Dr.Med. V.A. Kurashvili
PhD A.V. Generalov
All-Russian Research Institute of Physical Culture and Sport, Moscow

Keywords: planning, training process, intellectual technologies.

Background. Modern national sport theory and practice give a high priority to the studies to improve the elite athletes’ training for success in the top-ranking international events [1, 2]. The modern training process planning system is to be designed as a system of staged process management plans i.e. covering certain training process stages each having its specific successive goals [3, 6]. A training plan is largely determined by the integrated knowledge of the process with a special emphasis on the modern physiological concepts. Today a variety of process quantification methods for planning purposes with the most appropriate endurance rating sets of criteria is being increasingly applied in leading sport centres [4, 7]. Actual sport practice has demonstrated that traditional workload rating variables (such as mileage, tonnage and elapsed time) are not always sufficient for the modern training process quantification purposes [5].

Objective of the study was to develop and theoretically substantiate the target function analysing method designed to rate the “dose vs. effect” correlations. The method gives the means to accurately measure the trained function growth rate versus rated training workloads.

Methods and structure of the study. Subject to the study were the following elite racing skiers: men (n = 10) aged 23±9 years and women (n = 10) aged 22±8 years. Primary tests (О₁) of the subject athletes were performed in the primary conditioning micro-cycle/ stage (early May); the second test stage (О₂) was performed in the special snowless training stage (early September); and the third test stage (О₃) – prior to the skiing skills refreshment cycle.

We basically applied a training impulse method (TRIMPS) that implies the training process being measured in standard units, the so-called “physical effort doses” [7], with a TRIMPS index being applied to rate the workload using the following formula:

                                           TRIMPS = t_(mins) * ∆HR * y,                                               (1)

Where:

t means duration of training (min);

∆HR - fractional elevation in HR or HR reserve; and

y - weighting factor.

The weighting factor y refers to the average lactate profile estimated at 1.67 for women and 1.92 for men. TRIMPS index is calculated by multiplying the training time in every training zone by the relevant weighting factor specific for every training zone: for example 1, 2, 3. The duration of training in every training zone (as metered by any modern sport cardiometer: Polar, Garmin, Ciclosport etc.) is multiplied by the relevant weighting factor and added. The product gives the training workload estimated by the summarized training zones method.

Study results and discussion. Given in Table 1 hereunder are the study data.

Table 1. TRIMPS index variation over an annualtraining cycle

The study found only the following 3 intensity zones being significant in terms of physiological responses:

• Aerobic zone or below the aerobic threshold with the lactate level lower than 2 ml/l for an average athlete;
• zone two between the aerobic and anaerobic thresholds with the lactate level of 2-4 ml/l;
• Zone above the anaerobic threshold with the lactate level higher than 4 mlM/l.

Furthermore, the following performance criteria need to be taken into account to rate the training workload:

1) External criteria to quantify the conditioning work volume and intensity by external physical values;

2) Internal criteria indicative of the bodily function variations as a result of the training exercise(s) in the training process and upon its completion – including, among other things, physiological, biochemical and other criteria.

One may accurately measure the training workload only when both of the above sets of data are obtained. Actual competitive workload rates measured in real competitions may be lower, comparable with or higher than the precompetitive training process ones depending on the precompetitive practice type, goals, training stage and some other factors. The workloads may vary from relatively modest (particularly when the practices are meant to facilitate the rehabilitation processes following prior heavy training workloads) to the highest-intensity ones designed to mobilize the athlete’s potential to full extent so as to attain a new higher working capacity level.

Analysis of the training systems applied by the subject elite athletes showed that it is the speed-strength qualities that largely determine their technical mastery levels and the motor skill performance quality as verified by the training exercise performance quality rates. It is through the specific sport technique excelling plus the specific speed-strength quality development efforts that the athlete comes to perfect and efficient motor skills.

The due balance of the individual athletic qualities and techniques cannot but vary in the long-term training process, and their correlations are specific for every athletic excellence stage. It is not unusual that the core speed-strength qualities developing and excelling methods and tools are applied indiscriminately, with no customization for the individual biomechanical parameters of the techniques thereby largely hampering the athletic technical skills building process.

Conclusion. The study gives a variety of mathematical means for the training workload quantification. Training process quantification reports are processed in the training process planning based on the modern knowledge to find due correlations of and combination logics in different groups of training exercises customized for the individual combinations of parametric qualities of every athlete. The study offers optimal training workload management methods applicable in the racing skiers' training systems. The goal was obtained with the due contribution of innovative tools to develop customized athletic training systems staged from micro- to mega-cycles based on an integrated modern knowledgebase for different sport disciplines.

References

1. Kurashvili V.A., Neborskaya K.S. Integralnoe issledovanie pokazateley, opredelyayushchikh trenirovannost i vynoslivost u grebtsov akademicheskogo stilya [Integral study of indicators to determine rowers' fitness and endurance]. Uchenye zapiski un-ta im. P.F. Lesgafta, 2013, no. 9 (103), pp. 108-115.
2. Kurashvili V.A. Rashchet optimalnoy velichiny fizicheskoy nagruzki [Calculation of optimum volume of exercise]. Vestnik sportivnykh innovatsiy, 2011, no. 31. p.23.
3. Kurashvili V.A., Kofman L.B. Innovatsionnyie metody psikhofiziologicheskogo analiza deyatelnosti sportsmenov [Innovative methods of psycho-physiological analysis of athletes' performance]. Vestnik sportivnoy nauki, 2015, no. 3, pp. 19-23.  
4. Algrøy EA, Hetlelid K.J., Seiler S., Stray Pedersen J.I. Quantifying training intensity distribution in a group of Norwegian professional soccer players. Int J Sports Physiol Perform. 2011 Mar; 6 (1):70-81.
5. Gross M.J., Shearer D.A., Bringer J.D., Hall R., Cook C.J., Kilduff L.P. Abbreviated Resonant Frequency Training to Augment Heart Rate Variability and Enhance On-Demand Emotional Regulation in Elite Sport Support Staff. Appl Psychophysiol Biofeedback. 2016 Sep; 41(3):263-274.
6. Sylta O., Tønnessen E., Seiler S. From heart-rate data to training quantification: a comparison of 3 methods of training-intensity analysis. Int J Sports Physiol Perform. 2014 Jan; 9 (1):100-7.
7. Tabben M., Sioud R., Haddad M, Franchini E., Chaouachi A., Coquart J., Chaabane H., Chamari K., Tourny-Chollet C. Physiological and Perceived Exertion Responses during International Karate Kumite Competition. Asian J Sports Med. 2013 Dec; 4 (4):263-71.

Corresponding author: kurashvili@list.ru

Abstract

The process of speed-strength athletic training followed by the athletes’ adaptation is designed on a multifactor basis. These factors may vary in a wide range: from individual genetic and morphological factors to the training workload volumes, specifics and variations chosen by a coach. The study offers a training process design system based on objectively applied multisided knowledge of the following: physiological basics of competitive activity; individual athletic fitness rates (including technical mastery and endurance levels); training process efficiency; body responses to the training and competitive workloads with the adaptive resetting of the body functions; mental settings and many other aspects. The study gives a practical overview of the methods of efficient control the key variables of the training process including: training workload metering by the generalized training zoning method; training workload quantification based on the individual lactate level and oxygen demand profiling; training workload quantification in the endurance sports based on the critical speed ratings; and in the speed-strength sports – based on high-intensity interval trainings and plyometric exercises.