Why Is The NFL Slow To Adopt Analytics For Draft?

The NFL has been remarkably slow to catch up with the use of analytics in sports


Former Philadelphia 76ers and Detroit Pistons coach Doug Collins once famously said he’d rather ‘blow his brains out’ than be an ‘analytic’. A man with a near-30 year NBA coaching career emphatically rejected a shift he must’ve seen having impressive effects elsewhere. Collins reflects a lingering suspicion of analytics in professional sports, and his misunderstanding of the value of analytics is, fittingly, betrayed by his wording.

It’s important to remember when discussing analytics in sports as an influence on roster selection, that Moneyball was released in 2003 - the book that brought sabermetrics into the mainstream is 13 years old, and Oakland As’ but some sports are still desperately resistant - at least outwardly - to adopting it in their own decision making.

Generally in baseball, soccer, basketball, and even rugby, analytics and sports was, as put by Bleacher Report, ‘love at first sight.’ As soon as it became properly appreciated that analytics could hold the key to that extra 1%, that improvement on one metric that could be the difference between winning and losing, sports teams were quick to install analytics teams for fear of being left behind by their competition. Oakland As’ success was an early vindication of data’s place in sports, and was one built on sound player selection using the otherwise largely overlooked metric of on-base percentage. Billy Beane and his team were able to find undervalued players in a market dominated by the country’s richer teams, demonstrating to the world the value of statistics in sports where tradition rules.

In more fluid sports like basketball or soccer, specific metrics aren’t given quite the attention they were by the Oakland As, but data and analytics will influence player recruitment from the scouting process through to the medical examination. The NFL, though, has been remarkably slow to catch up. Management at most teams seemingly hasn’t been convicted, but analytics is still very much knocking on the NFL’s door.

One of the reasons for analytics’ slow growth in the NFL is the sport’s financial set-up. With both a salary cap and a revenue sharing system in place, the competing sides are placed on far more even a playing field than in baseball or soccer. No club is at a significant financial advantage across the competition, - innovation is both less necessary and less expected of teams with the means to properly compete with traditional methods. Yes, there are teams that dominate, and there are teams that are almost always considered outsiders, but there are no Oakland As, no team that must innovate or die.

Additionally, the NFL’s positional specialism makes for tricky analysis. You can quite easily compare two hitters’ ability to get on base, but measuring the ability of a quarterback up against a wide receiver or a safety requires completely different metrics. Comparing quarterbacks is straightforward enough, but building a team using data alone is markedly more difficult in the NFL. ‘One of the most common questions I get is, ‘Can you do Moneyball’, for lack of a better term, in the NFL? And the answer is, ‘no, you can’t’,’ Former NFL coach Brian Billick said. ‘You can’t quantify the game of football the way you do baseball. It’s not a statistical game. The parameters of the game, the number of bodies and what they’re doing in conjunction with one another.’ Football is the ultimate team game, where baseball could be considered an individual sport. Each cog affects the other, and choosing picks based on one or a handful of metrics could damage the choreography painstakingly put in place by coaches.

We have seen that in other areas of the club, such as business development and fan engagement, that analytics has a key role to play. For instance, Jonathan Martinez the director of business development at the Oakland Raiders, is discussing how the franchise is using data in business development. So why hasn’t this transferred onto the pitch?

This is not to say it cannot be done, though. The NFL is essentially behind other sports in the arc. The initial ridicule for the failed innovators eventually gives way to acceptance and then ubiquity - it would take just one Oakland As to convince the other teams of analytics’ relevance to football. According to some, many teams are working with analytics despite being publicly against its dominance of other sports. ‘There's always an opportunity for it,’ said Aaron Schatz, editor-in-chief of FootballOutsiders.com. ‘NFL teams are already using it, but they just aren't letting on to it. Just because you don't hear them talk about it doesn't mean they're not doing it. Lots of teams are criticizing it in public and using it in private.’ It’s unlikely players will be picked in the draft on one golden metric alone, football simply doesn’t cater for that. What football will undoubtedly see, though, is a rise in the application of analytics more widely, as the US’ most popular sport finally catches up with the trend. 

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