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This excerpt is from Sport Techie. To view the whole article click here.  

9 years ago
Analytics Is Playing a Bigger Part in The Game

 

Analytics is a hot topic in sports today. Pro teams and leagues are on the look out for new ways to use analytics for a plethora of decision making instances — from improving the fan experience and building sponsorships to making better draft picks and predicting injuries.

Everyone recalls the Moneyball story about how the Oakland A’s used analytics to create a winning team for the 2002 season. For many, that story was an eye-opener on the power analytics had on player selection. But a lot has changed since then. Today, teams are turning to analytics to answer tougher problems and mine unprecedented mountains of data. Here is a quick look at a few of the roles analytics plays in sports both off and on the field.

Getting closer to fans and building sponsorships

Fan loyalty is everything in the sports business. The more a team knows about its fans, the better it can connect with them and build loyalty. Sports teams today are using analytics to dig deeper into fan preferences and behaviors, so they can target their marketing efforts with laser precision.

Consider Major League Soccer (MLS), the top pro-flight soccer league in the US and Canada. MLS has been creating a data warehouse, merging fan data from all 19 of its soccer clubs and its many CRM and ticketing systems. Now MLS is using analytics on that data to get to know its millions of fans and create personalized campaigns to increase ticket and merchandise sales and build lifetime loyalty.

Segmentation also plays a role in sports. By combining variables, such as game attendance, purchase of team merchandise and attendance at season events, teams are grouping fans based how likely or unlikely they are to renew season tickets. By targeting ‘fence sitters’ with personalized content, they are able to increase retention rates. Further, teams can analyze how often fans click on emails to fine-tune approaches. Some teams are even beginning to use analytics to mine unstructured data on social media sites.

Professional teams and venues are looking for ways to use their fan data to engage during events.  Many venues already have iBeacons and Geofence technologies in-place.  By combining knowledge of fan preferences and behaviors with geo-location and predictive analytics, teams can deliver the targeted content to fans in real-time during an event.

Sponsorship is another main source of revenue for sports teams and leagues. Sports teams are looking for new ways to use fan information to build a better story for their partners on why they should invest. Analytics is beginning to play an integral role in building that story.

Better draft choices, unique training schedules and injury prevention

Like in the Moneyball story, analytics has the ability to play a key role in making smarter, better draft picks. But analytics also plays role in optimizing player training. Teams pay big money for players, so the last thing they want is for a player to get injured on the field.

What’s changed since Moneyball is today, teams are collecting massive amounts of player performance data — more data than they know what to do with.

Soccer teams in Europe are putting wearable technology on players to track speed, location, distance run and even collect biometric data, such as heart rate and temperature. Since the 2013 season, all MLS teams in the US started to use the Adidas miCoach Elite system for data collection.

In pro-basketball and baseball, where unions are against wearable devices, the focus is on viewable data. If you go to an NBA game and look up, you are likely to spot six SportVU cameras in the rafters.

At this point, the teams are still looking for novel ways to use the thousands of data points they collect during each game. This is where analytics comes in.

In addition to helping teams develop unique training schedules for players, analytics is also being used to predict when players become susceptible to injury. By combining data collected on the field with variables like fatigue, stress, sleep, training intensity and nutrition, teams are starting to uncover hidden trends that cause injury. Many experts believe this to be the future of advanced sport analytics.

Entering a new realm in sports

This excerpt is from Sport Techie. To view the whole article click here.

By: Guest Author, www.sporttechie.com
Originally published at www.sporttechie.com

3 thoughts on “Analytics Is Playing a Bigger Part in The Game

  1. Analytics has indeed become indispensable in modern sports. From enhancing fan engagement to optimizing player performance, its applications are diverse and evolving. While Moneyball popularized its impact, today’s teams delve deeper, leveraging analytics for intricate challenges like injury prevention and sponsorship optimization. With advanced tools and data accessibility, teams explore innovative strategies. Yet, amidst this evolution, one constant remains: the pursuit of competitive edge, now facilitated by analytics tools accessible to use at no cost.

     
  2. The integration of analytics in sports has fundamentally reshaped how teams operate, extending far beyond player selection. While the Moneyball narrative highlighted its early impact, contemporary sports analytics delves into multifaceted realms. Teams now harness data to refine marketing strategies, tailor fan experiences, and negotiate lucrative sponsorships. Moreover, analytics informs training regimens, injury prevention protocols, and in-game tactics, offering a holistic approach to performance optimization. This evolution underscores the indispensable role analytics plays in driving success across all facets of modern sports management.
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