Objectively quantifying the value of player actions in football (soccer) is a challenging problem. To date, studies in football analytics have mainly focused on the attacking side of the game, while there has been less work on event-driven metrics for valuing defensive actions (e.g., tackles and interceptions). Therefore in this paper, we use deep learning techniques to define a novel metric that values such defensive actions by studying the threat of passages of play that preceded them. By doing so, we are able to value defensive actions based on what they prevented from happening in the game. Our Defensive Action Expected Threat (DAxT) model has been validated using real-world event-data from the 2017/2018 and 2018/2019 English Premier League seasons, and we combine our model outputs with additional features to derive an overall rating of defensive ability for players. Overall, we find that our model is able to predict the impact of defensive actions allowing us to better value defenders using event-data.

WASHINGTON - A U.S. warship on Thursday destroyed an Iranian drone in the Strait of Hormuz after it threatened the ship, President Donald Trump said. The incident marked a new escalation of tensions between the countries less than one month after Iran downed an American drone in the same waterway and Trump came close to retaliating with a military strike. In remarks at the White House, Trump blamed Iran for a "provocative and hostile" action and said the U.S. responded in self-defense. He said the Navy's USS Boxer, an amphibious assault ship, took defensive action after the Iranian aircraft closed to within 1,000 yards of the ship and ignored multiple calls to stand down. "The United States reserves the right to defend our personnel, facilities and interests and calls upon all nations to condemn Iran's attempts to disrupt freedom of navigation and global commerce," Trump said.