The evolution of sports data - an interview with Christian Holzer


by Ben Tobin & Marco Lorenzi

How has the collection of sports data changed? How does its application feed into decision making? And what’s next for the sports data industry? Christian Holzer, Managing Director at Deltatre AG and Sportec Solutions - a joint venture between Deltatre and DFL - has his say


by Ben Tobin & Marco Lorenzi

How has the collection of sports data changed? How does its application feed into decision making? And what’s next for the sports data industry? Christian Holzer, Managing Director at Deltatre AG and Sportec Solutions - a joint venture between Deltatre and DFL - has his say

Sportspeople and sports teams analyzing games to try and gain an advantage over their opponents is nothing new. The collection of statistics, instrumental in enriching the broadcasting experience, is now an ace up the sleeve for clubs and teams who are using it to start building the algorithms of success for football.

We sat down with Deltatre’s Christian Holzer, Managing Director at Deltatre AG and Sportec Solutions, a joint venture between Deltatre and DFL. Starting with the history of sports data, to how this its use is changing the game today, he painted a picture of what the industry will look like over what promises to be an exciting decade.

“When talking about clubs, one of the primary goals is to increase performance. Each entity is seeking improvements at different levels of their operation. A number of tools have been introduced to help collect the data that helps drive this, and over the last few years the depth of information available to sports teams – whether that is coaches, players, medical staff or recruitment – has been revolutionary. It has heralded a new era of sports data collection and implementation.

What’s more, this data has helped broadcasters, journalists, businesses and fans attain greater insight into what is truly happening within the games they report on and enjoy. There has been huge, continuous growth in match analysis. Initially, it was almost all about visual observation - what can we see is happening? However, increasingly technology has played a more significant role in supporting this process with the sole aim of improving the game.”

How can sports entities monetize the amount of data that’s collected and analyzed?

“Monetization opportunities can be divided into non-direct and direct channels. An indirect way of monetizing the data is looking at this from a performance angle. Sports teams and players long to answer two simple questions; how can strengths and weaknesses be identified? And what can be done to win? Success naturally brings more opportunities to increase revenues for clubs and athletes.

"A more direct way of monetizing data sits with storytelling. Data is used to create and enhance content that engages audiences - for instance, by feeding this into a live video player for on-screen statistical visualizations. The biggest challenge comes in identifying the right messages contained within the mountain of data on offer. Today this is primarily through human-driven intelligence however, we expect a greater emphasis on the use of artificial intelligence (AI) in the future.”

Is that the reason why today there is a broader debate about how much trust we should put in data?

“It is. A coach might simply believe that a player isn’t good enough based on what they’ve witnessed either in training or during the 90 minutes of play in a football game. In this case, they may think there’s no need to look to data to confirm or counteract what they feel. Both human and artificial intelligence should work in harmony, complementing each other to give a richer and more complete picture.

"If a coach or scout believes a player does not have the right playing style, for example – can this be confirmed in the data? Similarly, data can be used to uncover things a coach may not be aware of.

"As part of our work as Deltatre and at Sportec Solutions, thanks to our comprehensive data capabilities, we’re able to showcase long-term trends such as passing patterns and tactical behavior. For instance, we can show if two people on the same team are reluctant to pass to one another or how offensive playing patterns are developed. Using this information, the coach can then analyze at a deeper level - are there any topics that are preventing success? And if so, can they be fixed for the good of the team?”

How does Deltatre position itself in this challenging ecosystem?

“As Deltatre, we operate in several ways. We do provide clients with our Data Gathering services, Data Storage, Data Analysis and finally, Data Distribution. And, of course, there is the storytelling itself. We analyze, curate and prepare data for its distribution to fan-facing products. We’re committed to helping our clients find the ‘gold nuggets’ in the data that will enrich the fan experience for their end-users.

"Once the data is in hand, we’re also able to provide our clients with broadcast and digital graphics and feed them into production systems, helping to automate editorial workflows. Deltatre has more than 30 years of experience in data storytelling, and our competitive advantage is the reliability and authenticity in working together with our clients. We are trusted as we provide the technological architecture for them to improve their own offering throughout.”

How are clubs and federations approaching the monetization of their own assets?

“It’s already a reality that some of the big leagues, such as the DFL/Bundesliga, owns its own official match data. Operators can buy the license to that official match data, representing direct commercialization of those assets. Licensees receive the use of that raw data - which still needs to be analyzed and curated - as part of their broadcast rights packages.

"However, it’s important to note that this is raw data we’re talking about; it needs work to be made ready for the end consumer and this depends on the objective the broadcaster has in mind. It could be greater editorial storytelling or graphics for TV transmissions."

What’s next for the sports data industry?

“In the future, there’s no doubt that technology will continue to improve player performance, broadcaster capabilities, and fan enjoyment. Just think of AI and the opportunities it presents.

"For teams and players, there is a chance to improve on game preparation and analysis. Think of a defender preparing to play against a league’s leading attacking player – what can AI tell you about the opponent’s playing style and tactical movements, and how can the defender adjust his game to counter this?

"For broadcasters, it will be possible to give fans a greater level of immersion and involvement in the live experience than ever before. And it’s not just football. Different sports have different challenges, and there is no one single data point that a team should focus on. For example, in football, the game flows more and is less rigid in its play, compared to baseball or cricket, in which the same fundamental repeated action occurs. Analysis needs to reflect this, and different patterns need to be identified.”

What do you think will be the next big thing in sports data? Join and tell us your thoughts on Twitter or LinkedIn.