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

作者：Novak Andrew R.; Bennett Kyle J. M.; Fransen Job; Dascombe Ben J.

来源：Journal of Sports Sciences, 2018, 36(1): 71-78.

DOI：10.1080/02640414.2017.1280611

• Cycling
• physiology
• power output
• decision-making

This study adopted a multidimensional approach to performance prediction within Olympic distance cross-country mountain biking (XCO-MTB). Twelve competitive XCO-MTB cyclists (VO(2)max 60.8 +/- 6.7mlkg(-1)min(-1)) completed an incremental cycling test, maximal hand grip strength test, cycling power profile (maximal efforts lasting 6-600s), decision-making test and an individual XCO-MTB time-trial (34.25km). 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 127.1s across 6246.8 +/- 452.0s (adjusted R-2=0.92; P<0.01). This model included VO(2)max relative to total cycling mass, maximal mean power across 5 and 30s, 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 R-2: 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.

• 出版日期2018