As a diehard football and Patriots fan, I watch as many games as humanly possible from September until February. Usually, the best game of the week is reserved for Sunday Night Football on NBC and traditionally the Patriots have hogged the spotlight there. The broadcast team of Al Michaels and Chris Collinsworth does a great job of presenting the game and the elements that go into it. One thing that I have noticed more and more often over the past couple of seasons are the “Next Gen Stats powered by AWS” features. The broadcast team will display highlights such as how far a player travels, their maximum speed or the likelihood a quarterback completes a pass. I often find myself saying, “how can they possibly get this data and analyze it?”. To learn more, I decided to dig into how Next Gen Stats started, how they work and how they benefit not just the fans but the actual teams as well.
How it works
Starting in 2013, the NFL sought out ways to obtain more data from on-the-field play. The best way to do it was to place data trackers on the things that actually moved during the game: the players, balls and referees. They partnered with a company called Zebra Technologies to first install RFID chips into the shoulder pads of players in 2014. The NFL was able to share the statistics they complied during the games on the broadcasts in 2015, which greatly enhanced the experience for the fans at home. Fans could get a statistical measurement and representation of what made their favorite players so great.
By 2016, the NFL pushed along its efforts and tagged chips in the footballs used in the preseason and Thursday Night Football games. A year later, the NFL decided that the data was so useful that the chips must be placed in every football used in every game. The NFL also placed RFID tags in the pylons, chains and on the referees to get as much data as available. To capture the data, each stadium has 20-30 ultra-wide band receivers and there three operators at each game to ensure they are working correctly. The end result is more than 200 data points created on each play that can be analyzed by the broadcasts, fans and teams.
Impact on the game
With all this data available, the question becomes how do teams use it to their own benefit? The Philadelphia Eagles created the first known analytics department in the mid 1990’s. At that time the front office, which decides which players will be on the team, were the primary users of the analytics. Data was viewed as something that could enhance the work that the scouting team would normally perform. The New Orleans Saints were the first team to individually use player tracking to their own benefit in order to understand trends in gameplay. That Saints team eventually went on to win the Super Bowl. In a copy-cat league like the NFL, this led other teams to start their own research on how they can get an edge through analytics.
When data analytics first made its way into the NFL, the teams that adopted it were reluctant to share their knowledge. The NFL leveled the playing field in 2018 when every club received the entire leagues Next Gen Stats. This provided teams the ability to judge the strengths and weaknesses of opposing players in a much more complete way than before. Teams can dive into the statistical breakdown of how specific players block, run routes, drop into coverage and tackle ballcarriers. All of this was previously done by scouts and coaches who had to make subjective observations and report their findings. These advanced analytics provide definitive numbers that can be used for easier decision making on how to attack other teams.
In the future, teams could conceivably use all of the data they built up for immediate predictive capabilities during the game itself. It’s not hard to imagine that a team could use rapid analytics to read a defense or offense based on personnel on the field and make a prediction on the exact play the opponent will run. If it ever gets to that point, it will be interesting to see how the NFL views that in terms of competitive gameplay and whether it is legal.
Is it worth it?
The question that I find myself coming back to in all of this is whether the data analytics capabilities are making the game better. It is clear that there have been teams that have had success and were driven by analytics. The 2017 Philadelphia Eagles, which went on to win the Super Bowl, used analytics to drive their decisions on to “go for it” on fourth-down plays when many other teams would either kick a field goal or punt it away. The Baltimore Ravens and San Francisco 49ers are two of the teams most heavily linked to data analytics and were the top seeds for the playoffs in the 2019 season. However, the Ravens ended up losing the Tennessee Titans; a team that bucked current analytics trends and ran the ball heavily instead of passing it.
As a fan, I want my team to be using analytics to help bolster their chances of winning. However, I do not want them to solely use it to make decisions and judgements. In sports there has to be a place for making human decisions based on the current moment. Analytics can only go so far because there are several other variables that impact the game. How do you statistically measure the momentum your team or the opponent has at the time and factor that into data models? Additionally, how do you measure the experience that a coach or player has and its impact? It sounds impossible to me based on my experience playing the game and from listening to others who have played professionally. An over-dependence on either data analytics or “gut feeling” will leave the team in a weaker position. A balance between the two should be taken to put players in the best position to succeed and make evaluations of opponents.