A multidimensional approach to performance prediction in Olympic distance cross-country mountain bikers

Novak, AR; Bennett, KJM; Fransen, J; Dascombe, BJ

A multidimensional approach to performance prediction in Olympic distance cross-country mountain bikers

Novak, AR

Bennett, KJM

Fransen, J

Dascombe, BJ

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Publication Type:: Journal Article
Citation:: Journal of Sports Sciences, 2018, 36 (1), pp. 71 - 78
Issue Date:: 2018-01-02

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Field	Value	Language
dc.contributor.author	Novak, AR https://orcid.org/0000-0002-2949-4150	en_US
dc.contributor.author	Bennett, KJM https://orcid.org/0000-0002-2288-4770	en_US
dc.contributor.author	Fransen, J https://orcid.org/0000-0003-3355-1848	en_US
dc.contributor.author	Dascombe, BJ	en_US
dc.date.issued	2018-01-02	en_US
dc.identifier.citation	Journal of Sports Sciences, 2018, 36 (1), pp. 71 - 78	en_US
dc.identifier.issn	0264-0414	en_US
dc.identifier.uri	http://hdl.handle.net/10453/94303
dc.description.abstract	© 2017 Informa UK Limited, trading as Taylor & Francis Group. This study adopted a multidimensional approach to performance prediction within Olympic distance cross-country mountain biking (XCO-MTB). Twelve competitive XCO-MTB cyclists (VO2max 60.8 ± 6.7 ml · kg−1 · min−1) completed an incremental cycling test, maximal hand grip strength test, cycling power profile (maximal efforts lasting 6–600 s), decision-making test and an individual XCO-MTB time-trial (34.25 km). A hierarchical approach using multiple linear regression analyses was used to develop predictive models of performance across 10 circuit subsections and the total time-trial. The strongest model to predict overall time-trial performance achieved prediction accuracy of 127.1 s across 6246.8 ± 452.0 s (adjusted R2 = 0.92; P < 0.01). This model included VO2max relative to total cycling mass, maximal mean power across 5 and 30 s, peak left hand grip strength, and response time for correct decisions in the decision-making task. A range of factors contributed to the models for each individual subsection of the circuit with varying predictive strength (adjusted R2: 0.62–0.97; P < 0.05). The high prediction accuracy for the total time-trial supports that a multidimensional approach should be taken to develop XCO-MTB performance. Additionally, individual models for circuit subsections may help guide training practices relative to the specific trail characteristics of various XCO-MTB circuits.	en_US
dc.relation.ispartof	Journal of Sports Sciences	en_US
dc.relation.isbasedon	10.1080/02640414.2017.1280611	en_US
dc.subject.classification	Sport Sciences	en_US
dc.subject.mesh	Humans	en_US
dc.subject.mesh	Exercise Test	en_US
dc.subject.mesh	Anthropometry	en_US
dc.subject.mesh	Hand Strength	en_US
dc.subject.mesh	Linear Models	en_US
dc.subject.mesh	Decision Making	en_US
dc.subject.mesh	Oxygen Consumption	en_US
dc.subject.mesh	Bicycling	en_US
dc.subject.mesh	Adult	en_US
dc.subject.mesh	Male	en_US
dc.subject.mesh	Athletic Performance	en_US
dc.title	A multidimensional approach to performance prediction in Olympic distance cross-country mountain bikers	en_US
dc.type	Journal Article
utslib.citation.volume	1	en_US
utslib.citation.volume	36	en_US
utslib.for	1106 Human Movement and Sports Sciences	en_US
utslib.for	1302 Curriculum and Pedagogy	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Health
pubs.organisational-group	/University of Technology Sydney/Faculty of Health/Sports and Exercise Science
pubs.organisational-group	/University of Technology Sydney/Strength - CHSP - Health Services and Practice
utslib.copyright.status	closed_access
pubs.issue	1	en_US
pubs.publication-status	Published	en_US
pubs.volume	36	en_US

Abstract:

© 2017 Informa UK Limited, trading as Taylor & Francis Group. This study adopted a multidimensional approach to performance prediction within Olympic distance cross-country mountain biking (XCO-MTB). Twelve competitive XCO-MTB cyclists (VO2max 60.8 ± 6.7 ml · kg−1 · min−1) completed an incremental cycling test, maximal hand grip strength test, cycling power profile (maximal efforts lasting 6–600 s), decision-making test and an individual XCO-MTB time-trial (34.25 km). A hierarchical approach using multiple linear regression analyses was used to develop predictive models of performance across 10 circuit subsections and the total time-trial. The strongest model to predict overall time-trial performance achieved prediction accuracy of 127.1 s across 6246.8 ± 452.0 s (adjusted R2 = 0.92; P < 0.01). This model included VO2max relative to total cycling mass, maximal mean power across 5 and 30 s, peak left hand grip strength, and response time for correct decisions in the decision-making task. A range of factors contributed to the models for each individual subsection of the circuit with varying predictive strength (adjusted R2: 0.62–0.97; P < 0.05). The high prediction accuracy for the total time-trial supports that a multidimensional approach should be taken to develop XCO-MTB performance. Additionally, individual models for circuit subsections may help guide training practices relative to the specific trail characteristics of various XCO-MTB circuits.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/94303