Using field based power meter data to model track cycling performance.
| dc.contributor.author | Ferguson, Hamish | |
| dc.date.accessioned | 2024-03-21T21:37:36Z | |
| dc.date.available | 2024-03-21T21:37:36Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | Track cycling events, both sprint and endurance, are primarily focused on performance of high and medium power durations, and it is suggested, measures of peak power govern performance in the sprint and pursuit cycling events. Various tests and metrics in the laboratory have been used to try and model track cycling. With the advent of power meters cyclists have been able to record power output in the field and several basic tests have evolved to use as a means to get started with training and racing with power. This thesis proposes a linear model based on total least squares regression, to evaluate these models and provide an option for coaches to see what durations are key for performance, and for sprint cyclists what types of training should be performed at a given part of a training build up. This analysis is applied to sprint cycling, male and female sprint cyclists, and pursuit cyclists to evaluate field-based data compared to lab and model derived metrics. The key conclusions from this thesis are: 1. For each specific power duration along the hyperbolic power-duration curve shows field-based data offers a better model for both sprint and pursuit durations. The linear model has a parabolic relationship the closer the inputs get to the specific duration assessed. 2. This disproves the contention of a linear process governed by peak power being the key metric of sprint cycling. The data in this thesis shows not only is this relationship incorrect, but strong relationships with sprint cycling durations hold for durations as long as 20-min. 3. This thesis finds there are sex differences for the model showing women have a higher variation of sprint power than men. 4. The linear model is applied to track endurance cycling to show, again, how a peak power (or maximal sprinting power or 𝑉̇O2max) does not govern performance, more a broad base of capacity reflected by a high lactate threshold, ventilatory threshold, critical power or other estimates of the maximal metabolic steady state. 5. Based on an understanding of the importance of capacity as well as peak power Chapter 6 shows this information can successfully be applied to the performance of sprint cyclists training towards peak performance. | |
| dc.identifier.uri | https://hdl.handle.net/10092/106832 | |
| dc.identifier.uri | https://doi.org/10.26021/15253 | |
| dc.language | English | |
| dc.language.iso | en | |
| dc.rights | All Right Reserved | |
| dc.rights.uri | https://canterbury.libguides.com/rights/theses | |
| dc.title | Using field based power meter data to model track cycling performance. | |
| dc.type | Theses / Dissertations | |
| thesis.degree.discipline | Mechanical Engineering | |
| thesis.degree.grantor | University of Canterbury | |
| thesis.degree.level | Doctoral | |
| thesis.degree.name | Doctor of Philosophy | |
| uc.college | Faculty of Engineering |
Files
License bundle
1 - 1 of 1
No Thumbnail Available
- Name:
- license.txt
- Size:
- 1.71 KB
- Format:
- Item-specific license agreed upon to submission
- Description: