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4 Analytics Lessons From Professional Sports

Nate Silver, Michael Lewis, Mark Cuban and other sports luminaries share analytics advice you can apply to your business.

3. Master The Art Of Communications.

Marathe, the 49ers COO, entered the sports world when the legendary, late 49ers GM and head coach Bill Walsh hired him to develop an algorithm to calculate the value of football draft picks. That was in 2001, and mirroring the rise in analytics in sports over the last decade, Marathe rose in the team's ranks, eventually taking on salary-cap management, contract negotiations and all player personnel decisions.

The NFL hasn't been as advanced as MLB or the NBA in the use of analytics, Marathe said, so he had to work that much harder to communicate the value of the data-driven decisions. "It's threatening to people if they're not comfortable with analytics and some guy shows up with all these charts and graphs telling you why you need to do things differently," Marathe explained. "After five or six years, I realized that the analytical work that you do is less than 50% of the challenge. The hard part is communicating your analysis so people believe in it and embrace it."

[ How does pro basketball share its data? Read NBA Launches SAP Hana-Powered Basketball Statistics Site. ]

Getting buy-in from the owner, head coach and scouts, Marathe said, required him to constantly communicate and shape ideas so that they eventually became collective, group decisions and not just ideas from "the little Indian guy with the charts."

It's a lesson that aspiring analytics professionals in any industry must learn. Indeed, in InformationWeek's recent examination of "Top Big Data Analytics Masters Degrees," we found that courses on communicating with stakeholders are typically required and extensive.

4. Look For The Next Frontier.

The embrace of analytics isn't a once-and-done deal. The push for new measures and analyses in baseball didn't stop with the on-base percentage stat favored by Oakland A's GM Billy Beane, and it shouldn't stop with one or two hot stats in your industry.

Cuban, the maverick Dallas Mavericks owner, said basketball has "just scratched the surface" of data analyses. "We're looking to extend data capture not just in-game but also in practices and in training," Cuban said. "Unlike baseball, we have a much more difficult time developing talent, so we have to look at what can we do to gather more information" on up-and-coming players.

Another new application in basketball and other sports is in sports medicine. "It's not just for injury avoidance, but for optimal use of treatments," Cuban said. "We're doing genetic testing to determine what the best anti-inflammatories are so guys can play more minutes and play in more games."

In football, Marathe pointed to player endurance, injury prevention, player mental aptitude and in-game strategy as uncharted or nascent areas of data analysis. Another area is analysis of team chemistry, "making sure that the offensive side and the defensive side have complementary skill sets," he said. "Individually the offense and defense might be really good, but when you put them together, they might not mesh."

As Cuban observed, a city won't hold a parade for you after you rack up a really good year in business, but everyone is looking to boost performance and results. Use these pointers to improve your game.

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User Rank: Apprentice
3/4/2013 | 5:26:18 PM
re: 4 Analytics Lessons From Professional Sports

Great points. Some of your readers may not know how important the "Stick with It" point is; the first sabermetric hire was probably Allen Roth back in 1947 and the first manager to really understand the importance of developing below-market talent was Branch Rickey, the guy who hired Roth for the Dodgers. But it took another 50 years to get to the point where the A's/Beane/dePodesta were able to get to where they got.

The alignment between the structured analysis of sports and the helter-skelter world of business intelligence is one that is poorly documented, but the importance of subject matter expertise and understanding the new world of geographic/meteorological/systems-based visualization can't be understated. This is an area where business analysts could learn a whole lot from their sports counterparts; I'd be glad to chat about it more.
D. Henschen
D. Henschen,
User Rank: Author
3/4/2013 | 5:59:44 PM
re: 4 Analytics Lessons From Professional Sports
Bill James of the Boston Red Sox is another pioneer in adopting analytics that deserves mention here. James wasn't at this year's conference, but he has been beating this drum since the '70s.
User Rank: Apprentice
3/5/2013 | 2:08:48 AM
re: 4 Analytics Lessons From Professional Sports
Sports is so dominated by statistics it's sometimes easy to forget that there's some real analysis going on. I love the idea that instead of players using PEDs to overcome injuries, better treatment, more prevention, etc., will be used.
Nathan Golia
Nathan Golia,
User Rank: Apprentice
3/5/2013 | 5:53:05 PM
re: 4 Analytics Lessons From Professional Sports
Some prominent people in the NHL, like former Maple Leafs GM Brian Burke; his son, a scout for the Flyers; and NBC lunkhead Mike Milbury, have questioned the use of advanced stats in that league recently. It surprises me to still see such resistance considering the fact that teams have had success using them in both baseball and basketball G«Ų sports that couldn't be much more divergent in style. You'd think hockey executives who want to win would be all over it, but it still appears to be widely derided.

The Buffalo Bills announced the creation of an analytics department this year. Coverage of it by the local media has fallen off somewhat as we've moved into the offseason but with free agency and the draft coming it will be interesting to see what effect this has on what has been a... let's say "frustrating" team to be a fan of for 20+ years.
User Rank: Apprentice
3/13/2013 | 4:43:06 PM
re: 4 Analytics Lessons From Professional Sports
I just want to say that I really enjoyed this article. As an avid sports fan, I immediately became fascinated with the greater use of objective numbers as opposed to the old G«£eye testG«• of a player. I am a huge basketball fan and have watched for years as Darryl Morey and a host of other general managers and franchises pioneer the use of advanced statistics that they developed from the data that they collected. For example, ask the average NBA fan who the most clutch player in the league is and the answer will likely be Kobe Bryant. But statistically speaking, Kobe is nowhere in the top 10 as far as clutch play goes (score within five points and last five minutes of the game or overtime) and his effective field goal percentage is precipitously lower than those ahead of him. But people have a tendency to perceive and judge with their eyes, rather than looking at the data itself.

I think that Morey is right in that the NBA will be a completely different game in a decadeG«÷s time. Ultimately this will force head coaches to better understand the data they accumulate about how players move on the court and then it just turns into a domino effect. And, no surprises here, it all starts with improving technology.

I love that you covered this because we so frequently hear about how other industries (healthcare, government, etc.) are using these tools to analyze their data and frequently the sports story is less heard. Thanks for the great read.
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