The Advent of Big Data in the NHL

big data in the nhl
KUOPIO, FINLAND - AUGUST 21: Big tackle between rival players during the Champions Hockey League game between KalPa Kuopio and Sparta Prague at Data Group Areena on August 21, 2014 in Kuopio, Finland. (Photo By Atte Rissanen/Champions Hockey League via Getty Images)

A new era in the NHL is upon us! The league officially announced that this season will usher in the fabled trackable puck. This has been planned for almost 25 years and has taken over five years of actual development. It will bring in a new way to track data and will undoubtedly change the way the game, teams, and players are evaluated.

Big Data Arrives in the NHL

Hockey has been slow to embrace new technologies, but the NHL’s acceptance of big data will give managers and fans the same wealth of analytics information that has transformed other sports like baseball, football, and basketball.

Technology is being implemented inside of pucks to collect data. But that isn’t all. Chips will even be put into players’ shoulder pads and there will be data sensors all around the actual hockey rink. David Lehanski, Senior Vice President of business development at the NHL, is hoping that it can improve fan engagement and drive revenue for the league.

But beyond just making money for the NHL executives and owners, the data collected will be able to be used to help players improve their game, coaches better their strategies, and scouts better evaluate current and potential pro players. Overall, the technology will give everyone a better understanding of just what goes into playing professional ice hockey.

You can see some of the statistics in the infographic provided by NHL Lines site Betway:

Performance Assessment in Real-Time

Ice hockey is one of the world’s fastest sports. The sheer speed at which the game is played makes it difficult to see the full picture of what’s going on at any given time. The most immediate benefit of big data is the abundance of analytics information it provides to the players, managers, and coaches. The sensors, chips, and tracking devices that will be implemented across all facets of the game provide about 2,000 data points per second. Information on puck speed, player possession, distance skated and many other metrics are live-streamed directly to managers’ devices throughout a game.

One major benefit of rink-side management being able to access this data in real-time is that it allows them to have better control over players during the games. If someone looks like they’re flagging, coaches can check the data to see the extent to which they have overexerted themselves and substitute them if they need to.

Aggregating this data across an entire season can also help inform which players to play depending on the situation. This might be further enhanced by the introduction of AI. Using bots to follow regularly-used plays will help AI algorithms learn how plays should work, and provide detailed information on how to make improvements if they ever go wrong.

Improving Player Health

One booming business outside of professional sports it Fitbits and wearable health devices. However, they are just as valuable in sports. A trackable puck can guide tactics and in-play decisions, and sensors within shoulder pads can provide vital data for monitoring player health and fitness. Information taken during games can feed into specialized training regimes for each player. Then additional wearables used during training can provide an even clearer picture of how to maximize player performance on the rink.

Considering its reputation for violence, there are few places where this information is more needed than the NHL. Statistically, about 51 per cent of players have missed a minimum of one game as a result of injury each season. This stat has the potential to decrease with this new technology, as it can compile data that will be able to anticipate injuries and allow coaches and players to adjust to prevent them.

Drawing Fans Back to the Arena

Although the league is projected to see a large increase in revenue from network broadcast deals, they are still having issues getting people to fill seats in actual hockey arenas. In-game attendance has seen a declining trend for the past few seasons. But, big data could be a tool to draw people back off their couches and into the arenas.

Most other professional leagues have already started feeding live audiences with the data being collected during the games, providing fans in attendance with a much more engaged feeling than in the past. The NHL is also looking to take advantage of this. Having on-demand access to data on each player and play could be a godsend for a game where teams skate at an average of 20mph. This info could be what hooks fans in. In fact, an app could serve as a one-stop-shop for all game information, from parking availability to seating charts, or even the location of the nearest bathroom.

Most uses of big data revolve around improving advertising opportunities, and data gathered from the apps will give the NHL a better idea of who’s coming to the games to support which teams. As a result, they can tailor their sponsorship—whether that’s rink-side or even down to minutiae like the fastest shot of the game—to the preferences of their fans.

Scouting Prospects

With each team playing 82 games per season in the NHL, it can be near-impossible to focus on one player at a time. Because of this, data analytics and tracking could be a godsend when it comes to transfer season, as it can give competing managers a much better idea of who the star player is in any given team, and help them to make offers accordingly.

This will likely also trickle down to the minor leagues. Scout teams already see hundreds of games a year and attempt to assess an even higher number of players to see if they are ready for the pros. This makes finding talent a very difficult business. But, if the tracking systems work for the NHL, they could pave the way for smaller leagues to invest in similar technology. From there, it would build a database of past performance which will help coaches predict how players will progress in the seasons to come.

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