Many times, sports have been at the leading edge of data analytics.  The book “Moneyball” was one of the first popular books to bring the basic concepts behind data analytics and data science to the general audience.  Fantasy leagues, sabermetrics and even games like “Strat-O-Matic” baseball and basketball provided an introduction into basic statistical concepts.

And it now seems that sports, in this case the National Basketball Association (NBA), are breaking new ground with another data analytics topic: who owns the data?  The National Basketball Players Association recently banned NBA teams from using a player’s wearable data in contract negotiations or other transactions (see “NBA Bans Teams From Using Wearable Data In Contract Negotiations”).

Maybe after the bitter fights professional and college athletes had about their “likeness” being used for advertising and promotions (think College Hoops 2K8), the players association wanted to get ahead of the curve on the data ownership issue.  If that’s the case, then that’s a very smart move – and a very telling move.  It brings to light a very interesting question:  who owns the personal data coming off wearables and other “intelligent” devices, and when and how can that personal data be used?

It’s easy to imagine how the NBA owners, agents and coaches could use the wearables data.  But there is already a plethora of data available on player performance.  Do I really need wearables data to tell me that Carmelo Anthony (over-rated New York Knicks forward) doesn’t hustle back on defense (or maybe even play defense)?  I can just look at some basic statistics to uncover that insight (see Table 1)

Table 1:  Source: http://www.espn.com/nba/statistics/rpm/_/sort/ORPM

From Table 1, we can see that Carmelo Anthony ranks #35 out of 445 NBA players for offensive effectiveness; however, he only ranks #403 out of 445 players on defensive effectiveness.  Again, I don’t need to see wearables data to understand where during the game Carmelo Anthony is putting his effort and hustle[1].  Plus there are other ways to get much of the same performance and effort data, such as video analytics.

Wearables data could be very beneficial to teams and players by scientifically flagging when a player is gassed and needs a rest, or whose body might be breaking down and needs to take a game off.  Wearables data could be used to create personalized training programs that optimize an individual athlete’s strength, endurance and agility capabilities.  Wearables data could be used to minimize training injuries and speed injury recovery.  The number of ways that wearables data, especially combined with in-game performance numbers and other external sources such as weather (temperatures, humidity, precipitation), social media and location data, could improve individual athlete as well as team performance is only being scratched.

By the way, check out the twitter account https://twitter.com/strong_science for examples as to how leading edge sports teams and athletes are combining data and analytics to achieve superior player development and in-game performance.

So Who Owns the Nest Data?

In order to take this conversation to the next level, I wanted to get a feel for the privacy statements that shield our personal information from being exploited for nefarious uses.  So I checked out a sample Privacy Policy.  And given the growing explosion of in-home Internet of Things (IOT) devices, I thought I’d start with the industry leader in home-based sensors and devices…Google Nest.

Just imagine all the insights that Google Nest could glean from having sensors placed throughout your house.  Here are just a few examples of the types of insights that Nest could glean from that data:

• How many people live in the house?
• When those people are typically home during the week?
• When those people are typically home during the weekend or holidays?
• When do they typically go to bed?
• When do they typically get up in the morning?
• Is there movement during the sleep period and if so, when and where is that movement?
• When are the residents on vacation? When do they typically go on vacation?  How long are they typically gone while on vacation?
• Do they take weekends away from the home (like ski weekends) and does that correlate to any holidays or
• Does the time away from the home correlate to turning down the heat?
• And more!

Boy, the Google Nest could know an awful lot about your home living patterns and tendencies.  That could be quite dangerous if all that were to get into the wrong hands.  So let’s see how Google Nest is protecting our personal and residence data via their privacy policy.

Here is the Google Nest Privacy Policy:

Device Usage information: If you are logged into your Nest account, we record the IP address you visit our website from, and if you have a Nest device or other connected device, we record adjustments you make to the product through the website interface. We store this data along with your email address, information about your Nest device, data collected directly by the device, a history of your device settings, and any other information we have collected about your use of Nest products and services. See our Privacy Statement for Nest Products and Services to learn more about the usage information collected through our products.

Okay, so not much comfort here that my personal data is being protected and won’t be used for whatever purpose Google decides.  But here is what I found even more concerning, selecting the “See our Privacy Statement for Nest Products and Services” link took me right back to this statement.  Yea, a circular reference to a privacy statement that says nothing about how they are going to protect your information.  If you have a Nest device and are not concerned, well I got a bridge in San Francisco to sell you…

Summary

As IOT devices continue to invade our homes, cars, work areas, shopping malls, movie theaters, coffee shops, grocery stores, sporting arenas, concert halls and airports, the multitude of different organizations that “own” that data will only become more confusing.  And while that data has great potential to do good for the individual, it also has the potential for much bad as well.  This issue is only going to grow as IOT continues its meteoritic growth in all aspects of our lives.  Read a few privacy policies and you will soon realize that the only thing that separates good from bad is only a few words in a paper-thin privacy policy.

And that should scare you.

[1] Real Plus-Minus (RPM) Real Plus-Minus is meant to be predictive.  RPM can help coaches (and agents) differentiate between players who have been consistently good (and will likely keep being good) and players who are merely going through a hot streak (and will likely regress to their mean).

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