Analytics Universe Blog
Sep 05, 2017 Sports Analytics Enters the Golden Age
Data Analytics Provides the Winning Advantage in Business and Sports
Everyone in sports is looking for an advantage. As it turns out, many techniques learned in Business Analytics can be applied to sports. Forward-thinking competitors are discovering their advantage in the vast amounts of newly available data. And they’re seeing transformative results on the courts and fields. That’s what “Dr. Dave” Schrader will reveal in his PARTNERS Sessions, along with his plans to grow these efforts through the Teradata University Network.
Coaches can use Sankey diagrams to see what defensive formations failed against specific offensives, resulting in explosive plays.
New Questions, New Thinking
Because so much of sports is bound in tradition, change can be a slow process. According to Dr. Dave Schrader, the adoption of data in sports is following the curve of data warehousing. “It wasn’t uncommon in the beginning to hear business people say, ‘I know how our market works, I know what we should be doing, I don’t need fancy analytics.’ And then the early adopters who bought Teradata started beating the competition and all of a sudden, guess what? Everyone wants in and the same is now true for sports.”
In sports, baseball was the early adopter. With a historic emphasis on data capture and stats and new opportunities created by the league’s Statcast video and radar systems, they have the inherent ability to collect and go much deeper to see fielder reaction times and route running efficiencies. Next, according to Dr. Dave, some basketball and European soccer teams got in the game, especially with video analytics. “The holy grail is to go from videos to automatic annotations of dots moving around in two-dimensional coordinate space. Then teams will see what pick and rolls work (a basketball play), which ones don’t, and how defenders are reacting.” While American football and hockey are starting to make good strides, Dave says it is still not uncommon for coaches to say, “I still know more about what to do than any of the computer insights.” But that’s the wrong way to think about it—it’s not either-or. The data is meant to augment your intuition, inform it, or maybe challenge it so you end up with new coaching questions.
Taking Your Eye off the Ball
From the first day of practice, players hear, “keep your eye on the ball,” which is true for the individual. But from a coaching and strategy perspective, the ball is just a single point of data. Actions that happen away from the ball could be just as critical and where data can make a difference.
Consider two American football quarterbacks. They could have statistics that appear equivalent based on the percentage of completions and rate of interceptions. What those stats don’t take into account is the duress the quarterbacks are experiencing from the opposing defense. One of them might actually deserve more credit because his offensive line isn’t blocking as well as the other quarterback’s and he’s almost always under pressure. The statistics need to be augmented to account for other players (the offensive line for example) that impact the play and should be given credit or blame when evaluating the team performance.
Where Can Businesses Learn from Sports?
Many business aspects of sports—merchandise, ticket sales, and concessions for instance—use analytics similar to other retail environments. But Dr. Dave points out that there are areas where sports are well ahead of business. “One example is Human Resources. Because athletes’ bodies are critical to their jobs, their health and injuries are carefully monitored. ‘How are you doing today? How much did you eat? How did you sleep?’ By contrast, when was the last time your boss actually did an in-depth performance review and asked about how you slept or what you ate? Or how often do you get feedback on business team metrics, or an opportunity to provide input on who to vote off the island because the team would be better? These are very serious analytics in the world of sport. In business, we are far away from that idea.”
Going Forward with Speed
One issue that has plagued both data science efforts and sports programs is the availability of resources. By contrast to professionals, there’s been a lack of awareness and a lack of funding to run analytical programs at the collegiate level in three key areas:
- Front office and fan/customer management
- Coaching tactics and strategy
- Training and injury prevention
Dr. Dave sees an opportunity for students and faculty to help their own athletic departments in these areas and has spent the past year giving talks on universities, doing what he calls “Moneyball on Campus.” “There’s something for everybody and everyone benefits. “You’ve got the athletic department giving their data to the business school, or math or computer science department for analysis. Often the athletic departments do not have the money, and usually don’t have the talent to do advanced analytics. So the students are learning applicable skills and are very eager to help, and we can show coaches and trainers some interesting insights.”
Learn more about where this exciting field is headed in Anaheim on Sunday, October 22, 1:30 – 2:30 P.M.
Sports Analytics Enters the Golden Age - Session 0236
Description: Sports analytics is a rapidly moving field and many of the business analysis techniques that Teradata customers use apply. The talk will describe:
- What’s happening around the world to collect and analyze data for recruiting, player development, game planning, and injury prevention? How are analytics being used to improve business operations—ticket pricing, sales, sponsorships?
- What analytics do pro teams use for basketball, baseball, football, and soccer? How quickly are analytics being adopted at the college level? Who is leading? What are they doing?
- Which analytic techniques used in business apply to sports? Where are there gaps? What are interesting research problems in sports analytics?
- How can other parts of any university, like the business school or stats or computer science departments, collaborate with sports programs to provide analytics for teams? What are good first projects to launch? Can we do “Moneyball” projects with Teradata University Network?
Sports Analytics Educator,
Teradata University Network (TUN)
“Dr. Dave” Schrader retired after 24 years with Teradata but has stayed involved as a Board Member of the Teradata University Network. For years, he has given Big Data and Business Analytics talks at universities in the U.S. and Germany, but now is focused on getting students excited about learning math and stats to do Moneyball on Campus projects, connecting up athletic departments with their business school students. Since the start of 2016, he’s given more than 70 talks at 40 universities to more than 3,500 students, and has launched several interesting sports analytics projects.
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