With the nature of the linear regression, I could encounter some drawbacks using a linear panel method as the dependent variable is assumed to be continuous rather than ordinally discrete. As I am dealing with count data throughout this model, a Poisson model will also be run in order to offset this problem. Unlike the linear panel model, this model will not include players that have received zero yellow cards in their appearances, as they would make no contribution to the conditional maximum likelihood function. The estimation of these models with fixed effects can occur using either a conditional maximum likelihood estimator or an unconditional estimator. The conditional procedure is conditioned on the sum of the counts for the individual over time, giving us an easier estimation process (Reilly & Witt, 2011). Also, with the econometric software of STATA that I have used, there will be no biases included due to the problem of ‘incidental parameters’. This allows my estimation of the method and use of software to leave me with both valid and reliable results.