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Relation between individualized training impulses and performance in distance runners.

Vincenzo Manzi¹, Ferdinando Iellamo, Franco Impellizzeri

¹School of Sport and Exercise Sciences, University Tor Vergata, Rome, Italy.

Medicine and Science in Sports and Exercise

|October 9, 2009

Summary

Individualized training impulses (TRIMPi) effectively monitor training load responses in recreational long-distance runners. This personalized approach improves quantification of training effects and race performance prediction compared to group averages.

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Area of Science:

Sports Science
Exercise Physiology
Running Performance Analysis

Background:

Monitoring training load is crucial for optimizing performance and preventing overtraining in recreational long-distance runners (LDR).
Traditional training impulse (TRIMP) methods often rely on group averages, potentially overlooking individual physiological responses.
Individualized training load monitoring can enhance the specificity and effectiveness of training programs.

Purpose of the Study:

To develop and validate a method for individually monitoring training load responses in LDR using individualized training impulses (TRIMPi).
To test the hypothesis that TRIMPi, based on individual weighting factors, offers superior quantification of training responses and performance compared to average-based group methods.

Main Methods:

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Eight LDR underwent an 8-week training intervention monitored with a modified TRIMP method, termed TRIMPi.

Individual heart rate and lactate profiles were determined via incremental treadmill tests to establish personalized TRIMPi values.

Training-induced changes in performance (5- and 10-km races) and submaximal aerobic fitness (running speed at 2 and 4 mmol/L blood lactate) were assessed pre- and post-intervention.

Main Results:

Significant improvements in running speed at 2 mmol/L (+21.3%) and 4 mmol/L (+10.6%) blood lactate were observed post-training.
Weekly TRIMPi sums strongly correlated with improvements in running speed at both lactate concentrations (r=0.87 and r=0.74, respectively).
No significant relationships were found using average-based group TRIMP values, whereas TRIMPi significantly correlated with 5000-m (r=-0.77) and 10,000-m (r=-0.82) race performances.

Conclusions:

Individualized TRIMP (TRIMPi) is a valid and superior tool for tracking fitness and performance in LDR compared to average-based methods.
TRIMPi effectively quantifies training responses and can predict race performance in recreational long-distance runners.
Personalized training load monitoring enhances the assessment of training adaptations and performance outcomes.