Quantifying Training and Competition Load

The following is an exclusive excerpt from the book NSCA’s Essentials of Sport Science, published by Human Kinetics. All text and images provided by Human Kinetics.

A key component for both programming and monitoring an athlete’s progression or regression is the quantification of training load. This process is critical for assessing whether an athlete is adapting positively to a training program (14). As mentioned earlier, external load refers to what the athlete has done (e.g., distance and speed of running, kilograms lifted), while internal load refers to how the athlete has responded to a given external load (72, 73). This internal response can be both physiological (e.g., heart rate, blood lactate) and perceptual (e.g., rate of perceived exertion [RPE]) (73). Ultimately it is the internal response to a given external load that drives the training outcome (72, 73). Importantly, measures of external and internal load should be used in combination to provide a complete picture of the training process and response (14). Furthermore, as mentioned earlier, a comprehensive understanding of the external load of a sport allows the development of specific training programs aimed at targeting the relevant underlying physiological qualities (e.g., aerobic capacity, speed, strength).

External load can be measured in a variety of ways depending on the sport or training modality (14). Technological advances such as camera systems and microtechnology (local systems and Global Positioning Systems [GPS]), often in conjunction with other sensors such as accelerometers and power meters, have made the quantification of various activity metrics in teams and in sports such as running and cycling relatively simple. While this process has become common, some critical elements should be considered with regard to the measurement of external load, and these are explored next.

The measurement of speed and distance metrics using GPS is now commonplace, and the validity and reliability of these devices have been extensively examined (21, 36, 75, 77). In general, higher-sample-rate (e.g., 10 Hz versus 5 Hz) GPS chips have demonstrated superior validity and reliability to lower sample rates, particularly for the measurement of high-intensity running efforts and accelerations (21, 75, 77). The sampling rate of these systems continues to increase, which may assist in further improving validity and reliability for the measurement of high-intensity events. Furthermore, the use of indoor stadiums has necessitated the development of indoor tracking systems such as Local Positioning Systems (LPS), which can provide information similar to that with GPS (131). Additional detail on these systems is provided in chapter 9. Furthermore, determining thresholds for classification of high-speed running, sprinting, and accelerations is challenging for practitioners regardless of the tracking technology employed, and doing this includes consideration of whether these thresholds should be based on team or individual values and whether they should have a physiological basis (134). Work in this area has used a movement sequencing technique rather than arbitrary thresholds to classify velocity and accelerations performed by elite netball athletes, and similar approaches in other sports may yield valuable insights (133). A primary driver for practitioners in deciding whether to use relative or absolute speed and acceleration thresholds is likely related to whether comparisons are being made between or within individual athletes. Furthermore, sport scientists and coaches should be aware that values transmitted live by the units and those calculated after downloading data can be different, and this may have significant implications for training or competition decision making (6). The impact of data processing (e.g., smoothing techniques) on measured variables should also be considered (137). Finally, a highlighted factor in the quantification of team-sport activity profiles is the consideration of average intensity versus peak intensity (41). Peak running intensity is substantially higher in relatively short time windows (e.g., 1 min) compared to the average intensity in a half- or full-duration rugby league match (41). This has important implications for the design of training programs targeted at developing the underlying physical qualities important for being able to perform at the required intensity; and in practice, both peak and average intensity should be considered. These and other considerations are discussed in more detail in chapters 9 and 10 of this book.

Given the chaotic nature of team sports, it has been suggested that speed and distance metrics may not completely quantify the full external load (15, 114). The reason is that many movements that are energetically costly and taxing on the neuromuscular system (e.g., accelerations, decelerations, change of direction, and contact) can occur at low speed and accumulate relatively little distance (15, 114). These activities can be measured with a variety of sensors such as high-sample-rate (e.g., 100 Hz or greater) triaxial accelerometers, gyroscopes, and magnetometers, and these accelerometers in particular have demonstrated high reliability and ecological validity (15, 30, 34, 97, 114). Manufacturers have tended to create their own metrics for values obtained from triaxial accelerometers, similar to the Catapult PlayerLoad™ calculation shown, but they all essentially represent a combination of individual vector values (15):

Interestingly, changes to these metrics or the individual vector contributions to the overall value have shown promise in the ability to detect fatigue-induced changes in movement strategy (30, 97, 114). The use of this type of metric, in conjunction with traditional locomotor variables as measures of external load, may provide practitioners with additional insight.

Of particular interest is the fact that various manufacturers have developed algorithms to auto-detect specific sport events, such as fast bowling in cricket and tackles in contact sports, with reasonable accuracy (56, 71, 95). This may be useful in reducing the time and effort required for accurate measurement of external load, leading to more precise quantification and therefore assisting with both planning and monitoring of training and competition.

The frequent accelerations and decelerations performed in team sports can substantially increase the energy cost (42). In order to account for this, the concept of metabolic power was developed, which is based on the principle that the energy cost of acceleration is equivalent to running at a constant speed up an “equivalent slope” (42). As a result, numerous measures have been proposed; these include metabolic power (in categories from low [0-10 W/kg] to maximum [>55 W/kg]), total energy expenditure (kJ/kg), equivalent distance (representing the distance that would have been covered during steady-state running on a flat grass surface), and equivalent distance index (representing the ratio between equivalent distance and total distance) (108). While the use of metabolic power has undergone some investigation (37, 80) and has attractive practical aspects, its validity has been questioned for various reasons, including the innate error in measuring accelerations using positional systems (16, 19, 21).

In addition, work has focused on the detection of specific variables such as stride parameters and vertical stiffness from accelerometry (20, 49, 84, 101). This type of analysis may prove insightful for practitioners, although there is some conjecture regarding the impact of unit placement (i.e., scapular versus center of mass versus lower leg) on the ability to accurately measure specific variables (20, 46, 109).

Measurement of external load in endurance sports is also common (100). Sports such as running, cycling, and swimming lend themselves well to external load measurement via quantification of various combinations of speed, distance, and duration (100). In addition, the development of power meters has allowed easy measurement of power from pedal strokes in cycling (100). Readers are directed to part IV of this book for extensive coverage of this topic.

Because not all training occurs in the field, other training components also require quantification. For example, various indices of external load can be calculated from resistance training, including sets, repetitions, volume load, and device displacement velocity (124). An important reason for the quantification of resistance training load is the impact of volume and intensity of resistance training on muscular adaptation (110). These approaches can be used to both program and monitor resistance training load, although some methods arguably provide a more complete representation of external load than others (124). For example, the total number of repetitions performed (i.e., number of sets × number of repetitions) in a particular exercise provides a global representation of external load; however, it fails to account for the intensity (i.e., percent repetition maximum) (124). Accounting for the intensity in terms of load lifted by quantifying resistance training load as [number of sets × number of repetitions × weight lifted] somewhat overcomes the limitations mentioned earlier; however, it does not account for the intensity of the load relative to the maximum strength of the lifter (124). Therefore, quantification of resistance training load as [number of sets × number of repetitions × percent repetition maximum] may be most appropriate. Furthermore, the availability of measurement devices such as force plates, linear position transducers, and bar- and body-mounted accelerometers allows measurement of variables such as displacement, velocity, and power, which may also prove useful for both the programming and monitoring of resistance training (4, 9).

In addition to the measurement of external load, the quantification of internal load is a critical component of the training process. There are numerous approaches to this, including the use of both objective and subjective (often referred to as “perceptual”) markers such as RPE, various heart rate indices, and biochemical markers. These measures are considered later in this chapter, and a detailed review of the assessment of internal load is provided in chapters 14, 16, and 17.

NSCA’s Essentials of Sport Scienceprovides the most contemporary and comprehensive overview of the field of sport science and the role of the sport scientist. It is the primary preparation resource for the Certified Performance and Sport Scientist^® (CPSS^®) certification exam. The book is available in bookstores everywhere, as well as online at the NSCA Store.