AI in Football

We’ll look at this through the lens of a new ownership group, giving us a natural foundation for introducing new processes and ways of thinking, hitting five primary areas along the way:

• Building a championship team (Leadership)

• Developing talent (Player and Personnel Development)

• Telling the story (Marketing)

• Getting fans into seats (Ticketing)

• Bringing the energy (In-game Experience)

The foundation of championship teams is their leadership, so we’ll start with looking at a few ways AI can enhance the ways ownership teams identify and retain talent across the organization. At the core of this challenge is identifying primary leaders that understand your vision and are capable of bringing that to life while developing the teams and individuals they lead. This process will always be human-driven, but AI is quickly making that process infinitely more dynamic.

Finding your Foundation

Relationships will always play an outsized role in how front offices are filled, but with the cost of doing business (as well as the potential for ROI) growing season-over-season, making hyper-informed decisions is more critical than ever. NFL teams—and most organizations—have access to more comprehensive data than ever before. What if they could use that data to analyze trends and reduce biases, pinpointing candidates whose values and philosophies align with your organizational goals

That’s exactly where I see us heading with the new innovations in Dynamic Talent Mapping. These systems are quickly becoming able to aggregate variables like organizational values, intended style of play (are you looking to turn games into track meets or are you more a fan of old school bully ball?), roster building philosophy (moneyball or build through the trenches?) and draft philosophy, then compare that to the profiles you’ve built of the Front Offices they were a part of to quantify an initial compatibility score for each candidate. This could also be used to keep an eye on emerging internal and external talent, providing an advantage when navigating the inevitable game of musical chairs that happens every offseason. 

Another advancement I’m excited about is one we’ll call “critical moment scenarios”. A blindspot of the job interview process is that most decisions we make are done outside settings that resemble job interviews. Time constraints also limit just how many scenarios we can talk through with candidates. Imagine if you could interject tailored, situation-specific challenges into the interview process that allowed your team to see and analyze how candidates work through certain situations.  AI will eventually provide something very close to that, using varying levels of physical and mental tracking to help assess how candidates work through specific, customizable scenarios. 

An actual ball example: let’s say you’re interested in hiring a candidate from the Eagles front office because you value their emphasis on building their fronts via premium draft capital, but you’re concerned that their philosophy of signing their young impact players early doesn’t quite mesh with how your overarching “Moneyball” approach.  Critical moment scenarios will allow you to present the candidate with a player-contract based situation that details key facets like current salary cap information, a “current” roster (tailored any way you want, of course), and comps of players who could potentially be available (want to get really wild? Layer in potential rookies for that upcoming draft class, complete with their current info from PFF, then give yourself an actual draft spot or range). From there, the candidate works through their decisions on things like signing or letting the athlete walk; how we can fill their void if they ultimately decide re-signing them isn’t the best path; as well as their POV on the waterfall effect of their decisions, all while AI helps drive assessment of the how and why behind how they got to those decisions.

Keepin’ ‘em Happy

Retaining talent is as much about the situation the person is leaving as it is about where they could potentially go. This makes arming your talent with optimized tools that help them do their job better and do more of the stuff they love (and that drive value) a distinct advantage in keeping teams intact.

This is another place AI will really move the needle from an efficiency standpoint. Automation is the AI equivalent of blocking and tackling - categorically important to anyone who knows anything, but also not something anyone but purests really want to talk about. Despite its lack of sexy, it’s going to play a massive part in the organizations of tomorrow. Payroll forecasting and processing - fully automated. Employee and athlete satisfaction - gathered, analyzed and reported on in real-time (no more surprises when The Athletic drops their annual rankings). Vendor agreement negotiations and contract execution - handled completely, needing only an overseer’s virtual signature. 

A place it will become really useful is in war rooms during the draft. We love the post-draft content that shows the breakneck-speed draft-day trade decisions are made. But what if AI recording and transcript features (already on a lot of your iPhones if you’re able to upgrade to the new software) could provide real-time valuations of the trades you're offered, with that valuation being based on your data and your valuation metrics? This would provide a real advantage in assessing incoming trade requests and understanding how to maximize value on the trades you send out the door.

The nuance and power of these examples will continue to grow, and with the success of teams like the Browns (current struggles as of publication aside) in leveraging data in new and unique ways, certain organizations will begin to find creative, innovative ways to build championship leadership teams.

Next challenge: maximizing growth. More on that next week.