Variables that influence Ironman triathlon performance &amp;ndash; what changed in the last 35 years?

Knechtle, Beat; Knechtle, Raphael; Stiefel, Michael F.; Zingg, Matthias Alexander; Rosemann, Thomas; Rüst, Christoph Alexander

doi:10.2147/oajsm.s85310

Cited by 31 publications

(25 citation statements)

References 72 publications

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“…However, anthropometric characteristics such as body height and limb length were not investigated in Ironman triathletes ( Knechtle et al, 2010c ; Knechtle et al, 2010d ). Personal best marathon time is a strong predictor for Ironman triathlon race in both women and men ( Knechtle et al, 2015c ). Also in male marathoners, body fat and running speed during training was a strong predictive variable, not body height or limb length ( Barandun et al, 2012 ).…”

Section: Discussionmentioning

confidence: 99%

Sex differences in pacing during ‘Ultraman Hawaii’

Knechtle

Nikolaidis²

2016

PeerJ

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BackgroundTo date, little is known for pacing in ultra-endurance athletes competing in a non-stop event and in a multi-stage event, and especially, about pacing in a multi-stage event with different disciplines during the stages. Therefore, the aim of the present study was to examine the effect of age, sex and calendar year on triathlon performance and variation of performance by events (i.e., swimming, cycling 1, cycling 2 and running) in ‘Ultraman Hawaii’ held between 1983 and 2015.MethodsWithin each sex, participants were grouped in quartiles (i.e., Q1, Q2, Q3 and Q4) with Q1 being the fastest (i.e., lowest overall time) and Q4 the slowest (i.e., highest overall time). To compare performance among events (i.e., swimming, cycling 1, cycling 2 and running), race time in each event was converted in z score and this value was used for further analysis.ResultsA between-within subjects ANOVA showed a large sex × event (p = 0.015, η2 = 0.014) and a medium performance group × event interaction (p = 0.001, η2 = 0.012). No main effect of event on performance was observed (p = 0.174, η2 = 0.007). With regard to the sex × event interaction, three female performance groups (i.e., Q2, Q3 and Q4) increased race time from swimming to cycling 1, whereas only one male performance group (Q4) revealed a similar trend. From cycling 1 to cycling 2, the two slower female groups (Q3 and Q4) and the slowest male group (Q4) increased raced time. In women, the fastest group decreased (i.e., improved) race time from swimming to cycling 1 and thereafter, maintained performance, whereas in men, the fastest group decreased race time till cycling 2 and increased it in the running.ConclusionIn summary, women pace differently than men during ‘Ultraman Hawaii’ where the fastest women decreased performance on day 1 and could then maintain on day 2 and 3, whereas the fastest men worsened performance on day 1 and 2 but improved on day 3.

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Section: Discussionmentioning

confidence: 99%

Sex differences in pacing during ‘Ultraman Hawaii’

Knechtle

Nikolaidis²

2016

PeerJ

Self Cite

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“…Similarly, the values of maximum oxygen consumption in children and adolescents diff er between the sexes (Armstrong, Tomkinson & Ekelund, 2011). While in elite endurance sports (e.g., triathlon) there are no diff erences in training volume between men and women (Knechtle et al, 2015), younger and lower-level sportswomen (intercollegiate distance runners) train fewer miles per week and have fewer weekly sessions than their male counterparts do (Deaner, Lowen, Rogers, & Saksa, 2015).…”

Section: Introductionmentioning

confidence: 99%

Comparison of Training Volumes in Different Elite Sportspersons According to Sex, Age, and Sport Practised

Saavedra¹,

Þorgeirsson²,

Kristjánsdóttir³

et al. 2018

Monten. J. Sports Sci. Med.

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Training is a complex process that depends, among other factors, on the intensity and volume of training. Th e objective of this study was to analyse the volume of training in several sports as a function of sex and age. Th e study sample consisted of 302 sportspersons (men, n=132; women, n=170) who participated in the 16 th Games of the Small States of Europe (1st to 6th June 2015) in representing nine countries. Th e subjects practised the following sports: artistic gymnastics, athletics, basketball, beach volleyball, golf, judo, shooting, swimming, table tennis, tennis, and volleyball, and were classifi ed by sex, sport, and age (younger: ≤20 years; intermediate: from 21 to 30 years; older: ≥31 years). Th ey responded to fi ve questions about their training volume and the annual number of competitions in which they participated. A one-way ANOVA with a Bonferroni post hoc test was used to establish diff erences by sex, sport, and age group. Th ree-way ANOVAs (sex [men, women] × age [3 levels: younger, intermediate, older] × sport [11 sports]) were performed to determine any relationships between the variables. Neither interactions between the groups nor diff erences depending on sex were found in the training volumes, but the older the sportsperson, the lower the training volume (days per week, and total time per week). Th e sports with the greatest training volumes were artistic gymnastics and swimming, while those with the most competitions per year were basketball and volleyball.

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“…However, anthropometric characteristics such as body height and limb length were not investigated in Ironman triathletes (Knechtle et al 2010c(Knechtle et al , 2010d. Personal best marathon time is a strong predictor for Ironman triathlon race in both women and men (Knechtle et al 2015c). Also in male marathoners, body fat and running speed during training was a strong predictive variable, not body height or limb length (Barandun et al 2012).…”

Section: Discussionmentioning

confidence: 99%

Peer Review #1 of "Sex differences in pacing during ‘Ultraman Hawaii’ (v0.1)"

Behm¹

2016

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Background. To date, little is known for pacing in ultra-endurance athletes competing in a non-stop event and in a multi-stage event, and especially, about pacing in a multi-stage event with different disciplines during the stages. Therefore, the aim of the present study was to examine the effect of age, sex and calendaryear on triathlon performance and variation of performance by events (i.e. swimming, cycling 1, cycling2 and running) in 'Ultraman Hawaii' held between 1983 and 2015. Methods. Within each sex, participants were grouped in quartiles (i.e. Q1, Q2, Q3 and Q4) with Q1 being the fastest (i.e. lowest overall time) and Q4 the slowest (i.e. highest overall time). To compare performance among events (i.e. swimming, cycling 1, cycling 2 and running), race time in each event was converted in z score and this value was used for further analysis. Results. A between-within subjects ANOVA showed a large sex×event (p=0.015, η 2 =0.014) and a medium performance group×event interaction (p=0.001, η 2 =0.012). No main effect of event on performance was observed (p=0.174, η 2 =0.007). With regards to the sex×event interaction, three female performance groups (i.e. Q2, Q3 and Q4) increased race time from swimming to cycling 1, whereas only one male performance group (Q4) revealed a similar trend. From cycling 1 to cycling 2, the two slower female groups (Q3 and Q4) and the slowest male group (Q4) increased raced time. In women, the fastest group decreased (i.e. improved) race time from swimming to cycling 1 and thereafter, maintained performance, whereas in men, the fastest group decreased race time till cycling 2 and increased it in the running. Conclusion. In summary, women pace differently than men during 'Ultraman Hawaii' where the fastest women decreased performance on day 1 and could then maintain on day 2 and 3, whereas the fastest men worsened performance on day 1 and 2 but improved on day 3.

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Variables that influence Ironman triathlon performance – what changed in the last 35 years?

Cited by 31 publications

References 72 publications

Sex differences in pacing during ‘Ultraman Hawaii’

Sex differences in pacing during ‘Ultraman Hawaii’

Comparison of Training Volumes in Different Elite Sportspersons According to Sex, Age, and Sport Practised

Peer Review #1 of "Sex differences in pacing during ‘Ultraman Hawaii’ (v0.1)"

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