NFL Pulls Back Curtain on Year 1 of Player Tracking, Next-Gen Stats

Speakers at the recent MIT Sloan Sports Analytics Conference emphasize the need for context

The NBA, NFL, NHL, and Major League Baseball have embraced player-tracking solutions over the past three years and have begun integrating graphic visualizations of the data into broadcasts and streaming content. The four major U.S. sports leagues join a rapidly growing global bandwagon of leagues, teams, and broadcasters beefing up data-analytics teams and investing in tracking/visualization. Despite the treasure trove of data available, however, the key remains adding context to make it digestible for both fans and professionals alike.

“You have to be very, very careful to provide context, because data in and of itself is just an overwhelming amount of zeros and ones that don’t mean anything,” cautioned Perkins Miller, chief digital officer/head of media operations, NFL, at the MIT Sloan Sports Analytics Conference this month in Boston. “That is where people will confuse data with insight. We spend a lot of time taking this data and making sure we provide the right context so you can develop the right insight. As Mark Twain said, ‘There are lies, damn lies, and statistics.’ You have to be very careful about how you provide that context and insight.”

NFL, Zebra Report on Deployment of Next-Gen Stats
The NFL partnered with Zebra Technologies to install player-tracking systems at all 31 NFL stadiums (as well as Wembley Stadium in London and Aloha Stadium in Hawaii) last year. NFL players wore RFID chips that delivered data points to these systems, serving the league’s Next-Gen Stats system. In all, Zebra’s system tagged and tracked 2.500+ NFL players and collected more than 180 billion bites of position data during the 2015 campaign.

“We spent a lot of time working with Zebra,” said Miller, “and they have done a great job to provide that level of fidelity so that the data that comes out is predictable and consistent. If it’s not predictable and consistent, it’s not trustworthy.”

A screen from the NFL Next-Gen Stats system

A screen from the NFL Next-Gen Stats system

With a full season of league-wide player-tracking in the books, coaches, scouts, and strength/conditioning staffs; the league’s broadcast partners and NFL Media; players and even fans are beginning to reap the benefits of deeper data.

“Not only does [data-analytics/visualization technology] work at the really granular level with player development, health, and safety and at the coaching level, we also look at it through the lens of how we can tell the story for our fans better on television?” Miller added. “How can you understand how hard it is from a quarterback’s [perspective] to throw to an eligible receiver in a split-second decision?”

He also stressed the importance of selecting specific scenarios in which to use the data within an NFL telecast, rather than forcing mountains of incomprehensible information on the fan.

“You’re not going to get someone really thrilled talking about a change-vector speed, … but they might want to understand how much separation a wide receiver had on coverage and has he been able to maintain that separation throughout the first quarter and is that why his team has gotten so many first downs?” Miller explained. “If you can find a way to package that right, [such as] a separation index that is easy to digest, you can get to the vernacular, and it becomes part of the story.”

NFL Hackathon Delivers Deeper Insights
In San Francisco last month, the NFL hosted a 24-hour hackathon, handing its Next-Gen Stats data to an army of software developers and challenging them to “develop the next generation of engaging NFL stories.” Given raw location data, developers were tasked with creating real-time, in-game pattern-recognition systems to provide deeper insight into the game. The winning group came up with a pattern capable of determining the probability of a successful pass immediately after the ball is snapped, based on the configuration of eligible receivers and the defensive line.

“That is just a fascinating piece of evolution,” said Miller. “[It] makes the game more interesting if you are able to understand the decision-making the quarterback has to make as he drops back to throw. Now, how soon we can make that a reality is still many leaps to the future, but … there are ways to make the game even more exciting than it already is on television by using the data to tell a story and showcase how hard it is for some of these players to perform on the field.”

More on Sports Tracking: The Next-Generation Panel
In addition to Miller, a panel on sports-tracking solutions offered insights ranging from the benefits of data analytics for evaluating player performance and the potential impact on fantasy-football games to player strength, conditioning, and medical evaluation. Here are a few highlights from the session:

Dean Oliver, VP, data science, TruMedia, on the potential impact of data analytics on fantasy football for fans:
“I think we can come up with all sorts of new fantasy stats for positions that have never really been measured. For [a player like New York Jets cornerback] Darrelle Revis, who is denying and clogging the passing lanes, we can add more to that conversation. Some of the players have rebelled against ‘I didn’t get the touchdown, but I ran 87 yards to the 1-yard line, and people were upset because I didn’t get the touchdown.’ I think we can add a few more meaningful statistics to that, and the consumer fantasy [market] is certainly going to be interested by some of these.”

Matt Sheldon, director, football analytics and research, Chicago Bears, on where player-tracking systems must improve to deliver more-valuable data:
“So many of these systems are really tuned towards open-field running. In American football, 45% of the players don’t open-field run on every play. We would like to see orientation to know when a player is running forward or backward. In the passing game, so many of the players are retreating from the line of scrimmage while facing the line of scrimmage in a back-pedal. The line play is so intriguing, but these systems are not drawing out that value at this time.

“[One example is] the ability to track movements of types of players that don’t do a lot of open-field running: an offensive lineman in pass protection or a lineman in a blocking play. Working backwards from what is necessary to be successful, [we determine] the traits to quantify the elite and then, hopefully, develop players up to that standard and select players that are competent in that area.”

Adam Beard, director, high performance, Cleveland Browns, on how player tracking helped to revolutionize Welsh Rugby Union while he was head of physical performance for the club from 2009 to 2014:
“Data helps us be more objective and look at the trends in terms of what is going to help win. When I first came to the States, it was interesting that the NFL didn’t track anything on game day. When I got there, I said, ‘We are tracking training, so are we aiming to get better at practice or the game?’… Our guys wore [heart-rate sensors] and GPS for the past six years during training and game day. Look at a sports like Formula 1, where the pit crews went from three or four members to nine or 10 specialists. They have gone from 68 seconds changing tires to as low as two seconds. You’re not changing the sport; you’re just making it more efficient.”

Bob Thurman, VP, innovation, Wilson Sporting Goods, on key findings from the company’s work in tracking and data analytics:
“We have learned a lot of things in [regards] to the flight of the ball and how much rotation and spin a quarterback gets on it. Tom Brady, who plays in a fairly windy stadium, gets more than 600 or 700 rpm of rotation on the ball. Those are little insights so we can start to build off of those things. We can’t measure that right now, but [coaches] can now say we need to work on mechanics that will produce that kind of rotation, which makes a more stable ball, and you get through the air much faster and, ultimately, score more touchdowns.”

Isaiah Kacyvenski, former NFL player and head of business development, MC10, where he oversees development of wearable electronics:
“I look at capturing these analytics as performance metrics and then unique media content and [fan-]engagement plays. The player really has to believe this can optimize my performance and minimize my risk of injury. There is value as a player to use this. If my body is my business, I want to make that business run as best as it possibly can. There is this buy-in that this is making me a better player, so I can play better, longer, and make more money to take care of my family. The idea of capturing data during live game play is not that crazy, because the understood value is already there. Will that drive [engagement]? Absolutely.”