Incorporating Analytics in Production
Some of the biggest arguments we see during the NFL Draft process are between “Film Twitter” and “Analytics Twitter” over prospects, particularly at the wide receiver position.
Analytics folks love the dominator rating, which measures a player’s market share in their offense. They believe that’s one of the better indicators of success in the NFL. A.J. Green, Julio Jones, and Demaryius Thomas are three names who had large dominator ratings who found success in the NFL.
Obviously, the film grinders (this writer included) believe that identifying top traits on film and grading them on a numerical scale will translate most to success in the NFL.
So how do we decide this? Well, it’s important for both sides to embrace the other. As much as the film doesn’t lie, if a player is limited athletically, that matters. If production analytics numbers aren’t great, it matters to an extent.
If we come back to the dominator rating quickly, think about it logically. Wouldn’t the best players get a lot of market share and produce with said market share. Isn’t it important for top talents to break out when they’re younger (the term in the analytics community is “breakout age”)? Of course, it does! But, there are always exceptions, which is why neither side is perfect.
So, to the film grinders out there, embrace analytics, try to incorporate things you think translate the most. A lot of this is trial and error to find the best correlation, and taking in as much information as possible is important.