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which plays result in offensive rebounds or threes.You can see the proportions on everything, the points per possession on everything.
    “You’re essentially taking three data sets and combining them to produce that report. There’s the stuff that we logged, the stuff that they logged, and the stuff the scorer’s table logged, so you got points, assists, and rebounds and all that stuff; you have shot locations—in college, based upon us tagging it; in the pros, they do it, so we just use their locations. And then you have all the play-type information we log, as well as the defensive side of the ball—who was guarding the play and what happened. Who the players are, what the play type was, where on the floor were they, what direction did they go, what was the move that was used. And then what was the ultimate result, and that’s all tied to the scorer’s table data—the stats feed—so we know who had the assist, whether it was a three or a two. We don’t have to tag all of that since it’s integrated data feeds.
    “The result is you have a report that tells you what your team or the opposing team does, what proportion, how good they are, what they get out of it, how they set up, etc. And any way you want to, you can click on a matching data point and get the related video.”
    Barr said he is aware of what companies like Second Spectrum are doing—in fact, Dallas Mavericks owner Mark Cuban, an investor in Synergy, brought the two parties together for a bit for potential collaboration—and, really, Synergy is providing similar types of data, similar access to video clips, and similar ease of use/accessibility for the end user. Barr makes sure his loggers also use “coach-speak,” so coaches are comfortable with the terminology returned in the queries.
    While neither CEO specified his exact price points, conversations with teams that utilize their products confirm that Synergy is more affordable than Second Spectrum’s solution, which certainly has some appeal. There also are differences in the outputs. Synergy’s output, while really robust and increasingly aided by data visualization, doesn’t have Second Spectrum’s same granularity, as plays on Synergyare tagged according to the final action that leads to a shot, foul, or turnover, rather than breaking down the possession into multiple elements. Also, while you are able to pull up sequences of video like the Chris Paul example earlier, each clip is of the entire possession. If you want to carve out more specific time periods within a possession, you would need to go into Synergy’s nice video-editing capabilities to do that.
    The quality of any output, though, is dictated by the quality of the data being used to generate it, and as such, the principal discussion in comparing the products of machine learning versus human loggers centers around the concept of “what is good enough?” While there are a few NBA teams that have brought most things in-house and hired a slew of programmers and data scientists to extract value from all of the different data being collected, most NBA teams don’t require—or want, for now—that level of rigorousness. A comprehensive outsourced solution with an acceptable standard of quality is a perfectly fine solution for them. They get much of the benefit without a lot of the operational headaches of hiring up and maintaining a database that still requires integration across other platforms to match the capabilities of top third-party providers.
    Barr believes his loggers’ accuracy is more than good enough. He touts the company’s rigorous standards for quality assurance, where data tags go through a series of second checks and global spot-checking for accuracy, and also he knows that if his work wasn’t accurate enough, he would hear about it directly from the thousands of coaches he works with. That said, Barr also understands the benefits of better technology, so he’s interested in the ongoing tech-driven