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Measuring workload objectively is challenging due to a variety of factors. One concept that assigns a numerical value to a work bout is training impulse (TRIMP). TRIMP uses time spent in physiologically significant heart rate zones to quantify session workload. Tracking average short-term workload (15-day acute training load, ATL) and long-term workload (45-day chronic training load, CTL) can be used to assess individual “fatigue” and “fitness” levels. Moreover, the difference between CTL and ATL scores (training stress balance, TSB) may be suggestive of readiness for optimal physical performance. This method has been used in elite male cyclists and recreational male distance runners, but not female endurance athletes. PURPOSE: To assess the acute and chronic aerobic training load placed upon a female collegiate distance runner by quantifying time spent in physiologically significant heart rate zones. METHODS: One individual was observed over a 6-month period during the fall collegiate cross country competitive season. Three heart rate zones (moderate, heavy, and severe) were determined by assessing heart rate during a sample training run, as well as measuring heart rate in comparison to critical velocity during a validated endurance capacity test. Heart rate was recorded with a data-storage capable, wearable bioelectrical monitor. Following the completion of each run, data files were imported into a software package that calculated TRIMP scores for the individual work bouts, as well as the moving averages used to determine ATL and CTL. RESULTS: CTL increased during the early competitive season as mileage and overall workout intensities increased. ATL generally decreased preceding competitions. Better race performances did not consistently reflect more positive TSB scores. CONCLUSION: Both ATL and CTL generally reflect subjective workload intensity over the course of a cross country competitive season. Although the TSB scores prior to important races were positive, a successful race outcome did not always occur. However, the participant’s best race performance did follow the most positive TSB score. It is likely that while TSB contributes to performance in competition, additional factors such as motivation and injury play an important role in describing race outcome.

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