Anaerobic Power Vertical Jump Margaria Kalamen Wingate What are we trying to measure? Two Anaerobic Systems 1-ATP – CP Energy System – Immediate Energy system – Free ATP.

Download Report

Transcript Anaerobic Power Vertical Jump Margaria Kalamen Wingate What are we trying to measure? Two Anaerobic Systems 1-ATP – CP Energy System – Immediate Energy system – Free ATP.

Anaerobic Power

Vertical Jump Margaria Kalamen Wingate

What are we trying to measure?

Two Anaerobic Systems 1-ATP – CP Energy System – Immediate Energy system – Free ATP in the muscles – Rephosphorylization of ADP by PCr 2-Glycolysis – Short Term Energy System

Physiological Definitions

Anaerobic Power:

– concept: production of energy (ATP) per unit time – measured value: mechanical power during short duration maximal exercise

Remember...

Work:

A force applied over a distance (F x d) also the area under a curve of power vs. time (P x t)

Power:

Work per unit time (W/t)

Subcategories of Anaerobic Power • Peak – The highest value reached – Must be measured over a very short time duration ( ≤ 5s) • Mean/Average – The mean is the average power value over the entire duration of the test – Sometimes referred to as anaerobic capacity – In the case of the vertical jump the mean and average have specific and different meanings • Mean – the total work of the jump divided by the time to reach the maximum height • Average – the average power while the muscles are exerting force

More Physiological Definitions

Fatigue Index

– Concept: Measures endurance during short duration high intensity exercise – Measured: the rate of decrease in power over a period of time

• •

Relative vs. Absolute Measures

Relative Measurements:

– Measurements standardized by dividing by body mass – Typically done for measurements that depend on muscle mass – Relative measures can be compared between people of different sizes and between men and women.

Absolute Measurements:

– Measurements not standardized by dividing by body mass – The term absolute is not necessary, but provides clarity when also dealing with relative measurements.

Ways to Examine These Energy Systems

• Vertical Jump • Margaria Kalamen • Wingate

Vertical Jump

• Variables – Mass of Subject – Height of Subject – Height of Jump • Procedure – 3 Trials – No stepping into the jump – Using arms tends to help • Calculations – Absolute Anaerobic Power (Mean & Average) – Absolute & Relative Peak Anaerobic Power

Margaria Kalamen

• Variables – Mass of Subject – Height of Stairs – Time between Stairs • Procedure – Run up six stairs two at a time – Start time on the 2nd step end on the 6th • Calculations – Absolute & Relative Anaerobic Power

Wingate

• Variables – Mass of Subject – Mass of Load – Number of Pedal Revolutions in 5 s Periods for 30 s • Procedure – Subject Pedals as fast as possible with no load for ~ 5-10s – Subject Pedals as fast as possible for 30 s with load • Calculations – Peak Anaerobic Power (absolute and relative) – Fatigue Index – Total Work

Success of Measurements in Studying the Anaerobic Systems • All tests are measures of performance • Variations in these particular tests may have a lot to do with muscular attributes that are not related to energy production • Variables that have the same name are measures of the same concepts, but not the same actual values

Problems with Performance Measures • Daily variance • Motivation • Learning effect • Not a direct measurement of physiological variables • Relationships to physiological variables (and other performance tests) must be determined and the accuracy of prediction can then be found

Relationships

• The relationship between two variables can be easily determined by fitting a line to a graph of the variables • The goodness of fit is described by a value called the correlation (R) • R 2 tells the percentage of the variance in the dependent variable that can be explained by the independent variable

Correlations

• R 2 • R 2 = 1 is a perfect relationship = 0 means there is no relationship • The level of acceptability in between 0 and 1 depends on the specific instance • For predictive success we will use the following criteria – R 2 > 0.9 is very good – 0.8 < R 2 < 0.9 is good – 0.7 < R 2 < 0.8 is adequate – R 2 < 0.7 is poor