Brian Josephs: Insightful Data Empowers Consumers and Improves Modern Sports Coverage

Sportradar’s Vice-President, Digital Sport, Brian Josephs, was a participant on the recent ‘Finding the Favorite: Engaging Fans and Bettors’ panel at the MIT Sloan Sports Analytics Conference alongside Doug Kezirian (ESPN), Zach Leonsis (Monumental Sports), Scott Kaufman-Ross (NBA) and Chad Millman (The Action Network). Prior to the event in Boston, Brian put together the blog below, analysing the role data is playing within modern sports consumption.

It’s no secret that sports consumption has changed. For years, the qualitative data suggested fans of all US leagues had a growing appetite for the sports, but a dwindling attention span when it comes to viewing habits. The question is – what can leagues and media companies do about it? How can you effectively capture the time and attention of sports fans? 

The answer? Deliver timely, relevant, personalized content.

As the tide in fan behavior shifts, so has the role of data. Now, as attention starts to focus on “moments,” there’s a need for additional context and insight to tell a more complete story that engages the consumer. Let’s say a player hits a basket. On current data feeds, you’ll see that player scored a three-pointer, and that their team is now winning by a certain score.

But why else was that basket important? Why else should a fan care?

If you go another step further, you can uncover that the player now has a career-high for points in a game, and they’re tied with a franchise legend for second on the team’s all-time scoring list. In addition to just traditional stats, end consumers are looking for “newer” data sets, such as tracking – that point was the player’s furthest make of his career – or betting – the team is -250 to win the game, and the player covered his pre-game prop with that point.

This transition from sharing what happened to providing context, or explaining why it happened, will unlock a golden opportunity for media companies, tech platforms, and others to more deeply engage sports fans with a range of motivations for tuning in.

At Sportradar, we’re analyzing our global database of official boxscore, betting, historical, and tracking data to compile it into a workable format, create logic that watches for certain interesting contextual elements, and then in real-time, when they happen, create outputs that contain everything from the data itself, to text and relevance metrics. We prepare the insights pre-game, so we’re able to say that a player is closing in on another player on the team’s scoring leaderboard, before it actually happens. This is in addition to the insights that we generate during and after the games.

Betting insights are an especially interesting area, where there is a rapidly increasing demand from the media marketplace. As legalized sports betting rolls out across the US, a growing number of sports fans will want to know when books are moving their lines pre-game, so that they can jump on opportunities for the best odds. This will also lead to interest in data surrounding market insights, which have basic outputs like how a team has done against the spread over their last five games, as well as more complex insights, like how many times a team has gone over on the road following a win, in the last five seasons.

As a fan, you can imagine the different forms this underlying data can potentially take. One great example is ticketing companies. Currently, ticketing companies offer limited pre-game information; just basics like location, opponent, and tip-off time. When a ticketing company implements a feed that includes these deeper insights we’re talking about, they’ll be able to tell fans that are looking to buy tickets that a seemingly normal game actually has a chance to be quite special because their favorite player is about to break a team record that has stood for 50 years.

On the broadcast side, what was previously done manually by research teams – things like assembling pre-game insights packages – can now all be automated, and fed directly into graphics engines or research tooling.

On the OTT side, any streamer of the game, from the rights holder to a vMVPD to the device itself can start to ingest insights to power experiences such as in-depth personalized alerting or overlays.

Editorially, there are user-facing UIs that allow writers to see all of the insights, so they can in turn be used in their journalistic pieces or on social media.

The list of use cases go on and on, but at the core, the idea remains the same. As the demand for snackable moments by sports fans continues to grow, so too will the interest in a new level of data and insights that help tell a deeper story behind the sports they love. Will you unlock the potential of this data to engage your audiences in these moments of time, or will you let the opportunity slip through your hands?

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