The analysis tries to determine the relation between number of goals scored by a football player and his age. While the analysis in this step appears straightforward, it is not very prudent to ignore other factors that influence goal scoring in a football match. There can be several factors that affect the performance of a football player as enumerated in the literature review. However, this analysis focuses on only some of them. The independent variables included in the analysis are appearances in the football matches, age, their teams, their nations, and their position as a layer. The dependent variable is obviously the number of goals scored in the match. The analysis further assumes that no playing position has any distinctive advantage or disadvantage with respect to other positions.
The prime focus of the analysis is to determine the relation of the goal scoring with age. This is done in the paper through a step wise process. The first calculation is done ignoring the secondary factors that might influence the goal scoring. Here also, there are two possibilities: first is carried out through a simple correlation analysis of the two variables: goals scored and age of the player. This analysis is further classified on the basis of the country they belong to, playing position and teams. However, since only Australia has a significantly good number of players in the collected data, the country specific analysis is done only for Australia. The data contains only two teams: WSW and New Castle Jets. So, this correlation analysis was carried out easily in two categories. The positional correlation analysis was carried out for the positions having at least fifteen data points. So the analysis has been carried out for the positions of attacking midfielder, central defender, central midfielder and striker. The second analysis is carried out through regression by ignoring and keeping the constant terms.