This article begins a mini-series on training-load quantification. In this first installment we synthesize the proposal that was presented and discussed at the previous
World Science and Triathlon Congress, assuming that, from the outset, all methods of quantifying training load are imperfect (including this one). We propose a relatively
simple method for triathlon, but we use it for any of the disciplines separately as well (swimming, cycling or running) in our training programs.
Background on quantification: it is poorly quantified Although in endurance sport we are used to quantifying, in reality it is still a problem to be solved. Partly because there is a habit of quantifying poorly, and partly because the question does not have a perfect solution either. As an example of incorrect quantification, volume is often counted as an accumulated (the total of a cycle), and yet intensity as a one-off (the most intense days of a cycle). This serves as a general reference, but it doesn't make sense for the purposes of a complete quantification of training.
We know that training load is defined by volume, intensity, and density (recovery). We can evaluate the volume as distance or time spent on it, the intensity can be indicated in references of speed/power or physiological zones, and recovery can be assessed in relation to the time of effort (density). We can design a harder workout by removing pause, increasing volume and/or increasing intensity, but it is not easy to dose how much the total hardness increases, depending on whether we do one thing or another. Basically there can be two problems, due to a quantification error: increasing the training load too little from one session to the next, or increasing the training load too much. The former will produce less adaptation (a mere maintenance of the level reached until then, i.e., a lack of effective stimulus), and the latter a risk of injury or negative adaptation (excessive stimulus).
Other background: training programming is underestimated
At the athlete level, sometimes the value of carrying out a "well-thought-out" program is not sufficiently appreciated. Sometimes more attention is paid to training equipment than to the training itself. Yet a better training program matters more than equipment when the goal is to improve performance. And in the same way that we measure or consult the effect of materials before acquiring or using them, we should measure training, which in the end is something more decisive than the material. Of course, we are not disqualifying the value of equipment, but also considering that of the hours of practice.
We suppose that the reader of this article has trusted that a pair of shoes, a special frame or wheels, a swimsuit or a certain suit, a power sensor or a compression garment, as examples, that will give them that extra performance they are looking for. And even if it were not objectively true, just believing it is sure to have a positive effect. Broadly speaking, studies on the benefits of small technological components (we are not talking about synthetic tracks in general or bicycles as a whole, but small components such as those mentioned above), show that they sometimes work, being able to provide improvements in the final performance (the marks) of between 0 and 6%. And in performance-related variables (not competition performance but related variables) up to 30% (Ihsan et al, 2010; Kemmler et al 2009; Chatard et al 2008; Burke, 2003).
Various studies comparing different ways of training show that over the course of a season, final performance (marks) improves by between 5 and 6%. We refer to them from the beginning to the end of the season and in fairly trained people, which can be higher in people who are starting out. The improvements of the best marks, however, if they occur are lower (less than 0,4% usually in the elite and up to 4-5% at lower levels). There may be training methods that make you improve more than others, in much greater differences between them (30 to 60%) than those produced by materials (Esteve-Lanao et al, 2007).
Therefore, the first thing to consider is that the training program is well thought out and controlled. Something that many amateur athletes (and sometimes coaches) pay little attention to often less than the materials they acquire. To do this, a key element is knowing how to measure its hardness. This article shows a proposal that is based on both the objective load (comparable between athletes at absolute level) and the subjective load (perception of training hardness, and therefore comparing perceived stress in response to specific objective loads or accumulation of situations in the person's life).
Training Quantification Methods
For a broad knowledge of the various quantification proposals in endurance sports, the reader is invited to a recent review (Cejuela & Esteve-Lanao, 2011; Jobson et al, 2009), as well as issue 28 of Sportraining (January-February 2010).
When one reviews current methods, two key aspects stand out:
- That there are different criteria for training control, with an eclectic vision and a mixed application being interesting.
- That there are several methodologies to quantify training, although all with some limitations. The coach must choose, according to available means and type of discipline, which of them best satisfies his dynamics of programming and control.
Objective and Constants assumed in the Model
The aim of the model is to compare the hardness of training in different disciplines (swimming, cycling and running), while integrating the complexity of the three disciplines, their linkage, the weighting of volume, intensity and density, and the assessment of global residual fatigue (including the effect of strength training). The model is applicable to their respective sports disciplines separately and to triathlon as a whole, as it also contemplates the effect of transitions.
Scientifically based, but which logically may not fit the particular individuality, it is assumed that:
- An Objective Load must be calculated to compare different performance levels objectively.
- A total Subjective Load must be calculated for each training day. The reason is threefold: 1) to be able to compare different levels of tolerance to training, 2) to observe their evolution in relation to the objective load to intuit states of prolonged fatigue, and 3) to assess the impact of strength training, both in central fatigue and muscle damage.
However, this model does not allow quantifying strength training (only residual fatigue), so another model is needed for this (which we will show in the next article).
Justification and Development of the Model The criteria that support the quantification of the Objective Load were the following:
- Relatively narrow training zones, in order to be able to weigh the transfer of them.
- Total load that is weighted between disciplines (swimming / cycling / running) according to:
- Energy cost.
- Difficulty maintaining technique
- Muscle damage (current and cumulative effect).
- Typical training density
- For triathlon or duathlon, the load in a transition (that of the 2nd segment) should be computed with a higher value than when the same effort is made without prior transition.
Quantification of the Target Load An exclusively three-phase model is avoided, adding "threshold" zones and glycolytic zones. A zone of alactic anaerobic capacity/power is discarded, which is often reduced in these sports to exercises of maximum or explosive force, qualities that we understand cannot be measured by means of the
«time», (as opposed to Foster et al, 2001), and which will be calculated as Subjective Load. The intensity is weighted exponentially, non-linearly, in the global of all the zones that are trained (from below the first threshold to glycolytic zones), to equal an equivalent total stress in the examples of maximum training loads for the same level of performance. The scoring by zones is based on the initial proposal of Esteve-Lanao (2007) based on the survey of its athletes in relation to the hardness of sessions after a season, looking for a coefficient that allows equalizing the hardest load achievable during a season in each zone (Figure 2).
Although the ideal would be to multiply Volume x Intensity x Density, continuous training would present the difficulty of what target value is quantified in Density. It is suggested to investigate, according to energy efficiency, critical speed or the individual Endurance Index (Péronnet et al, 2001), the individual limit times associated with zones on a standard protocol, in order to assign coefficients per zone and thus relativize them to an arbitrary value for continuous training, also weighting density. The volume is quantified in time because it is much better to compare both different levels of performance and ground conditions (pavement, orography, etc.). For this reason, and to simplify and make the model universal, time as volume and intensity are quantified by coefficients by zone and segment.
Therefore, Density is not explicitly contemplated. But since continuous training is the majority in these sports, choosing an arbitrary value would be a huge mistake. It is decided to solve it so that the density is computed in the global of the indices applied to each segment.
Segment Relative Weighting
The units obtained by multiplying time by coefficient are defined as "Objective Load Equivalents" or "ECOs". In order to weight the gross ECOs to the particularities of each segment, the ECO is relativized to the value of the race, which is 1. For swimming, the coefficient is 0,75, and for cycling, 0,5. The justification is made on the basis of a comparative analogue scale from 1 to 4, based on the total number of scientific studies on the subject of the sections in Figure 3. For details of the bibliographic justification, consult the original article (Cejuela & Esteve-Lanao, 2011).
Quantification of Subjective Load
It was chosen to develop a scale that would allow:
- Be easy to understand.
- Clearly identify maximal effort and rest.
- Distinguish few categories, for greater reliability.
A scale of 0 to 5 was chosen, to avoid an overall intermediate score (to force people to choose, instead of a scale of 0-10), although allowing "half" points (to be precise). The values obtained are called Subjective Load Equivalents (ECSs).
The justification of ECSs is pending study with biological markers of fatigue. For the time being, it is used with the understanding that it is one of the least bad ways to unify the impact of training and is based on the global proposal of Bompa (1994). The inability to control all factors (training, accumulated fatigue, global stress, previous feeding, etc.), as well as the variety of ways of quantifying training load between qualities (strength, endurance, etc.) make it impossible to know a single objective value.
For this reason, we understand that the 0 to 5 scale can be useful and comparable with particular variables of the training process, being able to quantify the daily and accumulated values. Figure 4 shows this scale and references that the athlete should review and rate about 20 minutes after the session (such as the model of Foster et al, 2001). For double sessions, the total stress for the day is assessed.
Application to the design and control of training programs
Once we understand the calculations of the Objective Scale and the Subjective Scale (Figure 4 shows an example), we move on to program the training. All of our programs follow scheduling guidelines according to those two scales. Apart from the test, physiological profile and periodization model, we consider that from the beginning of the season a correct adaptation will occur if the objective load progresses and the subjective load does so only initially to maintain or not to do so in such a proportion during the rest of the preparation (Figure 5).
This would indicate an adaptation to the stresses and a greater tolerance of loads, which at low levels will not be necessary to force, to achieve a significant improvement in performance. Logically, the accumulation of certain levels of ECOs and ECSs will depend on the level of the athlete, the stress in their daily life, the recovery measures and their tolerance to general stress. It is not intended to relate the absolute values between them, but the respective trend, as well as in relation to what was predicted by the coach in the face of a programmed load. What is intended, and we understand that it is achieved, is to systematize from a global point of view, the loads between performance levels and tests to be prepared.
BIBLIOGRAPHY
- BOMPA, T. (1994). Theory and Methodology of Training.McGraw-Hill.
- BURKE, ER. (ED) (2003). High-Tech Cycling.Human Kinetics, Champaign, IL.
- CEJUELA-ANTA, R. Y ESTEVELANAO, J. (2011). Training load quantification in triathlon.J. Hum. Sport Exerc. Vol. 6, N.o. 2, 2011.
- CHATARD, JC. Y WILSON, B. (2008). Effect of fastskin suits on performance, drag, and energy cost of swimming.Med Sci Sports Exerc. 40:1149-54.
- ESTEVE-LANAO, J. (2007). Tesis Doctoral. Periodización y Control del Entrenamiento en Corredores de Fondo. Universidad Europea de Madrid.
- FOSTER, C. ET AL (2001). A new approach to monitoring exercise training. J Strength Cond Res 15:109-115.
- IHSAN, M. ET AL (2010). Beneficial effects of ice ingestion as a precooling strategy on 40-km cycling time-trial performance.Int J Sports Physiol Perform. 5:140-151
- JOBSON, S.A. ET AL (2009). The analysis and utilization of cycling training data.Sports Med 39: 833-844.
- KEMMLER, W. ET AL (2009). Effect of compression stockings on running performance in men run- ners. J Strength Cond Res 23:101-105.
- PÉRONNET, F. (2001). Maratón. INDE, Barcelona.
AUTHORS
- Roberto Cejuela Anta> PhD in Physical Activity and Sport Sciences (UA). Senior Coach in Triathlon, Athletics, Cycling and Swimming – www.allinyourmind.es
- Jonathan Esteve Lanao> PhD in Physical Activity and Sport Sciences (UEM). National Athletics and Triathlon Coach – www.allinyourmind.es
