Greig, M., & Naylor, J. (2014). Lower limb isokinetic strength parameters as predictors of agility performance. Medicine & Science in Sports & Exercise, 46(5), Supplement abstract number 3000.

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This study evaluated agility-task inter-test correlation and the predictive potential of lower-limb strength parameters in sub-elite games players (N = 19). Ss completed four agility tests, differentiating linear speed, prescriptive and reactive change of direction, and deceleration. Ss also completed isokinetic testing of the eccentric knee-flexors and concentric knee-extensors at speeds of 60, 180, and 300/s. Peak torque and respective joint angle were calculated for the eccentric knee flexors and concentric knee-extensors at each speed. Dynamic control ratios (eccentric knee-flexors to concentric knee-extensors ratios) and fast:slow ratios (300:60) were calculated using peak torque values. Those ratios were also calculated using angle-matched eccentric knee-flexor and concentric knee-extensor isokinetic data.

There was little evidence of inter-test correlation; the strongest correlation was between a 10-m sprint and T-test (r = ~.7). Only T-test performance was strongly correlated with peak eccentric knee-flexor torque (r = ~.78). Stepwise regression modeling showed that only angle-matched strength ratios contributed to the prediction of each agility test. The angle-matched fast:slow ratio for eccentric knee-flexors was the strongest predictor of reactive change of direction speed. The primary predictor for 10-m sprint and T-test was peak eccentric knee-flexor torque at 180/s. Peak eccentric knee-flexor torque at 60/s was the best predictor of deceleration performance. Stepwise modeling showed that strength parameters were able to account for 78% of the variation in T-test performance, 70% of deceleration distance, 55% of 10-m sprint performance, and 44% of reactive change of direction speed.

Implication. Agility is not a global fitness component, with little correlation between different tests of agility performance. Traditionally-calculated strength ratios failed to predict agility performance, whereas angle-matched strength ratios featured in a predictive stepwise model for each agility task. A combination of strength parameters is required to predict agility performance. The efficacy and strength of a prediction is task dependent.

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