HPRowing - 3 - Stress Points: A Simplified Model for Quantifying Training Workload Based on the TRIMPS Model
Earlier this Fall, I read an interesting paper about Eric Bannister's TRIMPS (Training Impulses) model. This model was used to quantify the workload that an athlete takes on during a workout. I have previously seen and used several models to quantify the training loads of various workouts, however, TRIMPS stuck out to me because it expressed training load as the product of intensity and duration, instead of only intensity, duration, or mileage. I was so intrigued by this model, that I used my background in applied mathematics to create a TRIMPS based model specifically for rowing.
Stress Points (SP): A Model for Quantifying Training Workload based on the TRIMPS model
Stress Points (SP) is a method for quantifying the workload of a rowing session to determine a single estimate of a training session’s physiological stress. Intensity is determined by using the standard 6 Zone (UT3-TR2) intensity distribution. This cam expressed in abstract terms as the product of each training session’s intensity and duration.
The computation for the SP of a workout is as follows:
The following table can be used to calculate SP based on the standard 6 zone intensity distribution.
Examples of calculating SP
Ex. A 3x15 minute workout at AT intensity would yield a 45 * 1.333 = 59.985 WPM
Ex. A 90 minute steady state at UT2 intensity would yield a 90 * 1 = 90 WPM
Ex. A 10 minute race piece at TR2 intensity would yield a 2.5 * 10 = 25 WP
Model Pros:
• SP quantify the relative intensity and volume of a training session.
• One value can be used to represent how hard and how long an athlete works out.
• X points earned by a professional or a novice athlete are relatively similar because SP is relative to an athlete’s individual fitness and thresholds.
• Workouts are dynamically weighted by intensity.
• Weekly SP can be used in developing the periodization of training plans.
Model Limitations:
While the model does an accurate job of modeling workout stress during continuous such as steady state, tempo pace, anaerobic threshold training, races, or time trials, there exist limitations when using it during discrete workouts such as HIIT (High Intensity Interval Training) or fartlek sessions. Due to rest periods of low intensity between intervals, the SP model underestimates the amount of training stress during this type of training. However, it can be noted that an additional variable, δ, can be used to account for the sudden changes in heart rate intensity such that δ is the fractional elevation in the athletes heart rate. Due to the model being as simple as possible, δ was omitted from the equation. There also exists a limitation when doing strength endurance training with either a high drag on the indoor rowing machine or by using bungees on the water. This is because the system used to map intensity is a function of either heart rate or blood lactate accumulation. It does not take into account the additional load placed on the body during these types of workouts. Therefore, the model underestimates workout intensity during strength endurance sessions.
Derivation:
The standard intensity that the average endurance athlete uses for the majority of their workouts is the UT2 intensity. This is because UT2 is when the blood lactate concentration is between resting lactate (0.8 – 1.5 mmol/L) and the aerobic threshold (2.0 mmol/L). Therefore, we define the UT2 intensity to produce SP at the rate of 60 per hour. Due to the relatively linear correlation between blood lactate versus intensity level less than the anaerobic threshold (4.0 mmol/L), the UT1 and AT intensities respectively produce a SP of 70 and 80 per hour. However, since blood lactate increases exponentially after a concentration of 4.0 mmol/L, the TR1 and TR2 intensities respectively yield 110 and 150 SP per hour.
References
BANISTER, E. W. 1991. Modeling Elite Athletic Performance. In: MACDOUGALL, J. D., WENGER, H. A. & GREEN, H. J. (eds.) Physiological Testing of Elite Athletes. Champaign, Illinois: Human Kinetics.