Experts consider that training process is a complete system where, at every stage of portsmanship formation, particular specific features and didactic tasks are solved. The specificity of didactic tasks predetermines the direction of long-term sport training or certain phases of it. Accomplishment of preparedness “objective tasks” appropriate for athlete’s age, which are expressed with forecast result and suitable motor readiness mode characteristics value, makes efficiency of used didactic tasks evident. Therefore, athletes’ preparedness requirements setting should determine the value of parameters, considering the age specification of the long-term sport skills formation. Thereby, the training process that promotes stability at the demonstration of predictable result and matches the criterion of result achievement timeliness may be regarded as the effective one. Some scientific works testify as a rate (model characteristic) of “min-max values” (50,0-99,7 % from sample battery); average statistical value; minimum-required value; maximum-permissible value, etc. However, their variety in evaluation criteria, in the tests content, with the choice of norm parameters considerably decreases their informativity. The aim of the research is to form the battery of the tests and to calculate model characteristics of the motor readiness for triple jumpers (14-19 years). The research has used methodology and algorithm for sport result modelling and motor readiness index developed in VNIIFK. The base for model description calculation was the data received from long jumpers of age 14-19 (n=134) testing and retrospective analysis of the rates being investigated in triple jumpers of high professional skills (n=52). Results of the research show that using different methodologies and technologies, while defining the characteristics of athletes’ motor readiness, essentially decreases level of their informativity for professional experts as the valuation of the training effectiveness criterion. The identified readiness models are most often implied as the indices of functional optimum to the condition, which we should aspire to. In order to increase their informativity, the efforts were placed to define the model parameters by combining two approaches to generating database for the following calculation that was on the base of symbiosis of “slices” and retrospective methods. The found results have been used to calculate the fluctuations range of required values. These values variation within determined limits obtains standard characteristics and allows showing as an interval for the necessary level of athletes’ readiness at the age-related aspect.