and started then to get slower until the end. Wind speed, previous day’s race time and average heart race during cycling were significant independent variables influencing cycling time. Body weight and average heart rate during running were significant independent variables influencing running performance. Cycling performance, running performance, and body weight were significant independent variables influencing overall time. In summary, running time was influenced by body weight, cycling by wind speed, and overall time by both running and cycling performances.

Ultra-triathlon-Pacing, performance trends, the role of nationality, and sex differences in finishers and non-finishers

Ultra-triathlons are defined as triathlons longer than the traditional Ironman distance and became more popular in the last two decades; however, scarce scientific evidence of these events are available. Therefore, we aimed to investigate the trends of performance, pacing, nationality, sex differences, and rate of non-finishers in ultra-triathlons. Data from 1985 to 2018 were collected including Double Iron, Triple Iron, Quintuple Iron, and Deca Iron ultra-triathlons. Different pacing patterns by event and sex were observed (P < .05); athletes spent less %time in swimming and cycling, and more %time in running as the distance of event was longer; women spent more %time in cycling and less% time in running in Double and Triple. Performance analysis showed a negative trend over time for men and women since 1985. Switzerland, France, and Germany were the fastest nations in ultra-triathlons. The frequency of North Americans competing in Europe was very low (<5%), whereas Europeans often competed in North America (~25%). The rate of non-finishers between sexes was similar in all races with the exception of Deca Iron ultra-triathlon, which was much greater (~20%) for women. Non-finishers had slower race times in swimming and cycling splits than finishers. In conclusion, ultra-triathletes should redistribute their energy among swimming, cycling, and running depending on their sex and distance of race. Performance in ultra-triathlons has been decreasing in men and women over the years, but sex difference in performance remained. Europeans were the fastest ultra-triathletes and compete in Europe and North America. Additionally, non-finishers were slower swimmers and cyclists than finishers.

Celebrating 40 Years of Ironman: How the Champions Perform

We aimed to determine which discipline had the greater performance improvements in the history of Ironman triathlon in Hawaii and also which discipline had the greater influence in overall race time. Data from 1983 to 2018 of the top three women and men of each year who competed in the Ironman World Championship were included. In addition to exploratory data analyses, linear regressions between split times and years of achievement were performed. Further, a stepwise multiple linear regression was applied using total race time as the dependent variable and split times as the independent variables. Both women and men significantly improved their performances from 1983 to 2018 in the Ironman World Championship. Swimming had the largest difference in improvements between men and women (3.0% versus 12.1%, respectively). A negative and significant decrease in each discipline was identified for both women and men, with cycling being the discipline with the greatest reduction. The results from the stepwise multiple regression indicated that cycling was the discipline with the highest influence on overall race time for both sexes. Based on the findings of this study, cycling seems to be the Ironman triathlon discipline that most improved overall race times and is also the discipline with the greatest influence on the overall race time of elite men and women in the Ironman World Championship.