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Related Experiment Video

Updated: Jun 18, 2026

Using Gold-standard Gait Analysis Methods to Assess Experience Effects on Lower-limb Mechanics During Moderate High-heeled Jogging and Running

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Performance modeling in an Olympic 1500-m finalist: a practical approach.

Stephen J McGregor¹, Rachael K Weese, Ian K Ratz

¹School of Health Promotion and Human Performance, Eastern Michigan University, Ypsilanti, Michigan, USA. smcgregor@emich.edu

Journal of Strength and Conditioning Research

|November 14, 2009

Summary

A simplified impulse-response (IR) model effectively correlated with an elite runner's performance over 7 years. This training load modeling approach, using training stress score (TSS), helps analyze and optimize athletic performance.

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Area of Science:

Sports Science
Exercise Physiology
Performance Analytics

Background:

Elite middle-distance running performance relies on optimizing training load.
Understanding the relationship between training stress and competition outcomes is crucial for athlete development.
Existing models may not fully capture the nuances of individual training responses.

Purpose of the Study:

To evaluate the correlation between a simplified impulse-response (IR) model and elite middle-distance running performance.
To assess the model's predictive capability over a 7-year period, including two Olympic cycles.
To determine if training stress metrics can be linked to measurable competition results.

Main Methods:

Utilized 7 years (2000-2006) of daily training logs (pace, time) from an elite middle-distance runner.
Calculated training stress score (TSS) to derive acute (ATL) and chronic training loads (CTL).
Developed an IR model output p(t) = CTL - ATL and compared it with Mercier scores (MS) from 800m-1 mile races.

Main Results:

Mercier scores (MS) showed a significant positive correlation with the model output p(t) (p < 0.01).
MS demonstrated a significant negative correlation with acute training load (ATL) (p < 0.01).
Quadratic relationships between MS and p(t)/CTL (p < 0.001) suggest an optimal training balance.

Conclusions:

The simplified IR model's output correlates with performance in an elite athlete.
The model provides insights into the interplay of fitness, fatigue, and performance.
This approach can aid coaches in analyzing training-performance dynamics and optimizing future training regimens.