This data will now be for a preliminary exercise, with the differences in both fouls committed and cards received in comparison to their skin tone to be examined.  Due to the nature of this model, we will first allocate players to either a “white” or a “non-white” category, for the purpose of this initial experiment. As we are researching potential racial bias in a predominately white league, I felt that placing players into these two distinct groups, to begin with, would be interesting. Essentially, the two skin tones of “Very Light” and “Light” will fall into the former category and “Mixed”, “Dark” and Very Dark” will fall under the latter. This will be done with a set of parametric (T-Test) and non-parametric tests (Mann-Whitney U-Test) in order to determine if there are any significant differences statistically across these 2 groups. Both types of tests were used to assess any statistical differences between the population means for the t-test and the population median for the Mann-Whitney U-Test.  Where the standard t-test results may lack in applying for attributes, the non-parametric Mann-Whitney is able to apply for both variables and attributes, giving us a more reliable set of results. Having both types of statistical tests available also allows us to account for if there was no information about the population with regards to the non-parametric test, although this would not be a problem in our framework, with the number of observations and players known. Our parametric test also assumes that variables are measured on either a ratio or interval level, with both fouls committed and the total number of cards, falling under the latter category (Surbhi, 2016.) The results found for the aforementioned categories are reported in Tables 2 and 3 respectively.