Pacing Variation in Multistage Ultramarathons: Internet-Based Cross-Sectional Study.

BACKGROUND: Ultramarathon running is the most popular ultraendurance competition in terms of the number of races and runners competing annually worldwide; however, no study has compared pacing and performance over a long period. OBJECTIVE: This study analyzes the pacing of successful finishers and nonfinishers in multistage ultramarathons worldwide. METHODS: A total of 4079 athletes (men=3288; women=791) competing in 99 multistage ultramarathon events from 1983 to 2021 were analyzed, including the number of participants, age, gender, rank, and running speed of successful finishers. RESULTS: The results showed a significant increase in the number of events (n=338) and a significant increase in the number of finishers and nonfinishers (n=5575) in the ultramarathons worldwide during this period. The general linear models (GLMs) of pacing variation showed nonsignificant effects for gender (F1,36.2=2.5; P=.127; ηp2=0.063) and age group (F10,10=0.6; P=.798; ηp2=0.367), but it showed a significant interaction (gender × age) effect (F10,2689=2.3; P=.008; ηp2=0.009). Post hoc analyses showed that men have a higher pacing variation than women in the under 30 years (U30), U35, U45, and U50 groups. Additionally, the fastest women's age group (U35) had the lowest pacing variation. The GLM of pacing variation by gender and event distance showed significant effects for both gender (F1,3=18.5; P<.001; ηp2=0.007) and distance (F2,3=20.1; P<.001; ηp2=0.015). Post hoc analyses showed a growing pacing variation with increasing race distance for both men and women. In addition, men had a higher variation in long events. Furthermore, there was a significant main effect for both genders (F1,3=33.7; P<.001; ηp2=0.012) and rank (F1,3=136.6; P<.001; ηp2=0.048) on performance, with men being faster than women. Pacing varied greatly due to gender (F1,3=4.0; P=.047; ηp2=0.001), with a lower (ie, more even) pacing variation for male athletes in the top 3 finishers. Male nonfinishers showed a higher performance than female nonfinishers (F1,1340=25.6; P<.001), and no difference was identified for pacing variation (F1,789=1.5; P=.228) based on gender. In addition, a weak but significant correlation (r=-0.130; P<.001) was identified between the average running speed and pacing variation for both female and male nonfinishers. CONCLUSIONS: In summary, multistage ultramarathon competitions showed an increasing number of competitors and a higher performance challenge. Men have a higher pacing (ie, less even) variation than women, especially observed in longer events. A higher pacing variation was associated with lower performance for men, women, and nonfinishers.

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.

Pacing in World-Class Age Group Swimmers in 100 and 200 m Freestyle, Backstroke, Breaststroke, and Butterfly.

Pacing in swimming has been investigated in pool swimming for elite-standard and age group freestyle swimmers, but little is known about pacing in age group swimmers competing at world class level in backstroke, breaststroke, and butterfly. The aim of this study was to investigate pacing for age group swimmers competing at world class level in 100 and 200 m in the four single disciplines (freestyle, backstroke, breaststroke and butterfly). Data on 18,187 unique finishers competing in four FINA Master World Championships between 2014 and 2019 were analyzed. The sample included 3334 women and 14,853 men. Swimming speed decreased with increasing age (p < 0.05). Freestyle was the fastest and breaststroke the slowest (p < 0.05) stroke. Women and men were faster in 100 m (p < 0.05) than in 200 m. Backstroke was the stroke with the lowest and butterfly with the highest coefficient of variation in swimming speed. One hundred meters had a higher coefficient of variation in swimming speed than breaststroke (p < 0.05). For 100 m, swimming speed decreased for all strokes and all age groups during the second lap. For 200 m, swimming speed was the fastest for all strokes and all age groups during the first lap. In summary, the FINA World Masters Championships presented the unique characteristic that, when all competitors were considered, (i) swimming speed decreased with increasing age, (ii) women and men were faster in 100 m than in 200 m, (iii) freestyle was the fastest stroke and (iv) the largest increase in swimming time for 100 m all strokes and all age groups occurred during the second (out of two) lap and for 200 m, swimming speed was the fastest for all strokes and age groups during the first lap. These findings should help coaches to develop age- and event-tailored pacing strategies.

Pacing in World-Class Age Group Swimmers in 200 and 400 m Individual Medley.

The present research investigated pacing for world-class age group swimmers competing in individual medley in 200 m and 400 m. Data on 3,242 unique finishers (1,475 women and 1,767 men) competing in four Master World Championships [XV FINA WMC held in Montreal (Canada) in 2014, the XVI FINA WMC held in Kazan (RUS) in 2015, the FINA WMC held in Budapest (HUN) in 2017, and the XVIII FINA WMC held in Gwangju (KOR] in 2019) were analyzed. Men were faster than women among all age groups in both 200 and 400 m. Additionally, differences were found between almost all adjacent age groups, with the exception (p > 0.05) of age groups 25-29 to 30-34, 35-39 to 40-44 years in 200 m races and 25-29 to 30-34, 30-34 to 35-39, 35-39 to 40-44, and 45-49 to 50-54 years in 400 m races. Men showed a higher pacing variation in 200 m among all male age groups and all female age groups up to 69 years. Pace-variation pairwise comparisons between men and women showed no consistencies throughout age groups, with the exception of a higher variation in men in age groups ≥55-year-old. Men were faster for all splits and strokes in both 200 and 400 m, and significant changes were identified for each split and stroke for both men and women in both 200 and 400 m. Front crawl (freestyle, 4th split) was the fastest butterfly (1st split), backstroke (2nd split), and breaststroke (3rd split). In summary, men were faster than women for all age groups in both 200 and 400 m. Men showed a higher pacing variation in 200 m in all age groups, where women had a higher variation in age groups up to 69 years. The fastest stroke for the final spurt was front crawl, followed by butterfly, backstroke, and breaststroke. Based on these findings, coaches should advise their master athletes to focus on the final spurt in both 200 and 400 m individual medley for a fast final race time.

Isometric Exercise with Large Muscle Mass Improves Redox Balance and Blood Pressure in Hypertensive Adults.

PURPOSE: The aim of this study was to investigate the hemodynamic, oxidative stress (OS), and nitric oxide (NO) responses to a submaximal isometric exercise session (IES) involving large muscle mass. METHODS: Fourteen hypertensive (HTG: age = 35.9 ± 8.1 yr, height = 1.73 ± 0.10 m, total body mass = 78.0 ± 15.8 kg) and 10 normotensive (NTG: age = 41.1 ± 9.4 yr, height = 1.71 ± 0.12 m, total body mass = 82.3 ± 22.4 kg) participants performed two experimental sessions in the leg press and bench press: (i) control session and (ii) 8 sets × 1 min contraction at 30% maximal voluntary isometric contraction with 2-min rest interval. Blood pressure (BP) was measured at rest and during 60 min postexercise. Blood samples were collected at rest, immediately after the session, and 60 min postexercise. NO was obtained through the Griess reaction method. OS parameters were analyzed using commercial kits. A repeated-measures ANOVA with Bonferroni post hoc test was used to analyze all dependent variables. RESULTS: A significant decrease in systolic BP was observed only for HTG at 45 and 60 min postexercise (baseline vs 45 min: P = 0.03, Δ% = 4.44%; vs 60 min: P = 0.018, Δ% = 5.58%). NO increased immediately postexercise only for HTG (P = 0.008, Δ% = 16.44%). Regarding OS parameters, thiobarbituric acid reactive substances presented a significant reduction 60 min after the IES for NTG and HTG; catalase increased in both groups. CONCLUSIONS: The data showed that only 8 min of IES with a large muscle mass elicits an elevated pro-oxidant activity leading to a greater NO bioavailability, increases antioxidant reaction, and consequently reduces BP in hypertensive patients.

Heart rate cost of running in track estimates velocity associated with maximal oxygen uptake.

BACKGROUND: Running velocity associated with VO2max (vVO2max) is a parameter widely used for exercise prescription and is related to endurance performance. However, the vVO2max determination usually requires a maximal effort test and equipped laboratory for expired gas analysis, what make difficulty its assessment. OBJECTIVE: We aimed to test the validity of a simple method of vVO2max prediction through the heart rate cost of running (HRC) in a submaximal 6-min running test, both in treadmill and in a 400-meter track. METHODS: Male recreational runners (n = 16; 30.3 ±â€¯8.0 years; VO2max of 46.2 ±â€¯3.2 ml·kg-1·min-1) randomly underwent an incremental test in treadmill with gas analysis, and a 3000-m time trial in a track, to determine vVO2max. Before every maximal test, participants also performed a submaximal 6-min running (~85% HRmax), both in the treadmill and in a track, to assess HRC (bpm-1m·min-1) by dividing the submaximal running velocity by its respective HR. The vVO2max (km·h-1) was predicted by dividing the HRmax (bpm)/HRC (bpm-1m·min-1). RESULTS: No differences were verified (p > .05) among vVO2max determined both in the treadmill (13.8 ±â€¯0.9 km·h-1) and track (13.6 ±â€¯0.9 km·h-1) to those predicted by the HRC method both in treadmill (13.5 ±â€¯0.8 km·h-1) and track (13.6 ±â€¯1.0 km·h-1). The vVO2max measured directly with expired gas analysis was highly correlated with vVO2max estimated through HRC in treadmill and track (p < .05). Additionally, the intraclass correlation coefficient (ICC) and Bland-Altman technique revealed good agreement and reliability classified with substantial agreement [ICC = 0.673 (95% CI 0.064-0.886; p = .019)] and almost perfect agreement [ICC = 0.870 (95% CI 0.628-0.955 p = .0001)] between methods to identify vVO2max, respectively. CONCLUSION: A submaximal 6-min exercise test protocol to assess HRC of running was considered valid to estimate vVO2max of recreational runners both in treadmill and outdoor track.