Huge Effects of Analytics on NHL

Big Data and analytics are changing the sports landscape. Steph Curry epitomizes this change in the NBA, where the game turned to shooting a high volume of threes and making centers more or less obsolete. Likewise, many in-between game concepts are no longer relevant in baseball, and players focus on home-run or out. There are similar examples in many sports, and NHL and hockey are some of the last bastions turning towards analytics.

Fast-paced Spectacle

Players in hockey skate at 35 m/h speed, and the puck flies over 100 miles, making manual statistics challenging, but the development of numerous sensors in equipment changed the game for good. Tracking devices are now inside the puck, on the player’s shoulder pads, and another tech creates a surplus of data for analysis. The league leadership wants to use data-driven analytics to improve the experience, give fans another layer, and thus increase revenue.

Igaming companies are welcoming these developments, as well as users.
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With precise data on how much each player skates, his and team’s in-depth performance, users can enter their sports betting lobby here with much better insight on who will emerge as a winner in upcoming matches and during the game for live betting.

Help for Coaches and Players

Evaluating a fast-paced sport like hockey isn’t easy, even for coaches that spent countless hours by the rink. The coaching staff will still have their gut feeling and eye-test evaluation, but now with big-data analysis of over 2000 data points, coaches and managers can make data-driven in-game adjustments. For example, skating speed and covered space can indicate fatigue before players can sense the exhaustion. Data can help with training and gameplay. 

With extensive data analysis and AI algorithms, managers can improve schematics, create better movement, press tactics, and focus on what works best on ice to get the desired result. 

Another crucial possible use case is injury prevention, where sensors and exported data can hint at the coaching staff before a high possibility of injury is coming.  Such predictions, with the help of machine learning, can make hockey safer.
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Broad use of analytics in minor leagues and younger players can lead to better scouting. With the help of tracking analysis, you can spot better skaters, detect specific skills transferable to pros much earlier in player careers.

More Entertainment for Fans

The audience can benefit from big data analytics on two fronts. First, the home TV audience will have an in-depth overview of player performance with various statistical categories displayed during the game. Second, imagine goals replay with additional info on distance, speed, and other variables that come into play with scoring a goal. 

Analytics can boost arena attendance with engaging implementation in mobile apps. Applications on smartphones for sports venues are becoming a norm.
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You can get tickets, purchase food and drinks, and the app can introduce all the tracked data and statistics about the player, team and match to the fans. 

Countless data-point and automatic statistics make manual input obsolete, and the depth of the information improves player training, coaching and user experience for fans.