title: Modelling the determinants of 2000 m rowing ergometer performance: a proportional, curvilinear allometric approach.
abstract: Previous studies have investigated the determinants of indoor rowing using correlations and linear regression. However, the power demands of ergometer rowing are proportional to the cube of the flywheel's (and boat's) speed. A rower's speed, therefore, should be proportional to the cube root (0.33) of power expended. Hence, the purpose of the present study was to explore the relationship between 2000 m indoor rowing speed and various measures of power of 76 elite rowers using proportional, curvilinear allometric models. The best single predictor of 2000 m rowing ergometer performance was power at VO(2max)(WVO(2max))(0.28), that explained R(2)=95.3% in rowing speed. The model realistically describes the greater increment in power required to improve a rower's performance by the same amount at higher speeds compared with that at slower speeds. Furthermore, the fitted exponent, 0.28 (95% confidence interval 0.226-0.334) encompasses 0.33, supporting the assumption that rowing speed is proportional to the cube root of power expended. Despite an R(2)=95.3%, the initial model was unable to explain "sex" and "weight-class" differences in rowing performances. By incorporating anaerobic as well as aerobic determinants, the resulting curvilinear allometric model was common to all rowers, irrespective of sex and weight class.
authors.affiliation: Department of Sports Studies, University of Wolverhampton, Walsall, UK. a.m.nevill@wlv.ac.uk
authors.forename: A M
authors.initials: AM
authors.lastname: Nevill
authors.forename: S V
authors.initials: SV
authors.lastname: Allen
authors.forename: S A
authors.initials: SA
authors.lastname: Ingham
mesh_terms: D000328:Adult; D000332:Aerobiosis; D000704:Analysis of Variance; D054874:Athletic Performance / Q000502:physiology*; D001823:Body Composition; D016001:Confidence Intervals; D016552:Ergometry / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D008954:Models, Biological; D010101:Oxygen Consumption / Q000502:physiology; D011659:Pulmonary Gas Exchange; D012044:Regression Analysis; D012767:Ships; D013177:Sports / Q000502:physiology*