title: Physical Predictors of Elite Skeleton Start Performance.
abstract: OBJECTIVE
  An extensive battery of physical tests is typically employed to evaluate athletic status and/or development, often resulting in a multitude of output variables. The authors aimed to identify independent physical predictors of elite skeleton start performance to overcome the general problem of practitioners employing multiple tests with little knowledge of their predictive utility.
  
  
  METHODS
  Multiple 2-d testing sessions were undertaken by 13 high-level skeleton athletes across a 24-wk training season and consisted of flexibility, dry-land push-track, sprint, countermovement-jump, and leg-press tests. To reduce the large number of output variables to independent factors, principal-component analysis (PCA) was conducted. The variable most strongly correlated to each component was entered into a stepwise multiple-regression analysis, and K-fold validation assessed model stability.
  
  
  RESULTS
  PCA revealed 3 components underlying the physical variables: sprint ability, lower-limb power, and strength-power characteristics. Three variables that represented these components (unresisted 15-m sprint time, 0-kg jump height, and leg-press force at peak power, respectively) significantly contributed (P < .01) to the prediction (R2= .86, 1.52% standard error of estimate) of start performance (15-m sled velocity). Finally, the K-fold validation revealed the model to be stable (predicted vs actual R2= .77; 1.97% standard error of estimate).
  
  
  CONCLUSIONS
  Only 3 physical-test scores were needed to obtain a valid and stable prediction of skeleton start ability. This method of isolating independent physical variables underlying performance could improve the validity and efficiency of athlete monitoring, potentially benefitting sport scientists, coaches, and athletes alike.
authors.forename: Steffi L
authors.initials: SL
authors.lastname: Colyer
authors.forename: Keith A
authors.initials: KA
authors.lastname: Stokes
authors.forename: James L J
authors.initials: JL
authors.lastname: Bilzon
authors.forename: Marco
authors.initials: M
authors.lastname: Cardinale
authors.forename: Aki I T
authors.initials: AI
authors.lastname: Salo
mesh_terms: D054874:Athletic Performance / Q000502:physiology*; D005080:Exercise Test / Q000379:methods*; D005260:Female; D006801:Humans; D035002:Lower Extremity / Q000502:physiology; D008297:Male; D053580:Muscle Strength / Q000502:physiology; D064797:Physical Conditioning, Human / Q000379:methods; D059385:Plyometric Exercise; D025341:Principal Component Analysis; D012044:Regression Analysis; D055070:Resistance Training / Q000379:methods; D013177:Sports / Q000502:physiology*; D055815:Young Adult
keywords: PCA; athletes; multivariate; principal-component analysis; testing; validation