5 Aggressive Plays in Sports Analytics


In the runup to the NCAA's March Madness tourney, the guys in my house have been watching lots of college hoops. I usually don't join them, but even if I'm just listening to a game with half an ear, I'm sure to get an inundation of statistics-related commentary.

A lot of these stats are superficial, really -- basic stuff like number of games played, steals, and assists -- that any diehard fan could rattle off easily. Knowing the number of three-point shots attempted and the percentage made isn't going to get any team a competitive advantage.

Every sport has these sorts of basic insights on player and team performance, and many teams are applying them in the aim of picking the best players, putting together winning teams, and making sound decisions on the court (or, as I mentioned yesterday, on the field). These are "table stakes" in sports performance analytics, Tom Davenport writes in "Analytics in Sports: The New Science of Winning," a February International Institute for Analytics research report sponsored by SAS (which also sponsors this site).

Tom Davenport
Tom Davenport

In his report, based on a series of interviews with professional sports teams and vendors in the US and Europe, Davenport identified seven types of table-stakes analytics: use of external data sources, descriptive analytics on players, optimal lineup analytics (basketball), player scoring for draft analysis, player salary optimization, simulation of games, and analysis of game tactics. Teams need strong players and good coaching to win, but these analytics "have certainly become established as important augmentation for those basic success factors."

But let's look ahead to the types of player and performance analytics that are not quite so common yet. Davenport called out five "frontier" analytics applications and said that only a few teams are using them aggressively today. Could these applications really open the playing field, so to speak?

1. Analytics on video
Davenport called video the frontier source of data across all sports. Major League Baseball (MLB) and the National Basketball Association (NBA) have standardized on video capture services, which eases the pain of tagging and editing the video content for analysis. Other leagues, such as the National Football League (NFL) and the National Hockey League, haven't standardized on a video vendor, so teams are left to address the tricky tasks of editing, tagging, and analyzing video on their own. Regardless, the level of analytics here varies, from the simple tracking of descriptive analytics like ball touches and rebounds in basketball to the highly complex analysis of, say, how often a particular player goes left when driving toward the basket from the free throw line.

2. Analytics on location/biometric data
This includes data from GPS devices, radio frequency devices, accelerometers, and other types of biometric sensors. While the location data allows you to assess total activity, like miles run or steps taken, biometric data gives information on physical activity. "It's also possible to use this type of data to understand interactions between players, but this will require greater sophistication in data analysis," wrote Davenport, who will address this topic, among others, during a session on big data in sports at the MIT Sloan Sports Analytics Conference tomorrow.

3. Gathering and using proprietary data on players
Player and team data is readily available from leagues or external vendors, but a "few highly analytical teams... gather their own proprietary data, or adopt technologies that produce it." These teams include the NBA's Houston Rockets and Orlando Magic; MLB's Boston Red Sox and San Francisco Giants; and the NFL's New England Patriots.

4. Engaging players in analytics
A lot of sports experts, coaches among them, see no value in sharing analytics with players about how they or their opponents perform. However, showing players the data shouldn't be ruled out in all cases. Davenport cited some notable examples, including Patriots quarterback Tom Brady and Brandon McCarthy, a pitcher with MLB's Arizona Diamondbacks.

5. Open data analysis by fans
What's new here isn't the use of fan data, but the actual sanctioned use of such data or even the hiring of fans by teams. As one extreme example, Davenport cited Manchester City of soccer's English Premier League. "That organization has partnered with its primary data provider Opta to make all player performance data from all EPL clubs available for analysis by fans and researchers." To date, 5,000 fans have downloaded the data.

That last frontier is one of the most intriguing to me, pointing as it does to the sheer volume of data being collected on individual and team performance. Who wouldn't want a little help in analyzing it, especially if management isn't on the same page as coaches with their understanding of and desire for analytics? But which of these frontier analytics applications strikes you as the most interesting? Do you think any might provide a competitive advantage? Share below.

— Beth Schultz, Circle me on Google+ Follow me on TwitterVisit my LinkedIn pageFriend me on Facebook, Editor in Chief, AllAnalytics.com

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Beth Schultz, Editor in Chief

Beth Schultz has more than two decades of experience as an IT writer and editor.  Most recently, she brought her expertise to bear writing thought-provoking editorial and marketing materials on a variety of technology topics for leading IT publications and industry players.  Previously, she oversaw multimedia content development, writing and editing for special feature packages at Network World. In particular, she focused on advanced IT technology and its impact on business users and in so doing became a thought leader on the revolutionary changes remaking the corporate datacenter and enterprise IT architecture. Beth has a keen ability to identify business and technology trends, developing expertise through in-depth analysis and early adopter case studies. Over the years, she has earned more than a dozen national and regional editorial excellence awards for special issues from American Business Media, American Society of Business Press Editors, Folio.net, and others.

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Re: Biometric data
  • 3/2/2014 8:20:03 PM
NO RATINGS

@bulk    I see.  Thanks for the explanation.  Biometerics has merit for sure, probably more science than I want to apply.  But if I had millions resting on it - as Beth mentioned earlier - I would probably think differently.  

I appreciate you taking the time to bring me up to speed ( no pun intended ) on this topic.

Re: Biometric data
  • 3/2/2014 12:45:36 PM
NO RATINGS

There have been a lot of rumors that Apple is looking to take their smart watch in the health monitoring direction, they have even meet iwth the FDA. But those are just rumors and no one will really know until it launches. 

Re: Biometric data
  • 3/2/2014 12:37:43 PM
NO RATINGS

Whatever they do to make the iWatch stand out will be fascinating to see. Apple needs a big hit right now, and I'm not fully convinced smart watches are that hit.

Re: Biometric data
  • 3/2/2014 12:35:25 PM
NO RATINGS

I think we will definatly see an Apple smart watch, but when it comes out it will be unline anything else on the market. 

Re: Biometric data
  • 3/2/2014 12:21:28 PM
NO RATINGS

With Nokia seemingly spearheading the popularity of Windows Phones, it would appear anyone can pop out of the woodwork. I also see Apple doing just that, their own thing. They like to refine an idea and have it copied, so smart watches might not be on their itinerary.

Re: Biometric data
  • 3/2/2014 12:16:12 PM
NO RATINGS

@CandidoNick, I agree that the smart watch will being to play a greater roll in our lives. However; I do not think Samsung will lead the way, they were first out the gate of the major players, but I think we will see third parties rule in this space. Apple might do their own thing, and be hold ground in the apple sphere but I think the small players will run with this ball. 

Re: Biometric data
  • 3/2/2014 12:12:28 PM
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And with the rise of smart watches led by Samsung, were going to be seeing more and more people with multiple devices that MUST be replaced every few years, charged daily, and hold weight in our lives. The idea of electronic apparel is truly gaining steam.

Re: Biometric data
  • 3/2/2014 2:34:29 AM
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@Louis, 

If someone has pushed themself to the point of total fatigue and are out of breath that is far different then their heart rate being maxed out. Top athletes train to improve their performance and knowing where your peak heartrate is and being able to sustain or lower that number is keep to perforamance fore endurance athletes, also being able to track and monitor resting heartrate is key to measureing recovery and overall improvement. being able to use biometrics to capture this data in real time and apply that knowledge imediatly can be used to imoprove overall training in athletes. and help them perform at higher levels for longer times. 

Re: Biometric data
  • 3/2/2014 2:00:23 AM
NO RATINGS

@Beth, I think that might be the only way to come close, it seems like there are a lot areas where this might get tricky for them. Of course I guess they could always just have all the player sign waivers and that would take care of it. 

Re: Biometric data
  • 3/2/2014 1:56:54 AM
NO RATINGS

Pierre, you are right on point with that assumption. Nike is already making movies in that direction, their FuelBand is a consumer focused wearable fittness tracker and the Hyperdunk are smart shoes with sensor intergrated to capture performance data. I would say there is no doubt we will see them move towards intergrating more advanced tech into their exisisting product line. From the consumer sie it has a built in upgrade roadmap, when your current shoes have hit the end of the road its time to get new ones with upgraded sensors. 

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