Plugged In: Glenn Ware
Glenn Ware founded PwC’s Global Intelligence Operations Center in 2008 to help corporations deal with external threats to their business. In 2013, Ware started a sports intelligence group after being hired by an NFL team and an NBA team to assess situations involving allegations of domestic violence. The sports intelligence group now works for dozens of NFL, NBA, NHL and MLB teams, helping them assess threats, as well as draft picks, free agents and other talent based on an analysis of the social media commentary surrounding players.
Imagine someone sees someone at a party doing something violent against a woman. Someone takes a photo of it. It goes viral on social media and two days later, it’s in the papers. Right? That plays out every single day. Now imagine if you had two days advanced notice. You could take intervening action to get your handle on it.”
Players’ ecosystem: The teams do a background check on the players, that’s not our business. We are looking at the larger ecosystem around a team or a player or an event that could pose a risk to a player’s team or event.
How it works: We have technology that collects social media and straight source information feeds. You may not be active on social media at all and we are not looking at your tweets or your information, we are not looking at any of that. But the people around you, your friends — you may not know this, but they are commenting on you all the time.
Talk of the town: If there is a group of say 200 elite athletes that are coming out of the 4,000 universities in the country that are being considered for this draft, each one of these are mini celebrities on their college campuses. Wherever they go around campus, people are commenting on them.
Good and bad: So you aggregate the totality of all of that, and the platform has very sophisticated algorithms that can qualitatively measure the content of those communications and they can say, “There’s a persistent theme about this player being seen at parties constantly.” Or it can say, “This player is constantly being seen as a community leader.” So it ranges from the, let’s call it, negative sentiment to the positive sentiment.
No recommendation: The platform aggregates data on volume and quantity on bad things, volume and quantity on good things. So we don’t say, “This is a really good player.” We say, “There’s this much negative sentiment. This much positive sentiment. And these are the themes in the positive and negative areas.” The team then uses it to factor into their equation on how that might affect their performance.
Game changer: What we do know is I have seen teams adjust their draft picks or not draft people or develop strategies to draft them, but they know there are negative issues that they have to deal with. I absolutely know that is happening.