Resumen de Relation between Individualized Training Impulses and Performance in Distance Runners
Vincenzo Manzi, Ferdinando Iellamo, Franco M. Impellizzeri, Stefano D'Ottavio, Carlo Castagna
Purpose: The aim of this study was to develop a method to monitor responses to training loads on an individual basis in recreational long-distance runners (LDR) through training impulses (TRIMP) analysis. The hypothesis tested was that TRIMP on the basis of individually determined weighting factors could result in a better quantification of training responses and performance in LDR in comparison to methods on the basis of average-based group values.
Methods: The training load responses of eight LDR (aged 39.9 +/- 6.5 yr) were monitored using a modified version of the average-based TRIMP called individualized TRIMP (TRIMPi) during a period of 8 wk. The TRIMPi was determined in each LDR using individual HR and lactate profiles determined during an incremental treadmill test. Training-induced effects on performance (5- and 10-km races) and changes in submaximal aerobic fitness (speeds at selected blood lactate concentrations of 2 and 4 mmol[middle dot]L-1) were assessed before and at the end of the training intervention.
Results: Speed at 2 mmol[middle dot]L-1 (+21.3 +/- 5.2%, P < 0.001) and 4 mmol[middle dot]L-1 (+10.6 +/- 2.4%, P < 0.01) concentrations significantly increased after training. Improvements in running speed (%) at 2 mmol[middle dot]L-1 (r = 0.87, P = 0.005) and 4 mmol[middle dot]L-1 (r = 0.74, P = 0.04) concentrations were significantly related to weekly TRIMPi sum. No significant relationship between any variable was detected when average-based group values were used. The TRIMPi was significantly related to 5000- (r = -0.77; P = 0.02) and 10,000-m track performances (r = -0.82; P = 0.01).
Conclusions: Individualized TRIMP is a valid tool in tracking fitness (speed at 2 and 4 mmol[middle dot]L-1) and performance (i.e., 5000- and 10,000-m races) in LDR and is more valuable than the methods on the basis of average-based group values. TRIMPi could predict race performance in LDR.
