2017
DOI: 10.1123/ijspp.2016-0026
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A Computer Model of Drafting Effects on Collective Behavior in Elite 10,000-m Runners

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Cited by 3 publications
(3 citation statements)
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“…Additionally, to identify the particular contribution of different variables in elite middle- and long-distance running races, mathematical models should be generated. For example, Trenchard et al 60 modelled the influence of competitors on the collective behavior of competitors in a 10,000 m elite race and concluded that behaviors cannot be fully explained through drafting effects and that psychological processes are therefore involved in the mechanisms underpinning collective behavior. A potential advantage of this method is that it allows greater isolation and control of individual variables, as well as the running of large numbers of simulations.…”
Section: Further Researchmentioning
confidence: 99%
“…Additionally, to identify the particular contribution of different variables in elite middle- and long-distance running races, mathematical models should be generated. For example, Trenchard et al 60 modelled the influence of competitors on the collective behavior of competitors in a 10,000 m elite race and concluded that behaviors cannot be fully explained through drafting effects and that psychological processes are therefore involved in the mechanisms underpinning collective behavior. A potential advantage of this method is that it allows greater isolation and control of individual variables, as well as the running of large numbers of simulations.…”
Section: Further Researchmentioning
confidence: 99%
“…In running however, the energetic savings are smaller and may have less influence on behaviors. In a study that used computer modeling to simulate the effect of three different drafting quantities (i) no drafting benefit, (ii) realistic (8%) runner drafting, and (iii) unrealistic (35%) ‘cycle’ drafting, Trenchard et al (2017) found drafting had minimal impact on three measures of collective behavior. A realistic 8% benefit resulted in significant, but small, increases in speed in a simulated 10000 m running race, but no effect on Runner Conversion Ratio (the drafting benefit experienced by the follower in a pair) or distance between the leading and last placed runner.…”
Section: Emergent Human Behavior In Group Environmentsmentioning
confidence: 99%
“…Although physiologically less able athletes may be able to engage with others early in a race, over time accumulated physiological disruption would reduce the number of behavioral options available. We consider that this represents a limitation of some largely ‘physical’ modeling studies (e.g., Trenchard, 2015 ; Trenchard et al, 2017 ) which utilize rather crude measures of physiological capacity, and incorporate no psychological variables.…”
Section: Research Implicationsmentioning
confidence: 99%