Post-Production in the NFL

The concept of correlation is something that, as an NFL post-production manager, I encounter on a regular basis; whether it's evaluating hours of video content from various sources (player mic, coach, crowd noise), determining which storylines fans are most interested in, and making sure all of these elements come together for a cohesive viewing experience.

Within my world:

• The more engaging camera angles we use, the higher the likelihood a clip performs well online

• The more time we invest in storytelling-driven editing, the more emotionally connected fans feel

• The more mic’d-up player content we release after a win, the better the engagement

  metrics respond

The presentation showed us how correlation is a way of examining the relationship between two metric-based data points, and this is an everyday analytical tool that I utilize on a regular basis, but rarely name specifically. Correlation helps me determine if there is a relationship between two numerical measures, (i.e., page views vs. revisiting).

For me, this includes snap count vs. highlight popularity, and win margin vs. fan sentiment in comments sections. When breaking down my final edits, I am looking at how frame pacing, audio clarity, and storytelling density relate to the increase of audience engagement. On occasion, I'll also look at comparative data tracking across several games to see which editing style best relates to consistent audience engagement. Using correlation within the context of NFL media shows me more than just numbers - it shows me patterns of emotion, behavior, and attention. In a league where every frame can have an impact on perception, understanding those patterns is essential.