title: Lunge performance and its determinants.
abstract: For activities such as squash, badminton and fencing, the ability to quickly complete a lunge and return to the start or move off in another direction is critical for success. Determining which strength qualities are important predictors of lunge performance was the focus of this study. Thirty-one male athletes performed: (1) a unilateral maximal squat (one-repetition maximum, 1-RM) and unilateral jump squat (50% 1-RM) on an instrumented supine squat machine, and (2) a forward lunge while attached to a linear transducer. We performed stepwise multiple regression analysis with lunge performance as the dependent variable and various strength, flexibility and anthropometric measures as the independent variables. From the many strength and power measures calculated, time to peak force was the best single predictor of lunge performance, which accounted for 55% of the explained variance. The best three-variable model for predicting lunge performance accounted for 76-85% of the explained variance. The models differed, however, according to whether lunge performance was expressed relative to body mass (time to peak force, mean power and relative strength = 76%) or taken as an absolute value (time to peak force, leg length and flexibility = 85%). We conclude that one to two trials were reliable for strength diagnosis and that one strength measure cannot accurately explain functional performance because other factors, such as body mass, flexibility and leg length, have diverse effects on the statistical models.
authors.affiliation: Sport Performance Research Centre, School of Physiotherapy, Auckland University of Technology, Auckland, New Zealand. john.cronin@aut.ac.nz
authors.forename: John
authors.initials: J
authors.lastname: Cronin
authors.forename: Peter J
authors.initials: PJ
authors.lastname: McNair
authors.forename: Robert N
authors.initials: RN
authors.lastname: Marshall
mesh_terms: D000328:Adult; D000465:Algorithms; D001696:Biomechanical Phenomena; D006801:Humans; D007866:Leg / Q000502:physiology*; D008297:Male; D015233:Models, Statistical; D009068:Movement / Q000502:physiology*; D018482:Muscle, Skeletal / Q000502:physiology*; D012044:Regression Analysis; D015203:Reproducibility of Results; D013177:Sports / Q000502:physiology; D013647:Task Performance and Analysis; D014159:Transducers