Big data is going to change the NHL

Hockey has been a notoriously slow adopter of new technology, but after three decades of planning and development, the hope is that the tracking devices that are now fitted inside pucks — as well as players’ shoulder pads and sensors around the rink — will increase fan engagement and revenue for the league, according to the NHL’s Senior Vice President of business development David Lehanski. Big data is also expected to be a useful tool for players and coaches, improving the game itself.

There are four areas where analytics could kick off a new era for the NHL:

Real-Time Performance Assessment

Roughly 2,000 data points per second will be collected across all tracking devices, streaming real-time intel on puck speed, player possession, distance skated and more directly to managers’ and coaches’ devices throughout each game. With hockey being one of the world’s fastest sports, rink-side access to this set of stats will allow for better control over players during the games. For example, the data will enable coaches to confirm the physical state of players who seem to be flagging, helping them to make substitutions if necessary.

Aggregating a season’s worth of data will also help with game tactics, and the introduction of AI could further help with strategizing — bots are being taught who common plays work so that their algorithms so that they can suggest improvements when mistakes are made.

Player Health And Fitness

While trackable pucks are guiding in-play decisions and tactics, the sensors inside shoulder pads are monitoring player health and fitness. Along with the data collected from wearable health devices during training, additional info from games is aiding in the creation of customized training regimes to help each player be at their best on the ice.

Over half of the players in the NHL have missed at least one game per season due to an injury, making hockey one of the most dangerous major sports. Luckily the new tech will be of service in this area too, preventing players from overexerting themselves during training, or even anticipating injuries via AI.

Audience Engagement

The NHL stands to make a lot of money this season due to a new network broadcast deal, but filling arenas remains a challenge. Average attendance has declined steadily over the last few seasons, but big data promises to add incentive for audiences by feeding them stats through an app, as the NBL and MLB have done to great success.

On-demand access to data on each player and play could be particularly appealing for a game as fast-paced as hockey, not to mention the practicality of additional info like parking availability, seating charts and the location of the nearest bathroom. Stats will undoubtedly be a handy reference tool for those who bet on games via websites like Betway Lines.

While increased fan engagement isn’t all about putting butts in seats and money in the bank, it’s clear that the NHL will also use big data the way most organizations do: to tailor advertising and sponsorships on the basis of the info gathered from apps, based on the preferences of the fans.

Discovering New Talent

Analytics and tracking are going to be invaluable when the draft comes around. As closely as managers may watch their players, each NHL team plays 82 high-energy games per season, making it impossible to focus on one player at a time, let alone the competition. The strongest and weakest links in each team will be evident thanks to the data.

The minor leagues may benefit from this aspect of the new tech as well. The job of talent scouts — which involves seeing hundreds of games and assessing hundreds of players every year — would be made a lot easier if smaller leagues invested in the same technology to build a database of past performance so that coaches can predict the progress of their players across seasons. Pinpointing star pro players is important, but so is recognizing future talent.

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