I was disappointed by the 'data science' in this article. From selecting distribution as a criterion for the qualitry of a metric, for using Pearson correlation

I was disappointed by the 'data science' in this article. From selecting distribution as a criterion for the qualitry of a metric, for using Pearson correlation with non normal data, for using non correlation with Fandango as tie-breaking criterion, for failing to use external criteria (e.g. ticket sales) to validate or compare metrics, and to be picky, for failing to discuss (for example) generalized lin models with link functions to deal with non normal error distributions.