The obvious problem was that there are a ton of free parameters involved and tons of branching. Every little action creates a new branch of possibilities with its own set of probability distributions. So even if (as they describe in the article) helping out more often decreases the likelihood of the current ball handler making a shot, how does that propagate through the rest of the possession?
The 82-game NBA schedule really helps to generate large enough sample sizes about players.
I could see it being potentially possible to just use average data, but if your rec league is anything like mine, talent ranges from a guy can credibly fake a three and then dunk after one dribble to guys that can barely get up and down the court.
It will be interesting with this huge push in basketball over the past couple years to see where this type of analysis leads. The NBA model right now is pretty simple: get two or three superstars, align them with solid role players, and play in championships. It's hard to imagine analytics pushing a team like Houston to be able to beat a team like Miami or Oklahoma City in a seven-game series because the talent gap is so substantial. Houston can play a smarter game but the other teams still function better. What I could see happening, however, if a team like Oklahoma City, while slightly less talented than Miami, can implement insights from this analysis to raise their EV, it might overcome the slightly smaller talent gap. Even in that small sense, it makes more to spend a couple million a year on analytics than it does to pay an average NBA player several million. Since the NBA has both a salary cap and maximum contracts, it pushes the price of an average play up quite a bit, so better value may be had by raising the effectiveness of your current talent than trying to bring in new players.
When the system gets more optimized and easier to use, the role of a coach & GM could get diminished, and with it, their salaries. Of course they would do everything in their power to stop that.
As someone who is on the periphery of working in a professional sport in both analytics and player development, the simple answer is the fact that market forces are comparatively weak here. You have monopolies with a ton of inertia in doing things the same way, plus a lot of the decision-makers are luddites in nature who think the human element is the single most important factor.
Times are changing as the economics of sports tightens and becomes more efficient, but it's not like there are ways to disrupt the market openly. The Dallas Mavericks (Cuban) and the Houston Rockets (Morey) are the ones leading the charge in the NBA, just like the Oakland Athletics (Beane), Cleveland Indians (Shapiro), and Tampa Bay Rays (Friedman) led the charge in MLB.
The analytics vs. coaching issue is a real one too, but don't discount owners being cheap.
I can imagine facilities like hockey rinks buying the cameras and selling the service to the teams that play there, but not at that price. My impression of hockey rinks is that they're not terribly profitable. Most of the ones I've played in seem like borderline charities.
I don't think the price will come down, the only people who need it are wealthy and the wealthy can't afford to not have it.