To that end, we considered an angle of 0�� as the angle between the defender and the attacker when they form a line perpendicular to the goal, being the defender closer to it. The way the angle increases or decreases follows the basic principles of the unit circle where the origin of the referential is the defender. This means that when the attacker overtakes Tubacin microtubule the defender, i.e., when the attacker is closer to the goal, the angle will be situated on the 2nd or 3rd quadrant, i.e., 90o<|��|��180��. The mapping allowed the construction of frequency histograms based on the spatial distribution of the attacker. Each heat map refers to a condition of practice for each player, i.e., each heat map represents 10 trials of each player in each condition of practice.

For this purpose, the whole scene was split in a 20 �� 20 matrix resulting in a resolution lower than 1 m2, thus obtaining a histogram representative of the most occupied zones of the field by a given player in a given practice condition. Figure 3 (left) illustrates an example of an obtained histogram. Figure 3 Illustrative image of a histogram (left) and its heat map (right) representative of the most occupied zones of the field by a player in a practice condition To support the analysis of the occupied zones we proceeded to the design of heat maps (Figure 3 right). These heat maps consist of a graphical representation of the data in which the frequency values obtained by the spatial distribution histograms are represented in a two-dimensional table with different colors.

The darker colors represent a higher occupation frequency in a certain zone of the field. This graphical representation allows a quick view of the data, giving a potential to analyze possible trends of spatial occupation of attackers. In addition, to analyze the traveled distance, we also proceeded to the statistical analysis of required time the attackers needs to complete the offensive attempt in each practice condition. This analysis allows to verify if different instructions provided by the coach results in differences while achieving the task. Thus, in each trial, the time spent by the attacker to complete the offensive process was also collected. The one-way ANOVA was used to establish the statistically significant differences between football players, in each practice condition.

The assumption of normality distribution Cilengitide of one-way ANOVA in the three practice conditions (i.e., conservative, neutral and risk) was investigated using the Kolmogorov-Smirnov test with correction Lillefors. It was found that the distributions are not normal in the dependent variable. Although it was not normal, since n = 110, using the Central Limit Theorem we assumed the assumption of normality (Akritas and Papadatos, 2004). The analysis of homogeneity was carried out using the Levene test. It was found that there is no uniformity of practice under the previously mentioned conditions.