Scorigami: Simulating the Distribution and Assessing the Rarity of National Football League Scores

NFL Scorigamis have a cult-like following, and occur whenever a game ends in a new, never-before-seen score. While substantial research has gone into simulating and predicting NFL game scores, most work has been in relation to winner prediction and betting spreads. We analyze a Poisson random variable model for the distribution of NFL game scores and show that it fails to incorporate important game dynamics. Through an analysis of extensive play-by-play data, we extend this to a non-stationary, state-dependent Poisson process model. This latter model more closely fits real NFL score data, and we use it in NFL score simulations to forecast likely future Scorigamis.