Determining the Impact of Socioeconomic Status on Athletic Performance Using Machine Learning

Because increasing athletic competition at the middle and high school levels has shifted the focus in sports towards achieving superior physical performance, optimizing athleticism and minimizing injury risk have become even more critical. However, the effects of socioeconomic disparity extend into youth sports participation; using machine learning algorithms, this research examines the correlations between socioeconomic statistics among school districts and the physical ability scores of youth athletes in those communities. Although all of the models achieved predictive accuracies above 94.2 percent when determining athleticism scores, they ultimately indicate that there is no direct correlation between a school district’s socioeconomic profile and the physical ability of its students.