Multivariate Statistics

Many statistical methods can be performed using ordinary pocket calculators. But, this is not the case with multivariate statistical analysis. For its execution, a computer is needed and a statistical program, whichare offered on the market. In such conditions, even untrained and inexperienced people can perform complex multivariate statistical procedures, which is a double-edged sword, because, although the result is relatively easy and fast, there is a great chance to make a mistake.

Multivariate statistical analysis has been present in the sciences for almost a century. However, its application in economic research began in the late 1950s. Eventually, applications of multivariate analysis have become more and more frequent since they were increasingly appreciated by both scientists and businesses.

Prior to multivariate statistical analysis, most researcher used analysis that treated at most two variables at the same time. As a product of such analysis, results were most commonly reported as central tendencies (arithmetic mean, modus, median …), variation measures (variance, standard deviations, quarters…), confidence intervals and tests based on a normal schedule, t-schedule and similarly. The longest range in the study of the relationship of two phenomena was the correlation coefficient.

Multivariate statistical analysis has provided much more powerful techniques that enabled researchers to detect patterns ofbehavior in the interrelation of a large number of variables, patterns that would otherwise be hidden or barely noticeable.

In sports analytics, multivariate statistical analysis can be used to determine the development of functional abilities of a group of soccer oriented athletes. In the experimental group of soccer-oriented respondents, the “circular” form of exercise was implemented for the additional 33 hours of motor exercises. Determining the load level as part of modeling the program for functional abilities development was in accordance with the individual abilities and characteristics of the respondents. Particular care was taken to ensure that the dosage of the load has a gradual and progressive character in all its components (intensity and extensiveness). The selection of the methods of exercise applied in the “circular” form of exercise for the functional abilities development was in the function of achieving goals and tasks, raising the level of preparedness, respecting the age characteristics and conditions in which the experimental program was realized. The organizational form of the “circular” form of work was carried out within homogenized groups. Transformation of functional abilities in both subunits during experimental treatment was determined by analyzing variance at the multivariate level.

The other purpose of multivariate statistical analysis in sport is determining which team has chances of winning in a competition. This is achieved by using principal component and cluster analysis based on the previous results of every sport’s team. After determining the principal components, first and second were used as new data and cluster analysis was used to divide them into two groups. The multivariate statistical analysis made it possible to crystalize the more and less successful teams within the groups.

Multivariate statistical analysis in sports is most appropriate when a researcher wants to analyze the relationships between multiple variables (more than two), and simultaneously according to the appropriate model on which this technique is based.