DeCosta emphasized that the goal is to simplify a complex decision-making process on draft day.
"I can't really get into specifics of the analytics, but I would say that we do a lot. [Director of data and decision science] Derrick Yam upstairs, [vice president of research & development] David McDonald, [director of football systems] James Oncea, [senior quantitative analyst] Samantha Lazar, they all do a really good job. We have a lot of different things that they're looking at that help us parse out the different buckets of players and the nuance of 'this guy' or 'that guy.' And when you get down in there, who are the players that might have the traits versus who are the guys that are the most productive football players? Things get layered in like age and injuries and all these different things, as well. And it's really just the decision making. It's trying to help us sort of figure it out [who is] the best pick at the best time. And [it's] also [about] when we think guys might get taken and when we think guys are going to be available and not available, [with] those kind of percentages and things, as well. [It is] all kind of with the idea to take something that's very complicated and make it a little bit easier so that we can make the best decisions on the clock."
DeCosta pointed to Baltimore's expanding analytics infrastructure as a key support tool in navigating the uncertainty of draft-day decision-making.