re: Massive ESPN article on analytics - Pelicans segment

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critique on the Pelicans' moves more than an assessment of whether or not they're interested in analytics.

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It's not a stretch to look at the Pelicans moves and how they play throughout the Monty/Demps tenure and conclude they aren't really analytically driven in their decisions.

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An actual skeptic won't give two shits about that article and definitely wouldn't feel the need to try to prove them wrong

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It's a one sentence blurb in a massive article from a multibillion dollar news/entertainment conglomerate; a grain of salt is needed.

It also paints the franchise as behind the curve with the rest of the NBA. That the team would respond this way is not surprising in the least.

From Ben Alamar, former OKC and Cavs analytics consultant.

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But soon a new challenge emerged: Starting in the 2013-14 season, SportVU cameras were installed in every NBA arena. The amount of data available to teams suddenly grew from a pond to an ocean. Think about it: Those cameras capture the coordinates of 10 players plus the ball 25 times every second. That's a vast amount of data. As a result, the race to unlock the secrets of the SportVU requires a much higher level of skill than what was needed when I first started working for the Sonics. In the beginning, anyone with advanced spreadsheet skills could probably add value to a front office. Now, though, deep statistical programming skills, along with advanced computer science knowledge, are needed to create value. These are skills for which companies such as Google and Facebook pay quite handsomely.

But teams have been slow to recognize the sandbox they're now playing in. The analytics community worked hard to be accepted and learn the language of the NBA, but maybe we did too good a job fitting in. Entry-level analysts are viewed not much differently from entry-level video assistants: lucky to be in the NBA and worth a salary not much higher than $35,000. Teams are used to competing with high school and college athletic departments for staff, not with McKinsey and Bain. Realistically, aspiring NBA analysts must be willing to take at least a 50 percent pay cut from what they could earn elsewhere.

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Some teams are starting to figure it out -- some even are raising salaries -- and departments are growing in number. And thanks to new streams of data, there are whole new languages to learn -- the biggest advantage will go to teams that want to learn them

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Like I said earlier, everyone uses advanved stats. Per 36, %, etc. They're just modified box score numbers.

The camera data is a Pandora 's Box. That's what is interesting. How willing is the team to go out and spend $$ to discover an edge?There are teams pouring $ into exploring this mountain of information. You can call it self promotion. Just seems like a wise investment to me.