NEW YORK – When Germany defeated Argentina 1-0 to capture its fourth FIFA World Cup championship last year in Brazil, it accomplished something most soccer aficionados believed to be impossible – a European nation winning the World Cup on South American soil.
The Germans did not just win the World Cup, they dominated the entire tournament. The team did not lose one game; it only allowed four goals against. They defeated the host nation and five-time champion Brazil 7-1 in the semifinal. And, in that final match, they beat an Argentina side featuring the world’s best player in Lionel Messi.
Besides fielding an all-star team led by Captain Philippe Lahm, the German Nationals came into the 32 team tournament with something no other squad thought to bring: sports science technology developed by SAP SE.
The German National team worked with SAP to see if the enterprise resource planning (ERP) giant could help them win more games, said Frank Wheeler, general manager of SAP’s sports and entertainment group. In turn, Wheeler wanted to know if the German team had a data strategy. Together, they developed a match insight solution that is now a commercial product called SAP Sports One.
“It’s a secure end-to-end platform for sports teams,” Wheeler said.
The Sports and Entertainment group at SAP has only been around for a short time, but Wheeler has already discovered that while teams do not deal with super-sized data, they do handle information in many different forms including game performance, injury, and the overall fan experience.
Wheeler added that 85 per cent of the money earned from sports teams are put back into improving the product on the floor, field, ice or court. More teams are hiring data scientists to properly analyze the information they have. The thinking among sports teams is that it can provide a level of competitive balance.
What the German team wanted was to be better prepared for the World Cup in Brazil and deliver on the result it wanted – a championship.
One of the reasons for Wheeler’s data strategy questions is that SAP has realized the $100 billion USD sports industry is no different than any other vertical going through a digital transformation; the four mega trends of cloud, mobile, big data, and social media have also hit the sports world in a big way.
Teams such as the New York Giants of the NFL and entire leagues like the Women’s Tennis Association (WTA) have taken the approach of the German National team to see if big data can provide a competitive advantage. Sports apparel companies such as Under Armour Inc. are also investing heavily in data capture and analytics to bolster its line of products not just for the high-performance athlete, but to all middle-aged joggers who want to be healthy and fit.
SAP has gone so far as to create the Digital Athlete Framework, based on SAP HANA, to provide a platform for teams, players, and companies in the sports industry to access big data and sensor technology in a meaningful way.
Under Armour
At Under Armour Inc., the company has always looked at ways to make the consumer feel better and look great, said Kurt Kendall, global head of engagement at Under Armour, attending the SAP Spotlight tour.
The Baltimore-based company has recently spent more than $710 million USD acquiring MapMyFitness, MyFitnessPal, and Endomondo three digital app vendors to spruce up its focus on big data and the Internet of Things.
According to Kendall, Under Armour took to redefining its customer base from athletes to global consumers. “We realized who we were helping with our products and changed the focus to transform our apparel business into two – a digital business and a fitness business,” he said.
Wearable technology is a key part of its future strategy. Under Armour has developed a workout shirt called E39 that features sensors; these devices measure heart rate, metabolism, body position, and lung capacity. The data can be collected and displayed to coaches, trainers, or an individual who can then develop a personalized workout routine that could potentially reduce injuries.
Kendall said in five to 10 years, enhancements to wearable technology will become seamless to the users and be part of a natural data collection process for an improved experience.
New York Giants
The New York Giants of the NFL are also looking at how wearable technology can improve the win/loss record of the team. Kevin Abrams, assistant general manager of the New York Giants, is responsible for analytics and his approach is to use big data as a form of injury prevention and wellness for 58 players on the squad.
He said the Giants have made investments and devoted more resources on wearables that focus on player performance and injury.
The team, for the most part, evaluates players at 18 years old and again at 26. At 18, they have started their college football careers and by 26 they could become a free agent. The data captured on these players provide selling points to the decision makers in the football department at the Giants.
But there are barriers to collecting this data not just for the Giants, but for every other NFL team. Since all 1,700 players who make an NFL roster in any calendar year become members of the NFLPA union; Abrams needs to ask permission from the NFLPA on which areas of personal data he can collect. All of this needs to be collectively bargained by league officials and the leaders of the players union, he said.
WTA
Football may be one of the most heavily coached sports in the industry. On the opposite end of that is the game of tennis.
For the longest time coaching was not allowed in the sport of tennis during a match. The WTA in 2009 changed that rule to allow on-court coaching. However, it’s only permitted during 90-second breaks. Kathleen Stroia, senior vice-president of sports science and medicine for the WTA admits that’s not a lot of time.
Working with SAP, coaches in the stands can now access the patterns in play on a tablet device. Tennis coaches can analyze where the ball is being hit and compare that to the opponent’s patterns and suggest modifications.
Adapting technology to tennis has been an enormous challenge for Stroia. Big data, in its current form, has not been useful mainly because of the unique movements made by tennis players.
She hopes to develop new methods for training, measure recovery time from injury, and produce specifics to a player’s own game in the near future. The WTA is experimenting with tracking racket speed and how it relates to performance and injury along with other measurables such as length of point.
“We want the data to be individualized, not just put out on a database,” she said.
One area where they did improve was with tennis shoes for the women players. The sport shoe manufacturers did make footwear specific for females, however not in all sizes. Some players wore men’s shoes, which are heavier, Stroia said. WTA along with the sport shoe manufacturers have since corrected it.
A common theme at the SAP Spotlight tour was that data can be used effectively for preventing sports injuries.
For Bill Seringer, a clinical supervisor at Stanford Health, big data can lead to injury prediction methods.
He cited that one of the reasons for the Golden State Warriors winning the NBA Championship in 2015 over the LeBron James led Cleveland Cavaliers was the fact that they had the lowest injury rate among NBA teams. The Cavaliers, meanwhile, lost two of their starters in Kevin Love and Kyrie Irving in the final series against the Warriors.
Seringer has determined that 15 to 30 per cent of a team’s cost can be associated to injuries.
However, more work needs to be done and it’s one of the reasons why Stanford Health, as part of the University of Stanford, has partnered with SAP and is HANA platform.
“We are good at collecting the data, but we have no idea what to do with it,” he said. Seringer said Stanford Health and SAP are working collaboratively on new ways to get information to the right people, but the user experience with data needs to be simple.
“Big data needs to come down and become sure data if we want to elevate the experience,” Seringer said.
Notre Dame Sports
The Fighting Irish of Notre Dame has a reputation of producing some of the fittest athletes in college sports. Most people recognize the school’s football team from the hit movie Rudy, but Jack Swarbrick Jr., vice-president and director of athletics for the University of Notre Dame is responsible for 26 different sports teams that represent the school.
Part of his job is to break down big data for the many coaches and trainers of those teams. He outlined at the SAP Spotlight Tour three areas for big data in sports. They include:
- What data do you want to collect? What are the key pieces coaches are looking for instead of a swimming pool of data?
- Marry the data up to subjective data; an example of this is data capture on a player during practice could be meaningless if he or she was suffering from the flu
- Converting the data for a coach
“The third piece is the most challenging because most coaches can only handle two pieces of data and smart coaches can do three,” Swarbrick said.
One of the newer conclusions Notre Dame made from analyzing big data came from the sleep patterns of student athletes. Swarbrick said sleep is an important predictor of performance and possible injury. With this knowledge, the University began to prepare hotel rooms with customized pillows for the players to provide them with better sleep Big data has changed the way Notre Dame treats the student athletes. Swarbrick said five years ago players never asked questions such as “how are you going to make me better?”
They do now.
College-age students today have grown up in the connected world, said Greg McStravick, global general manager and head of SAP’s databases and technology group. Students, he said, are digital and are demanding data and analytics. Swarbrick is also working with SAP and the HANA platform to develop a new system for capturing and managing data for the student athlete. He called it a CRM for students that can track statistics from the time the players are 14 or 15.
The challenge for him, along with the coaches, is to present this data on a single platform where they can see everything.