Technology is increasingly present in, and is impactful on every detail of our lives. This is seen in obvious ways; the fact that everything can be done just as well, if not better, on a smartphone as an online desktop computer, for example. But there are other ways too; in fact there is almost nothing that advances in technology has not affected.
Until quite recently, it seemed that sports had not benefitted as much from this as most other areas had, but it appears as if this is changing now. While all the latest digital trends in sports are interesting, we’ll focus on the National Football League and how it collects and uses Big Data.
What Kind of Big Data is Collected?
The definition of Big Data is a very large data pool that is computationally analysed to reveal trends, associations and patterns. The fitness data of NFL athletes is to be tracked with WHOOP, according to a 5-year contract, signed by that company and the NFL Players Association that was announced on April 24th.
The wearables that Whoop manufactures can track health and performance data such as how much sleep they got and how long they take to recover between workouts and games. A contract between the NFL itself and Zebra Technologies has seen similar (though not identical) information tracked since 2014. There are also sensors in stadiums, on helmets and in shoulder pads, documenting where and how far players have moved.
If Big Data, by definition, uses large sample sets, some argue that this excludes football right from the start. There are, after all, only 16 games for every Football team during the season, compared to 162 games with the exact same starting play in baseball. In terms of sheer numbers, Football might simply not do as well. So why all the fuss? Is Football really another example of Moneyball?
Big Data Could Still be Very Useful to the NFL
While it may seem that the NFL has been slow to climb on the Big Data mining and analysis bandwagon, this is a little too simplistic. As many industry insiders point out, much of Football comes down to analytics anyway. Rather than being beaten to the post, Football coaches and scouts have been performing this kind of action all along.
And while the information pool might be smaller than in Baseball, Big Data still helps to formalise and break it down in very useful ways. If a scout likes the way a player has performed in their last 4 games, the rest of their time on the field could be analysed for patterns. The way two players work together could be critiqued, and injuries and illnesses could be picked up and treated earlier.
What About Abuses?
The key difference between WHOOP and Zebra is that with the former, players will be able to disclose their stats information to third parties. The NFLPA has become an investor, meaning that every WHOOP band that is sold nets them a profit. Learning from and sharing their data could be financially and physically beneficial, but it could also spell disaster and a whole new era of insults to the principles that Football holds dear.
What, for example, would it mean if every coach had an up-to-the-minute report on the wellbeing of each member on the opposing team? And knew that their coach had the same intelligence on his men? Could using the devices be seen as an unfair advantage, in the same way that performance-enhancing drugs might be? What about the information itself – could it be tampered with to create false impressions? For now, with all these questions swirling, the NFL itself has yet to approve WHOOP to be used in games.
What everyone seems to agree on is that Big Data shouldn’t replace good old-fashioned gut instinct. The new technology should be used as a tool in making decisions and setting limits, rather than some all-knowing oracle. However a compromise between WHOOP and Zebra is reached, this equilibrium should remain of primary importance. And if this balance of artificial and human intelligence can be achieved in Football, after all, why not other industries too?